Devices and methods for optimizing personal well-being

Abstract

An apparatus for optically measuring the concentration of a substance or biomarker in a sample, comprising: a contact surface that can be brought into contact with the sample during the measurement process; an optoelectronic component in the form of a plurality of optical emitters for emitting photons; and a plurality of detectors for receiving at least one portion of photons emitted from the emitters and passing through at least one partial volume portion of the sample, wherein the emitters and detectors are on a common plane, and at least nine emitters and at least three detectors are provided, the emitters and detectors are assembled at intervals shorter than 15 mm with respect to the contact surface, and there are at least three wavelength intervals having interval lengths between 2 nm and 20 nm, where at least three peak wavelengths of each emitter are located within each wavelength interval, and within each wavelength interval, at least two of the emitters that are both located within the wavelength interval have a difference of at least 0.5 nm with respect to their peak wavelengths.

Description

[0001] Device and method for optimizing personal well-being

[0002] Description of the problem

[0003] It is widely known that nutrition has a significant impact on human well-being and health. A balanced diet with plenty of fruit and vegetables, for example, reduces the risk of developing common lifestyle diseases such as cardiovascular disease or cancer. The antioxidants contained in fruit and vegetables play an important role in this, acting as free radical scavengers and helping to prevent the negative effects of oxidative stress. The World Health Organization and many national health ministries therefore recommend consuming large amounts of fruit and vegetables daily. The German Nutrition Society, for example, recommends consuming 650g per day.Carotenoids are a substance with strong antioxidant effects and are considered the best marker for the consumption of fruits and vegetables (see Institute of Medicine, National Academies, “Dietary Reference Intakes for Vitamin C, Vitamin E, Selenium, and Carotenoids”, National Academies Press, 2000, hereinafter referred to as Ref. 1).

[0004] Despite numerous recommendations and campaigns by health authorities, doctors, nutritionists, and other public and private institutions, in practice, actual fruit and vegetable consumption is often significantly below these recommendations (see, for example, National Consumption Study II, ed. Max Rubner Institute, Federal Research Institute for Nutrition and Food, Germany 2008, hereinafter referred to as Ref. 2). The associated health costs worldwide are correspondingly high. The question, therefore, is: Are there technical means that can be used to initiate and sustainably promote behavioral change among citizens?

[0005] The quality of diet and the amount of physical activity, for example, play a crucial role in another problem: obesity. In 2015, 2.2 trillion people worldwide were overweight. Between 1980 and 2015, the number of obese people (BMI > 30) doubled. Overweight and obesity are often associated with secondary diseases such as type 2 diabetes mellitus, gout, atrial fibrillation, or coronary heart disease.

[0006] In addition, there are a large number of people worldwide who, while not medically considered overweight, struggle with those extra pounds for aesthetic reasons, and whose well-being suffers greatly as a result of subjectively perceived weight problems. Increasing occupational stress, insufficient exercise, an unbalanced diet, and the consumption of convenience food or fast food instead of cooking their own meals are some of the reasons for unwanted weight gain. Even desperate attempts to lose those extra pounds through dieting and increased exercise usually fail. Here, too, the question arises: Are there technical means or technical support available to help people cope with this problem?

[0007] According to the current state of the art, there are currently only solutions or technical devices that independently address partial aspects of these problems using different technical approaches:

[0008] Cars allow you to check your body weight or even measure your body fat percentage. Pedometers count the number of daily steps as a measure of exercise and use this to determine calorie consumption. Smart watches and fitness watches also measure heart rate and oxygen saturation and inform you when a heart rate is reached during training at which fat loss begins. Apps show distances traveled while cycling and hiking, along with associated elevation profiles, and calculate calories burned from this.

[0009] Monitoring individual aspects with different technical solutions may only provide an incomplete picture if the real physiological networking of these aspects influences the measurement result and the measurement cannot be carried out simultaneously with different systems.

[0010] What is missing is a system that integrates partial aspects of well-being into a measurement process, so that, for example, different aspects of nutrition and lifestyle are monitored simultaneously in order to achieve comprehensive health and well-being in the long term.

[0011] The invention described here shows a technical system that, for example, records various parameters and / or substances in the human body through a common measurement, estimates the physiological state of an individual on this basis and, based on algorithms and collected data, automatically provides individual user recommendations, for example with regard to behavior, nutrition, taking medication or other possible influences that help stabilize or improve the user's well-being.

[0012] Summary

[0013] A spectroscopic device for the non-invasive measurement of substance concentrations or biomarkers in human or animal tissue, skin, or blood, and a method for evaluating the measurement data and deriving recommendations that stabilize and / or improve the user's well-being. Conventional biomarker sensors can generally only determine the concentration of a single substance, usually either with a technically complex device that is not suitable for everyday use or with low accuracy, so that changes in user behavior do not lead to a clear change in the measured values. The device according to the invention, in its exemplary embodiments, enables the non-invasive determination of multiple substance concentrations with a sensor that is so small that it can be integrated into everyday objects such as smartwatches or mobile phones and can partially utilize the hardware available there.

[0014] In a spectroscopic system that aims to determine biomarkers, the emitters and detectors must emit and detect photons in wavelength ranges in which the desired biomarkers absorb photons. To determine the concentration of these biomarkers, more than one emitter and detector are required. According to the state of the art, the measurement accuracy is increased when emitters with the same emission spectrum are present multiple times on the sensor. Surprisingly, it has now been found that the measurement accuracy improves significantly when the emission spectrum of these emitters differs within the boundaries of an interval, e.g., in terms of their peak wavelength or half-width. Emitters that are located within a common interval are considered to be approximately identical emitters. A sensor that detects the concentration of different biomarkers simultaneously has several intervals with approximately identical emitters.The intervals then collectively cover the wavelength range required for biomarker detection. The same applies to multiple detectors on a sensor.

[0015] This application presents a method which exploits the properties of such a device to increase measurement accuracy. This improvement can go so far that, in addition to displaying the measured values, behavioral recommendations can also be automatically calculated from the measured data. These could, for example, be nutritional recommendations. Such changes often occur only slowly because the body has its own storage capacity for many substances, so that even a significant change in user behavior only a slow change occurs. If the system can reliably measure small changes, it can still give the user timely feedback on their behavior. Positive behavior can be praised and negative behavior reminded, so that the user is highly motivated, for example to eat healthily.This invention is considered an optimization of the invention already known in patents EP 3013217; EP 3175783; US 10,416,079; US 11,08,5876 and applications US 17 / 396,556, EP 4005469A1. All aspects presented in this invention can therefore be combined with the embodiments mentioned in this invention. The disclosure of this invention is to be considered part of this disclosure.

[0016] Some of the particularly advantageous embodiments of the invention can only realize their full potential when a novel, particularly advantageous method for evaluating the measurement data is used. Since this method is partly based on machine learning methods, the following section presents the state of the art in this area.

[0017] Conventional machine learning methods rely on the uniform and consistent acquisition of raw data to be processed. Each raw data set has the same form, and each data point in the data set always represents the same information. However, this is often not the case with sensors. Due to fluctuations, including manufacturing inaccuracies and / or failure of individual emitters or detectors, the raw data sets from different sensors differ from one another. These deviations make the raw data sets no longer uniform and consistent from a machine learning perspective, causing conventional methods to introduce further inaccuracies.

[0018] For conventional procedures, missing data are usually interpolated (ART Donders, GJ van der Heijden, T. Stijnen, and KG Moons, “Review: A gentle introduction to imputation of missing values,” Journal of Clinical Epidemiology, vol. 59, no. 10, pp. 1087-1091, 2006, hereinafter referred to as Ref. 3) or inaccurate data are corrected using further machine learning methods (PK Sharpe and RJ Solly, “Dealing with missing values ​​in neural network-based diagnostic systems,” Neural Computing & Applications, vol. 3, no. 2, pp. 73-77, Jun 1995, hereinafter referred to as Ref. 4).

[0019] Some machine learning methods, the so-called “Convolutional Neural Networks” (CNN) (Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, “Gradient-based learning applied to document recognition,” Proceedings of the IEEE, vol. 86, no. 11, pp. 2278-2324, 1998, hereinafter referred to as Ref. 5) can process such inconsistencies and inaccuracies with the help of continuous filter kernels (DW Romero, A. Kuzina, EJ Bekkers, JM Tomczak, and M. Hoogendoom, “Ckconv: Continuous kernel convolution for sequential data,” CoRR, vol. abs / 2102.02611, 2021, hereinafter referred to as Ref. 6), (KT Schütt, P.-J. Kindermans, HE Sauceda, S. Chmiela, A. Tkatchenko, and K.-R. Muller, “Schnet: A continuous-filter convolutional neural network for modeling quantum interactions,” in Proceedings of the 31st International Conference on Neural Information Processing Systems, 2017, p. 992-1002. hereinafter referred to as Ref.7), (W. Wu, Z. Qi, and L.Fuxin, “Pointconv: Deep convolutional networks on 3d point clouds,” in 2019 IEEE / CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 9613-9622 (hereinafter referred to as Ref. 8). Such CNNs exhibit what is known as translation invariance. Translation invariance means that the result of the method is independent of the position of the input.

[0020] The sensor principle used here belongs to the class of MSRRS sensors (MSRRS = Multiple Spatially Resolved Reflection Spectroscopy; see patent numbers mentioned above).

[0021] A new aspect of this application is the representation of MSRRS sensor data as a collection of values, each with a "position" in the measurement range. This position is advantageously defined by its associated wavelength and emitter-detector distance. Considering the radiation and detection directivity can be a further position parameter.

[0022] However, since a shift in the measurement points in wavelength or emitter-detector distance implies a change in the significance of the values ​​(thus the data is position-dependent), the translation invariance of CNNs is explicitly counterproductive for the evaluation of data from MSRRS sensors. This is a disadvantage of previously known approaches.

[0023] In order to exploit the advantageous properties of continuous filter kernels for the evaluation of MSRRS sensor data, a novel machine learning method is presented.

[0024] Previous work on continuous filter kernels primarily focuses on their application in CNNs. In Ref. 6, continuous filter kernels are used to process various types of inconsistently acquired sequential data. Furthermore, different types of continuous filter kernels are analyzed and compared. Ref. 7 uses continuous filter kernels in CNNs to represent and process atoms in a non-grid-bound manner. In Ref. 8, continuous filter kernels are used to directly process three-dimensional point clouds without prior rasterization.

[0025] Continuous filter kernels are advantageously represented by dedicated neural networks. Analysis of the usability of neural networks as a learnable representation of a continuous function, a so-called “implicit neural representation,” is known from (JJ Park, P. Florence, J. Straub, R. Newcombe, and S. Lovegrove, “Deepsdf: Learning continuous signed distance functions for shape representation,” in 2019 IEEE / CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 165–174, hereinafter referred to as Ref. 9), (K. Genova, F. Cole, A. Sud, A. Sama, and T. Funkhouser, “Local deep implicit functions for 3d shape,” in 2020 IEEE / CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2020, pp. 485–56).

[0026] 4865. hereinafter referred to as Ref. 10) for the representation of signed distance functions, which are required to represent three-dimensional geometry. In (V. Sitzmann, JNP Martel, AW Bergman, DB Lindell, and G. Wetzstein, “Implicit neural representations with periodic activation functions,” in Proceedings of the 34th International Conference on Neural Information Processing Systems, 2020. hereinafter referred to as Ref. 11), a network architecture, called SIREN, is presented as an implicit neural representation, which is suitable for generic data, including audio, images, and signed distance functions. Based on the use of these basic methods for kernels, a novel architecture for neural networks is presented that enables higher precision of the substance concentration to be measured by taking differences between sensors into account.

[0027] Short description of the characters

[0028] Further advantages of the invention will become apparent from the description and the figures. Likewise, the features mentioned in the text and those contained in the figures can be used individually or in combinations. The embodiments shown and described are not intended to be exhaustive, but rather serve as examples for describing the invention.

[0029] Fig. l-la shows an embodiment of a sensor (20) with 6 emitters (1) and 3 detectors (2) in plan view (Fig. la) and section (Fig. l). It has a three-dimensional sensor surface element component (3) that is in contact with the skin (4) and is preferably identical in size to the sensor surface. The area (3a) occupied by the sensor surface element and the area (3b) occupied by the emitter and detector on the circuit board (6) are shown. In a preferred solution, the emitters can emit photons in different wavelength ranges, and the detectors can detect photons in different wavelength ranges. The sensor surface element 3 can be made of transparent material or it can be made of transparent and non-transparent parts. It has a thickness (3.1). The surface of the skin (4.1) is in at least partial contact with the sensor surface element (3) during the measurement. Fig.2-2a The figures show a cross-sectional view of an embodiment of a sensor (20) with at least two emitters (1) and one detector (2), in which the three-dimensional sensor surface element (3) in contact with the skin (4) has one or more convex curvatures toward the skin. In Fig. 2a, there are two convex curvatures toward the skin, while in Fig. 2 there is only one convex curvature. Fig. 2 is an example of how the curvature can extend over the entire sensor. The emitters (1) and detectors (2) are mounted on the circuit board (6).

[0030] Figs. 3-3a show a cross-sectional view of an embodiment of a sensor (20) with at least two emitters (1) and a detector (2) on a circuit board (6), in which the three-dimensional sensor surface element (3) in contact with the skin (4) has a concave curvature toward the skin. In Fig. 3a, there are two concave curvatures toward the skin, whereas in Fig. 3, there is only one concave curvature that extends across the entire sensor.

[0031] Fig. 4-4a show an embodiment of a sensor (20) with 6 emitters (1) and 3 detectors (2) mounted on a circuit board (6) in a top view (Fig. 4a) and a section (Fig. 4). There are many ways to select the shape of the cavities. In the example shown here, the three-dimensional sensor surface element (3) has partially beveled corners arranged in this way. By adapting the shape of the sensor surface element 3 in this way, different beam directions can be generated or openings (3.2) of different geometries can be formed above the sensor components. An opening is understood to mean a passage for light. This can also be formed by a transparent material. The sensor surface elements are in contact with the outermost layer of the skin (4.1). In Fig. 4a, the sensor components (1, 2) are shown with exemplary geometrically different shapes of the openings (3.2).In a preferred solution, the emitters (1) can each emit photons in different wavelength ranges, although it is not specified here which emitter emits which wavelength. In a preferred variant, the detectors (2) can detect photons in different wavelength ranges.

[0032] Fig.5-5a show, as in Fig.4, an exemplary sensor (20) with 6 emitters (1) and 3 detectors (2) arranged on a circuit board (6), in a top view (Fig.5a) and a section (Fig.5). The three-dimensional components (5) are components made of a material that is not transparent. Preferably a material that is almost impassable for photons. It can be a single element (5) or several individual elements. The non-transparent elements (5) and the circuit board (6) enclose the sensor components in such a way that when, for example, a hand is placed on the sensor, the emitted photons have to pass through the skin (4) before they can be detected by the detector. A cavity (8) is formed above the sensor components (1 and 2), which cavity can be filled, for example, with a gas, e.g. air, or another transparent material.The sensor surface elements (3) through which photons can pass have different geometric shapes due to the geometry of the components (5). Component (5) and transparent parts of the sensor surface elements (3) do not form any height differences compared to the skin. The skin surface (4.1) can therefore lie flat on the sensor. Fig. 5a shows a top view of the sensor components as a dashed line above which the sensor surface elements (3) are located. In a preferred solution, the emitters can emit photons in different wavelength ranges and the detectors can detect photons in different wavelength ranges. Transparent elements (3) with the thickness (3.1) mechanically close the cavities with the height (3.3) in which the optoelectronic components are located, but allow photons to enter and exit.

[0033] Fig.6-6b show, as in Fig.5, 5a, an exemplary sensor (20) with 6 emitters (1) and 3 detectors (2) in plan view and section, in which three-dimensional components (5) which are almost impassable for photons and sensor surface elements (3) enclose the sensor components in such a way that when, for example, a hand is placed on the sensor, the emitted photons have to pass through the skin (4) before they can be detected by the detector. In Fig.6, the sensor surface element (3) is arranged in such a way that, compared to the component (5), there is a height difference (3.3) in the direction of the skin (4) and a cavity (8) is created above the sensor components (1, 2). Fig.6b shows an alternative in which the sensor surface elements are, for example, subsequently introduced into the enclosed spaces in which the sensor components (1, 2) are located, so that there is no longer a cavity above the sensor components.Figure 6a shows the sensor components and the geometric shape of the sensor surface elements (3) in a top view as a dashed line. In a preferred solution, the emitters can emit photons in different wavelength ranges, and the detectors can detect photons in different wavelength ranges. The remaining reference numerals have the same meaning as in Figure 5.

[0034] Figs. 7-7a show an exemplary sensor (20) in which the enclosed spaces formed by component (5) and sensor surface elements (3) each contain either 1 emitter (1), 2 emitters, or 2 detectors (2). In total, the sensor has 9 emitters and 6 detectors. In a preferred version, the emitters can emit photons in different wavelength ranges, and the detectors can detect photons in different wavelength ranges. Fig. 7a shows the arrangement of emitters and detectors of the sensor in the enclosed spaces. Fig. 7 shows that there is no step between component 5 and sensor surface element (3) in the direction of the skin (4) or the outer layer of the skin (4.1). However, this sensor can have openings (3.2) in the sensor surface element. One opening is shown in Fig. 7.The dashed lines (1c) symbolically show the path the photons take through the skin before being detected by the detector. The remaining reference numerals have the same meaning as in Fig. 5.

[0035] Fig. 8-8a show, as in Fig. 6b, an exemplary sensor (20) with 6 emitters (1) and 3 detectors (2) in plan view (Fig. 8a) and section (Fig. 8), in which three-dimensional components (5) which are almost impassable for photons and sensor surface elements (3) enclose the sensor components in such a way that when, for example, a hand is placed on the sensor, the emitted photons must pass through the skin (4) before they can be detected by the detector. In contrast to Fig. 6b, however, there is no difference in height between component (5) and sensor surface element (3) in the direction of the skin (4). In Fig. 8a, the sensor components are shown as a dashed line and the size of the sensor surface elements (3) as a continuous line. In a preferred solution, the emitters can emit photons in different wavelength ranges and the detectors can detect photons in different wavelength ranges.The remaining reference numerals have the same meaning as in Fig. 5.

[0036] Fig.9-9c Fig.9 shows an example unit consisting of a sensor surface element and component (5), which can be manufactured using an injection molding process, for example. The thickness of the sensor surface element (3.1) is selected such that when the unit (9) is placed on the circuit board (6), the sensor components (1, 2) do not have direct contact with the sensor surface element. In a preferred solution, the unit (9) is connected to the circuit board (6) at the contact point (6.1) in such a way that photons cannot pass through the contact point. As in Fig.7, 7a, after unit (9) has been placed on, there is 1 emitter, 2 emitters, or 2 detectors in a closed space. In total, the sensor has 9 emitters and 6 detectors. Fig.9a shows a plan view of the arrangement of the sensor components. Fig.9b shows a cross-section of an alternative to the variant in Fig.9.In this case, a unit (5b) consisting of components (5) virtually impervious to photons, which have three-dimensional openings (3.2), is placed on the circuit board and connected to it. Fig. 9c shows a top view of the sensor (20), showing the planar dimensions of the openings (3.2). The arrangement of the sensor components is not shown. It corresponds to the arrangement in Fig. 9a. In a preferred solution, the emitters can emit photons in different wavelength ranges, and the detectors can detect photons in different wavelength ranges. The remaining reference numerals have the same meaning as in Fig. 5.

[0037] Fig.10-10b Figs.10, 10a, 10b show example arrangements of sensor components. The limiting solid angles at which the photons can leave the sensor to penetrate the skin, or at which they can reach the detector from the skin, are determined by an additional component (5a) that is impassable or almost impassable for photons and is located on the component (5b) and in contact with the skin (4). The limiting solid angles are shown as dashed arrows. The angles (5.1) show the limits for the angles of movement that can occur in the interface between the circuit board and the emitted or detected photons. The differences between the three figures lie in whether and where transparent parts of the sensor surface elements (3) are included. Fig.10 does not have a sensor surface element. The additional component (5a) has three-dimensional openings (3).2), through which the photons can pass through the component (5a). This also applies to Fig. 10a. However, in this sensor, sensor surface elements through which the photons can pass are located between the components (5), so that the sensor components (1, 2) are located in completely enclosed spaces (8). In Fig. 10b, the sensor surface elements (3) are located in the openings of the additional component (5a). Therefore, in this variant, the sensor components are also located in enclosed spaces. In a preferred solution, the emitters can emit photons in different wavelength ranges, and the detectors can detect photons in different wavelength ranges. The remaining reference numerals have the same meaning as in Fig. 5.

[0038] Fig. 11 The figure shows an exemplary arrangement of the sensor components (1, 2). Compared to Fig. 10a, a transparent material (7) with a convex shape is located on the additional component (5a), which consists of material that is impermeable or almost impermeable to photons. Between the transparent material and the additional component (5a), a cavity (8) is formed, which can be filled with a gas, for example, air. In an alternative and likewise preferred variant, the transparent material (7) can also be a component that rests completely on the component (5a), so that no cavity (8) is created. In a preferred solution, the emitters can emit photons in different wavelength ranges, and the detectors can detect photons in different wavelength ranges. Other reference numerals have the same meaning as in Fig. 10.

[0039] Fig. 12-12a The figure shows an exemplary arrangement of sensor components (1, 2). Between the components (5), which are impassable or almost impassable for photons, there are no sensor surface elements passable for photons. The sensor components (1, 2) are therefore located in enclosed spaces that are open towards the skin (4) or the outer layer of the skin (4.1). In the preferred variant shown as an example, additional components (5a) are arranged in two enclosed spaces such that they are located on the components (5) at a defined distance parallel to one another or almost parallel to one another. The emitted photons can therefore only leave the sensor towards the skin (4) in certain preferred directions.For illustration, the components (5) above the two emitter chambers are arranged orthogonally to each other, resulting in a north-south preferred direction for one chamber, while the preferred direction of the photons leaving the sensor in the other emitter chamber is west-east, as shown in Fig. 12a. The other reference numerals have the same meaning as in Fig. 10.

[0040] Fig.l2b-12b2 The arrangement of the sensor components (1, 2) shown as an example in the figures corresponds to Fig.12a. In the direction of the skin (4), the sensor has a transparent, convex material layer (7) which comes into contact with the outer layer of the skin (4.1) during measurement. The additional components (5a), which are located above two emitter spaces, lie below the layer (7) in the cavity (8). The variants Fig.12b1 and 12b2 show solutions in which the transparent layer (7) is a three-dimensional, transparent component through which the photons can pass, the upper side of which is convexly curved towards the skin (4) and the underside of which is flat towards the circuit board (6). The difference between Fig.12b 1 and 12b2 is that the additional components (5a) in Fig.12b 1 are integrated into the transparent component (7), while in Fig. 12b2 the transparent component (7) rests on the components (5a).The other reference numerals have the same meaning as in Fig. 10.

[0041] Fig.l2b3-12b5 The difference between the sensor shown in this example and Fig.l2b-12b2 is that the sensor has a sensor surface element that is passable for photons. It is located between the components (5) and has no height difference to the components (5) in the direction of the skin (4). In Fig.l2b3, the transparent, convex-shaped material (7) forms a cavity (8) on its underside in which the additional components (5a) are located, while the curved upper side is in contact with the outer layer (4.1) of the skin. In Figures 12b4 and 12b5, the transparent material (7), as described in Fig.12b1, forms a three-dimensional, transparent component with a convex curvature in the direction of the skin. The difference between the two figures is that the additional material (5a) in Fig.12b4 is integrated into the component (7), while in Fig.l2b5 the component (7) rests on the component (5a).

[0042] Fig. l2c-12c5 The arrangements shown in the example of Fig. 12c to 12c5 correspond almost identically to Fig. l2b-12b5. The difference lies in the curvature of the transparent material (7) or the transparent component (7). In Fig. 12c to 12c5, the curvature is concave, so that less extraneous light can penetrate between the outer skin layer (4.1) and the component (7) when the sample, e.g. the hand, is placed on it and influence the measurement result. It will be obvious to a person skilled in the art that the component (7) has a light protection device, e.g. a film impervious to photons, wherever ambient light can penetrate directly into the transparent material or component.

[0043] Fig. l2d-12e The exemplary arrangement of the sensor components (1, 2) is shown in Fig. l2e. Figs. l2d-12d5 essentially correspond to Figs. l2b-12b5. The difference is that an additional component (5a) limits the solid angle under which photons are emitted or photons emerging from the skin (4) can reach a detector. In the example shown, the middle detector (2) is additionally enclosed by component (5a), as can be seen in Fig. 12e. This component also limits the solid angles of the two emitters (1) located next to the detector when they emit photons, as can be seen for example in the sectional drawing of the emitter to the left of it. The steepness of the solid angle when emitting photons is no longer determined by the edge of the surrounding component (5), but by the position of the additional component (5a) located on the component (5), as shown by the dashed arrow.In a preferred variant, such an additional enclosing component (5a) can be located above more than one detector. In a further preferred variant, this additional enclosing component (5a) is located above all detectors. The same applies to the components (5a) located above the emitters, which are shown in Fig. 12e with different orientations above two emitters. In a preferred variant, they can be located above one or more than one emitter. In a further preferred variant, these components (5a) have the same orientation. In a further preferred variant, they are located above one or more than one detector, wherein they can have the same and / or different orientations.

[0044] Fig. 13-13a show advantageous procedures and definitions for determining the emitter-detector distances (1c), which are also referred to elsewhere in this document as photon light paths. In one variant, the emitter-detector distances (1 c 1 ) and (1c4) can be the same. In a particularly advantageous variant, the emitter-detector distances (1 c 1 ) and (1c4) are approximately the same. In a particularly advantageous variant, the emitter-detector distance (lei) of one manufactured sensor is different from the emitter-detector distance (lei) of another manufactured sensor. In a preferred variant, this applies not only to one distance (e.g., Icl) but to a plurality of emitter-detector distances.

[0045] Fig.14 Fig.14 shows an example of the distribution of the peak wavelengths of the emitters. The wavelength in nm is plotted along the horizontal (x) axis. The relative intensity of the emission is plotted along the vertical (y) axis. Four intervals (10) of peak wavelength (1a) of approximately identical emitters can be seen. These intervals are as follows: (10cb) lies in the blue light range. (10cg) lies in the green light range. (10er) lies in the red light range. (10cir) lies in the near infrared light range. The graph shows the relative intensity of the light emission of the emitters in the example. The interval length (10) is 10nm in each case, where (10a) describes the lower limit and (10b) the upper limit of the interval length. Together, the four intervals cover a wavelength range (11) of 400 nm, where (11a) describes the lowest lower limit of the wavelength range and (Hb) the highest upper limit of the wavelength range.The interval gaps (10c) between the intervals are different.

[0046] Fig.14a Fig. 14a shows an example of four intervals (10) of the wavelength ranges covered by the half-width of the emitters. The wavelength in nm is plotted along the horizontal (x) axis. The relative intensity of the emission is plotted along the vertical (y) axis. Four intervals (10) of approximately identical emitters can be seen. These intervals are as follows: (10cb) lies in the blue light range. (10cg) lies in the green light range. (10cr) lies in the red light range. (10cir) lies in the near infrared light range. The intensity limit (1b) defines which wavelength range lies within the half-width of an emitter. The range (10) and its interval length show the wavelength range of approximately identical emitters in which at least one of the emitters emits radiation of the corresponding wavelength with an intensity of at least 0.5.Although the emitters in an interval all have the same half-width, the wavelength range covered by the respective half-width varies from emitter to emitter within an interval. The four intervals, each with a different interval length (10), are located in the blue, green, red, and near-infrared wavelength ranges. The interval gaps (10c) between the intervals vary. The boundaries (10a) and (10b) indicate the boundaries of the intervals. Together, the four intervals cover a wavelength range (11), where (11a) describes the lowest lower limit of the wavelength range and (11b) the highest upper limit of the wavelength range.

[0047] Fig. 14b shows an example of two intervals, each with different peak wavelengths (la) of approximately identical emitters, where the emitters of an interval are not distributed over the entire interval length (10). The other reference numerals correspond to Fig. 14. Fig. 14c shows an example of two intervals (10) with different peak wavelengths (la) of approximately identical emitters, where a not approximately identical emitter (Ul) is located between the two intervals. In each of the intervals, there are three approximately identical emitters, whose peak wavelengths do not cover the entire interval length. The other reference numerals correspond to Fig. 14.

[0048] Fig. 14d shows an interval (10) of the wavelength ranges covered by the full width at half maximum (FWHM) of the emitters (1b) of three approximately identical emitters in the wavelength range from 538 nm to 576 nm, and the full width at half maximum (FWHM) of two not approximately identical emitters, which lie in the wavelength range below or above the interval. The interval length (10) is 38 nm and is not completely filled by the three emitters. The dashed lines show that the wavelength range covered by the full width at half maximum of the three emitters lies within the limits 10a (538 nm) and 10b (576 nm) of the interval. The other reference numerals correspond to Fig. 14a.

[0049] Fig. 14e shows an example of five peak wavelength intervals of approximately identical emitters with different peak wavelengths, each containing two emitters. The interval length is 13 nm and 15 nm, respectively. The reference numerals correspond to Fig. 14.

[0050] Fig.15 shows an example of an interval (10) of 3 approximately equal detectors whose emitted current at a certain wavelength and a received power of 10mW / cm 2 between 0.2 mA, lower limit (10a), and 10 mA, upper limit (10b). Along the horizontal (x) axis, the light intensity arriving at the sensor is in mW / cm 2 This is shown for an example of detectors with an integrated gain factor in mA. However, detectors without amplifiers can also be used in an advantageous variant. In such cases, the relationships apply analogously. The current output by the detector is plotted along the vertical axis (y). Detector (2.1) delivers 0.6 mA at a received power of 10 mW, detector (2.2) delivers 3 mA, and detector (2.3) delivers 7.5 mA, all at the same wavelength. The figure has logarithmically scaled scales.

[0051] Fig. 15a shows another example. The reference numerals correspond to Fig. 15. Fig. 15a shows another criterion for assigning detectors to an interval of approximately identical detectors. This criterion is the emitted current at the same wavelength and received photon power, which must differ among the detectors by a certain factor (12). Along the horizontal (x) axis, the light intensity arriving at the sensor is plotted in mW / cm. 2This is shown for an example of detectors with an integrated amplification factor in the unit mA. However, detectors without amplifiers can also be used in an advantageous variant. In such cases, the relationships apply analogously. The current output by the detector is plotted along the vertical axis (y). For example, the current output by detector (2.1), at 0.6 mA, is only 1 / 5 of that of detector (2.2), or 12.5 times lower than the current output by detector (2.3), which is 7.5 mA.

[0052] Fig. 16 The example in this figure shows the peak wavelength (2b) of two non-approximately identical detectors that differ in their peak wavelength. The wavelength in nm is plotted along the horizontal (x) axis. The relative sensitivity of the detectors is plotted along the vertical (y) axis. The difference in the peak wavelengths between detector (2.5) and detector (2.4) is 360 nm.

[0053] Fig.16a The example shows a combination of two non-approximately identical detectors with approximately identical emitters. The wavelength in nm is plotted along the horizontal (x) axis. The relative sensitivity of the detectors is plotted along the vertical (y) axis. The basis is Fig.16 and the reference numerals have the corresponding meaning. In Fig.16a, four intervals of approximately identical emitters are shown, based on the half-width (1b). These are the intervals from Fig.14a. Fig.16a shows the advantages of combining non-approximately identical detectors with approximately identical emitters. Preferably, the combination achieves a higher spectral resolution.

[0054] Fig. 17 shows an example of the system's user interface. The screen display is in German. Text (1701s) means "measured value." Text (1702s) means "Studies show that people with this carotenoid value need to eat more fruit and vegetables on average every day to meet the WHO / DGE nutritional recommendation." Text (1703s) means "Please replace part of your daily diet with fresh fruit and vegetables. We have determined how much more fruit and vegetables you should eat:." Text (1704s) means "additional daily requirement 290 grams." Shown is an example of how the measurement results for the carotenoid value and the amount of additional fruit and vegetables the user should eat daily over the next four weeks to reach the target value.

[0055] Fig. 17a shows an example of a system user interface. The screen display is in German. Text (1710s) means "Weight management." Text (1711s) means "What are your preferences?" Text (1712s) means "Moderately reduce body weight" and represents, for example, a reduction of 250 kcal less energy intake than the user's energy consumption. Text (1713s) means "Strongly reduce body weight" and represents, for example, a reduction of 500 kcal less energy intake than the user's energy consumption. Text (1714s) means "Maintain body weight" and represents, for example, an energy intake that corresponds to the user's energy consumption. Text (1715s) means "Moderately increase body weight" and represents, for example, an energy intake that is 250 kcal more than the user's energy consumption.Text (1716s) means "significantly increase body weight" and represents, for example, an energy intake that is 500 kcal higher than the user's energy expenditure. The illustration shows a user-defined preference, using the example of weight management. Selectable rates of change are offered. The user can specify their preference, for example, by entering a cross below the category.

[0056] Fig. 17b shows an example of the system's user interface. The screen display is in German. Text (1720s) means "Target daily consumption." Text (1721s) means "Total." Text (1722s) means "Selected preference." Text (1723s) means "Recommended target value, e.g., from the German Nutrition Society." Text (1724s) means "Own target value." Text (1725s) means "Fruit." Text (1726s) means "Vegetables." The figure shows an example input option for a suggested and / or self-selected target value.

[0057] Fig. 17c shows an example of the system's user interface. The screen display is in German. Text (1730s) means: "Nutritional quality." Text (1731s) means: "How quickly do you want to improve your nutritional quality?" Text (1732s) means: "Slow improvement / increasing target value." Text (1733s) means: "Moderate improvement / target value of measured requirements." Text (1734s) means: "Rapid improvement / 2x measured fruit and vegetable requirements." Text (1735s means: "User defines target value ... grams of fruit and vegetables." By entering this value, the user determines how quickly they want to achieve their daily fruit and vegetable intake. A reference value, for example, is the measured carotenoid status, which corresponds to a certain amount of metabolized fruit and vegetables. Carotenoids are considered the best indicator of fruit and vegetable intake.With the "Moderate Improvement" preference, the additional amount of fruit and vegetables the user should consume daily corresponds to the needs determined by measurement. If they select the "Rapid Improvement" preference, they should consume twice the needs determined by measurement. The more fruit and vegetables the user consumes daily, the faster the carotenoid levels measured in tissue and blood change. They can specify their preference for a speed category, for example, by entering a cross below the category.

[0058] Fig. 18 shows an example of the system's user interface. The screen display is in German. Text (1801s) means: "Suggestions for a day's meals." Text (1802s) means: "Selection." Text (1803s) means: "Meal." Text (1804s) means: "Recipe No." Text (1805s) means: "Dish." Text (1806s) means: "Breakfast: Banana Rolls (Vegetarian)." Text (1807s) means: "Photo of the meal." Text (1808s) means: "Main course: Baked cod from the oven with vegetables (Vegetarian)." Text (1809s) means: "Photo of the meal." Text (1810s) means: "Main course: Green risotto with spring vegetables (Vegan)." Text (1811s) means: "Photo of the meal." Text (1812s) means: "Snack." Text (1813s) means: "Daily balance." Text (1814s) means: "815 grams, 0 grams, 125 grams." Text (1815s) means: "How well do the dishes correspond to your chosen preferences?" Text (1816s) means: "Weight management." Text (1817s) means: "Moderate weight loss."Text (1818s) means: "Dietary quality." Text (1819s) means: "Moderate improvement." Text (1820s) means: "How well do the meals support your long-term well-being." Text (1821s) means: "Healthy Food Relation," which stands for "a proportion of healthy food." Text (1822s) means: "Effect on your body weight." Text (1823s) means: "Vegetables." Text (1824s) means: "Fruit." Text (1825s) means: "ORAC." Text (1826s) means: "Fish." Text (1827s) means: "Meat." Text (1828s) means: "You are losing weight." Text (1829s) means: "15,199 pmol TE." Text (1830s) means: "-759 cal." Text (1831s) means: "Total fulfillment level." Text (1832s) means: "Restart monitoring." Text (1833s) means: "Date 20.08.2022." Text (1834s) means: "Save daily balance." The user interface provides an example of the information the user receives when recipes orComplete dishes from a restaurant are suggested for a full day's food intake, and the user selects specific suggestions. The daily selection is automatically evaluated based on the measurements taken by the measuring device and the user's selected preferences and higher-level categories, for example, and displayed as a graphic. The selection and evaluation for one day is shown as an example. The user can make the selection for more than one day, for example, for a period of one week, and can, for example, have a corresponding shopping list generated or have the ingredients delivered by a supplier.

[0059] Fig. 19 shows an example of the system's user interface. The screen display is in German. Text (1901s) means: "Weight management history - ratio of kcal intake to daily energy requirement." Text (1902s) means: "Target kcal reduction achieved." Text (1903s) means: "Reduction < than target." Text (1904s) means: "Target kcal reduction achieved." Text (1905s) means: "History period in days." Text (1906s) means: "kcal intake greater than energy requirement." Text (1907s) means: "Start 02 / 08 / 2022." Text (1908s) means: "On average, your kcal reduction is much better than your 4-week goal." Text (1909s) means: "Target -250." Text (1910s) means: "current average -456." Text (1911s) means: "Today, August 20, 2022." As an example of automated, digital nutrition advice, Fig. 19 shows the user the results of their weight management over the past 18 days, e.g., in the form of a bar chart.The graph shows the relationship between the calorific value of the food consumed (in kcal) and the user's daily energy requirement (in kcal) based on their selected preferences. Relative to a zero line, on all days with negative values, the user consumed less than their average daily consumption. On these days, they are losing weight. Whether they have reached their set target of -250 kcal / day is indicated by the dashed line. On all days on which the bar breaks the line, they have reached their self-defined target. In this example, the user has decided that the calorific value should be 250 kcal below their daily energy requirement, which was the case on 6 days. The automated nutritional advice also shows them that, on average, they have significantly fallen short of their target / preference over the last 18 days. The freely selectable maximum observation period in this example is 30 days.

[0060] Fig. 19a shows an example of the system's user interface. The screen display is in German. Text (1920s) means: "Calculation of the user's daily average energy consumption." Text (1921s) means: "Basic metabolic rate." Text (1922s) means: "Performance metabolic rate."

[0061] (Basal metabolic rate*(PAL value-l))”. Text (1923s) means: “Energy consumption (incl. factor for food intake)”. Text (1924s) means: “Harris-Benedict”. Text (1925s) means: “(kcal / day)”. Text (1926s) means: “(kJ / day)”. Text (1927s) means: “WHO & FAO*”. Text (1928s) means: “DGE**”. Text (1929s) means: “Mark preference with ‘X’”. Text (1930s) means: “Mean of the various calculations for daily energy consumption in kcal”. Text (1931s) means: “*FAO=Food and Agricultural Organization of the United Nations” and is an explanatory text for Text (1927s). Text (1932s) means: "* *DGE = German Nutrition Society" and is an explanatory text for text (1928s). This figure shows an example of the automatic calculation of the user's average energy consumption, where basic data such as age and gender have been previously entered by the user.The user has the option of selecting a specific calculation method or calculating daily energy consumption as an average of four calculation methods. In this example, the user has chosen the average of various calculation methods.

[0062] Fig. 20 shows an example of the system's user interface. The screen display is in German. Text (2001s) means: "History of Carotenoid Measurements." Text (2002s) means: "History Period in Days." Text (2003s) means: "Carotenoid Measurements." Text (2004s) means: "Reduce / Stop Supplementation." Text (2005s) means: "Target Range." Text (2006s) means: "Average in: D, A, CH," which stands for Germany, Austria, and Switzerland. Text (2007s) means: "Critical Zone." Text (2008s) means: "Start 02.08.2022." Text (2009s) reads: "Your average carotenoid level is only slightly above the mean—but the values ​​show an increasing trend." Text (2010s) reads: "Today, August 20, 2022." As an example of automated, digital nutritional advice, Fig. 20 shows the user their carotenoid readings for the past 18 days, determined using the measuring device.Both a target range for the measured values ​​and a critical zone that should definitely be exceeded are specified. To better classify the user's own measured values, the average values ​​of users from other countries, such as Germany, Austria, and Switzerland, are also displayed. The freely selectable maximum observation period in this example is 30 days. By mutual agreement, users can also display their measured values ​​to each other for guidance or motivational support. In an advantageous variant, this can also be enabled for other information displayed by the system according to the invention.

[0063] Fig. 21 shows an example of the system's user interface. The screen display is in German for example. Text (2101s) means: "History of fulfillment - How well the meals of a day correspond to all of your selected goals." Text (2102s) means: "Degree of fulfillment." Text (2103s) means: "Recipe No. :." Text (2104s) means: "Breakfast." Text (2105s) means: "Main Course 1." Text (2106s) means: "Main Course 2." Text (2107s) means: "Snack." Text (2108s) means: "Start 02 / 08 / 2022." Text (2109s) means: "On average, you achieve an acceptable fulfillment of all your goals with your meals." Text (2110s) means: "History period in days." Text (2111s) means: "Current average 76.1%." Text (2112s) means: "Today, August 20, 2022." As another example of automated, digital nutritional advice, Fig. 21 shows the user how well the meals they have chosen over the past 16 days correspond to their various preferences.The goals have been met and the resulting overall level of fulfillment. For each day's meals, the respective dishes or recipes are listed, the overall level of fulfillment for each day is presented, and the average fulfillment over the current usage period (16 days) is determined. The freely selectable maximum observation period in this example is 30 days.

[0064] Fig. 22 shows an example of the system's user interface. The screen display is in German. Text (2201s) means: "History of nutritional quality - fruit and vegetable consumption and requirements." Text (2202s) means: "Fruit / vegetable proportion of selected recipes." Text (2203s) means: "Measured value - additional fruit / vegetable requirement to achieve the DGE recommendation." Text (2204s) means: "Grams of fruit + vegetables." Text (2205s) means: "DGE recommendation 650 / daily." Text (2206s) means: "Start 02.08.2022." Text (2207s) means: "You have exceeded your priority goal for the selected speed of behavior change on average. However, the measured biomarker shows that the equivalent of 650g of fruit and vegetables is not yet present in your body." Text (2208s) means: "History period in days." Text (2209s) means: "Priority: moderate." Text (2210s) means: "Today, August 20, 2022."As another example of digital nutritional advice that the user can have automatically displayed on a display device, Fig. 22 shows the ratio of actual fruit and vegetable consumption to the daily requirement determined with the measuring device over the last 16 days, based on a speed selected by the user (moderate) to achieve the priority goal of 650g / day. The bars represent the fruit and vegetable proportion in the selected recipes or consumed dishes, and the lines represent the additional daily requirement of fruit and vegetables determined with the measuring device. Although the fruit / vegetable proportion is often more than 200g above the target value of 650g / day, the measuring device determines that the biomarker has not yet accumulated in the user's body to the extent that it corresponds to an equivalent of 650g / g fruit / vegetables.This result reflects, on the one hand, individual metabolism and possible quality issues with the fruit / vegetables consumed, and, on the other hand, the speed of the individual biomarker accumulation process in the user's body. The freely selectable maximum observation period in this example is 30 days.

[0065] Fig. 23 shows an example of the system's user interface. The screen display is in German. Text (2301s) means: "History of Healthy Food Relation - ratio of grams of fruit and vegetables / kcal of the selected meals." Text (2302s) means: "History period in days." Text (2303s) means: "Grams / kcal." Text (2304s) means: "Target value." Text (2305s) means: "Today, August 20, 2022." Text (2306s) means: "Start date: August 2, 2022." Text (2307s) means: "On average, the ratio of fruit and vegetable consumption to the energy value (kcal) of your meals is significantly worse than your target value." Text (2308s) means: "Current average 0.60." Fig. 23 shows an example of digital nutrition advice with automatic calculation of the ratio of fruit and vegetable consumption (e.g., in grams) to the energy value of the meals consumed by the user (e.g., in kcal). In this example, this ratio is called the "Healthy Food Relation."The target value for the gram / kcal ratio is 1.0. In this example, the user hasn't reached it once in the last 16 days. The sample bar chart clearly shows this: No bar reaches the target level of 1 (dashed line). The average over the last 16 days is only 0.6. The freely selectable maximum observation period for displaying fruit / vegetable consumption was set to 30 days in this example.

[0066] Fig. 24 shows an example of the system's user interface. The screen display is in German. Text (2401s) means: "History ORAC value (pmol TE) - selected meals of a day." Text (2402s) means: "History period in days." Text (2403s) means: "ORAC value." Text (2404s) means: "7,000 pmol TE." Text (2405s) means: "Today, August 20, 2022." Text (2406s) means: "Start: August 2, 2022." Text (2407s) means: "On average, the target value of 7,000 pmol TE / day was significantly exceeded." Text (2408s) means: "Pulse 197%." Text (2409s) means: "Current average per day." As another example of digital nutritional advice that the user can have automatically displayed on a display device, Fig. 24 shows the automatic calculation of ORAC values ​​for the meals selected by the user during a day. In this example, the target value per day is assumed to be 7,000 pmol TE.The meals selected by the user on a given day usually significantly exceed this target value. The average for the last 16 days is 13,816. The freely selectable maximum observation period for displaying the ORAC values ​​was also set to 30 days in this example.

[0067] Fig. 25 shows the back of a smartphone (1001) with a multi-camera unit (1002). This includes four cameras (1003), (1004), (1005), (1006).

[0068] Fig. 26 shows an example of how the smartphone from Fig. 25 can be expanded into a sensor according to the present invention. For this purpose, several light emitters are arranged in close proximity to the cameras. An example of a light emitter is (1007).

[0069] Fig. 27 shows the smartphone from Fig. 26, supplemented by a scale (1008) and a scale (1009), which facilitates the description of individual emitters. Two example emitters are emitter (1010) and emitter (1011). A detector (1012) is also shown.

[0070] Fig. 28 shows a sectional view through an exemplary embodiment of a sensor integrated into a smartphone. The camera module (1012) shown in the detail consists of an image sensor (1022) which has numerous pixels. These include the pixels (1015) and (1016) chosen as an example. Furthermore, there is at least one lens (1014) which is mounted in a lens holder (1021). The lens holder and lens are preferably movable. A transparent cover (1013) protects the camera. The numbers (1018) to (1020) represent emitters. (1017) is a transparent surface which protects the emitters. This preferably forms a smooth surface with element (1013) and the non-transparent housing parts (5b). The object or sample to be measured (1023) is, in an advantageous variant, human tissue.

[0071] Fig. 29 illustrates a spatial region of the sample traversed by photons using the example of Fig. 28. The numbers have the same meaning as in Fig. 28. In addition, a region traversed by photons is marked with the lines (1024) and (1025).

[0072] Fig.30 explains using the example of Fig. 28 another path traversed by photons

[0073] Spatial region of the sample. The numbers have the same meaning as in Fig. 28. In addition, a region traversed by photons is marked with the lines (1026) and (1027).

[0074] Fig. 31 shows an advantageous structure of an evaluation algorithm. Level (I) shows the raw data. A number i of raw data is assumed. The raw data has a position in a feature space. For clarification and explanation, it should be noted that this is typically not a classic spatial position in the sense of a location. The crosses on the surface each symbolize a raw data value of the i raw data on a two-dimensional feature surface, for example. Level (II) shows an exemplary number k of continuous filter kernels, which represent functions that, in an advantageous variant, determine at least one output value from a majority of the raw data values, taking into account their positions in the feature space. To symbolize the filter kernels, a representation has been chosen as is known from maps that show the elevation of locations on a two-dimensional plane.Different elevations are represented by different color gradations and contour lines. The area over which the filter kernels are displayed corresponds to the area of ​​the raw data features from layer (I). The gray level above each point in the layer symbolizes a weighting applied by the filter kernel. Output values ​​are calculated for the raw data points for the filter kernels. The output values ​​are represented in layer (III) as k vectors with elements w. i kwhere k stands for the number of the filter kernel and i for the number of the raw data point. Level (IV) describes the reduction of the respective vector, preferably to a value for each filter kernel. Preferably, a reduction function is used for this purpose, in a particularly preferred variant, a sum. The reduction function is symbolized by a circle with a "+" sign. Level (V) shows an algorithm (ALG) that calculates an overall result value from the results of level (IV). In an advantageous variant, the algorithm (ALG) can be a multi-layer perceptron. The overall result value (ERG) is shown in level (VI).

[0075] Fig. 32 shows the improvements achieved by an evaluation algorithm similar to Fig. 31 as a function of the number of unusable detectors. The vertical axis (y) shows the mean square of the prediction errors. The horizontal axis (x) shows the percentage of detectors excluded from the evaluation. The left column (cfin) shows the algorithm of the method according to Fig. 31. The right column (mlffn) shows the results achieved with traditional methods. These show significantly larger errors.

[0076] Fig. 33 shows the distribution of the frequency of prediction errors as a histogram depending on the number of unusable emitters when using the advantageous design of the evaluation algorithms. Fig. 31. The vertical axis (y) shows the frequency of error occurrence. The horizontal axis (x) shows the magnitude of the errors. The percentage entered in the respective diagram area indicates what percentage of the detectors were blocked for the measurement evaluation.

[0077] Fig. 34 shows the distribution of the frequency of prediction errors as a function of the number of unusable emitters without using the advantageous embodiment of the evaluation algorithm in Fig. 31. Comparing Fig. 33 with Fig. 34, it can be seen that the frequency of larger errors is significantly increased without using the evaluation algorithm in Fig. 31. Fig. 35 shows, as an example, the housing of a miniaturized measuring device (30) with an exemplary sensor (20). This consists of a unit (9) of transparent parts of the sensor surface element (3) through which photons can pass, and three-dimensional components (5) that are impassable or almost impassable for photons. The measuring device has a removable positioning aid (P) for placing the sample, in this example the hand, on the sensor in such a way that the palm of the hand is measured in a specific area of ​​the ball of the hand.In an advantageous embodiment, the positioning aid (P) can be removed or relocated or replaced with another positioning aid. This preferably allows adaptation to different hand sizes. Furthermore, the measuring device has a socket (3501), e.g. USB. Advantageously, the measuring device has operating elements, e.g. an on / off switch and / or a button for setting up a radio connection. These can be arranged, for example, at locations provided for this purpose (3502). In an advantageous embodiment, openings for mechanical buttons can be provided in the housing. Advantageously, these openings can also be closed in versions that do not require operating elements, as shown as an example in the image.

[0078] Fig. 35a shows the example housing from Fig. 35 from a different perspective. The housing shown has signal LEDs for the WIFI function indicator (Sla), for the measurement progress (Slb), and a status indicator (Sic) (e.g., whether the device is turned on).

[0079] Fig. 36 shows the exemplary sensor (20) from Fig. 35 and Fig. 35a without the transparent parts of the sensor surface element (3). The detectors and emitters of the sensor are shown, located in openings in the component (5b) whose material is impermeable or almost impermeable to photons. For reasons of space, only the detectors are numbered in Fig. 36. The exemplary sensor has 8 single-channel (2) and 1 multi-channel (2, 4) detectors. As an example of the length of a photon path or light path (1c), two dashed lines are shown in Fig. 36. The distance between the two indicates the photon path / light path between an emitter and a detector. The dashed lines identify the center of the emitter or detector. In an advantageous variant, the circuit board is painted together with the electronic components to protect the electronics from moisture. Fig.36a shows the exemplary sensor (20) of Fig.35 with the numbering of the emitters. It has 28 emitters (1.1) that emit photons in a wavelength range, whereby the wavelength ranges can differ. Additional emitters (1.3) can emit photons in three different wavelength ranges, e.g. they can be RGB emitters. In an advantageous variant, the emitters (1.3) can emit yellow, green, and blue light. The emitters (1.3) can differ from one another in terms of the three wavelength ranges they can emit. The sensor has 9 emitters of type 1.3. The emitters (1.1 and 1.3) can be present multiple times within one opening. The sensor (20) contains 4 openings in the non-transparent element (5b) (see corner areas of the sensor), each of which contains an emitter and a detector, while all other openings contain either emitters or detectors.In an opening in the element (5b), a temperature sensor (40) is located, for example, in addition to optoelectronic components. As an example of the length of a photon path or light path (1c), two dashed lines are shown in Fig. 36a. The distance between the two represents the photon path / light path between an emitter and a detector. The dashed lines identify the center of the emitter or detector, respectively.

[0080] Fig. 36b shows that the part of the measuring device (30) numbered (20) is shown in detail in Figures 36 and 36a.

[0081] Fig.37 shows a section through an exemplary design of the sensor surface element.

[0082] It consists of one or more opaque elements (5b) and one or more transparent elements (3). It has a surface that can be brought into contact with the skin (4). The opposite side preferably rests on the circuit board. The side with the circuit board (not shown) is marked (6). In an advantageous variant, the shape of the elements (3) and (5b) has a positive connection that prevents the element (3) from slipping out of the element (5b) in the direction of the skin (4). In an alternative advantageous variant, the shape of the elements (3) and (5b) has a positive connection that prevents the element (3) from slipping out of the element (5b) in the direction of the circuit board (6) (not shown). In a particularly advantageous variant, positive connections prevent any movement of the element (3) relative to element (5b).

[0083] TI Fig. 38 shows an exemplary design of the transparent elements (3) from Fig. 37 or Fig. 35. In an advantageous variant, the gate area (3ag) is arranged such that it is located to the side of the optically used window area. In an alternative advantageous arrangement (not shown in the figure), the gate is centrally located in the window area. In an alternative advantageous arrangement (not shown in the figure), the gate is in the window area, but not centrally located above an emitter. The step (3st) is an advantageous design feature for the positive connection (Fig. 37 5st) already explained in Fig. 37 for fixing the transparent elements (3).

[0084] Fig. 39 shows the elements of Fig. 38 from the bottom. The reference numerals correspond to those in Fig. 38.

[0085] Fig. 40 shows a non-transparent element (5b) matching the transparent elements shown in Figs. 38 and 39. This can preferably have form-fitting elements for fixing (5st). Elements (5p) can be present which facilitate precise positioning of the element (5b) relative to electronic components. In an advantageous variant, the cavities in the component (5b) have bulges (5ab). This can be advantageously used to create space which is required, for example, for sprues of the transparent elements or which is required for electronic components or their connections. In an advantageous variant, the element (5b) can be manufactured by being manufactured in a 2K injection molding process together with the transparent elements (as shown, for example, in Fig. 38). In an advantageous variant, the non-transparent elements are injection molded first, followed by the transparent ones.In an advantageous variant, the plastic of the transparent components has a lower softening temperature than the plastic of the opaque parts. In an advantageous variant, the transparent and opaque components are connected in such a way that no water can penetrate the gap between them to the circuit board.

[0086] Fig. 41 shows an advantageous variant of the construction of the transparent and non-transparent components of the sensor surface. On the left in the image, an opaque component (5b 1) is shown. A transparent component (3) is inserted into this. In an advantageous embodiment, the transparent component is connected to an element (3ag) which connects several or preferably all of the transparent parts. This makes insertion easier, for example, because each transparent part does not have to be inserted individually. The right-hand side of the image shows the component (5b2) being put in place. In an advantageous variant, the parts (5b 1) and (5b2) are connected, e.g. by gluing, welding or locking. In an alternative variant, the elements (5b2) and (3) can also just be clamped between the circuit board and (5b 1). In an alternative variant, (5b 1) and / or (5b2) are connected to (3).In an advantageous variant, the components have a separation point (3tg) where plastic parts not required for the device can be removed. Preferably, the separation process interrupts connections made of transparent material, thus ensuring that light must pass through the sample to travel from the emitter to the detector. In an advantageous variant, parts (3ar) are not incorporated into the final product, but rather removed beforehand, for example.

[0087] Fig. 42 shows an advantageous variant of the structure of the transparent and non-transparent components of the sensor surface. On the left of the image, an opaque component (5b) is shown. A transparent component (3) is inserted into this, which is shown from above and below on the right side of the image. In the center of the image, the transparent components (3) are inserted into the opaque component (5b). In an advantageous arrangement, the shape of the components is designed so that they cannot fall out onto the contact side of the skin. In an advantageous arrangement, the shape of the components is designed so that the transparent components can be supported on the circuit board. In an advantageous embodiment, the non-transparent element also touches the circuit board. In an alternative advantageous embodiment, the circuit board does not touch the elements shown in Fig. 42 directly, but via a layer of adhesive or double-sided adhesive tape.In an advantageous variant, the transparent and non-transparent components can be manufactured in a single 2K injection molding process. In an advantageous variant, the transparent elements are molded first, followed by the non-transparent ones. In an advantageous variant, the plastic of the non-transparent components has a lower softening temperature than the plastic of the transparent parts.

[0088] Fig. 43 shows an advantageous variant of the construction of the transparent and non-transparent components of the sensor surface. On the right in the picture, an opaque component (5b) is shown. A transparent component (3) is inserted into this. In an advantageous embodiment, the transparent component is connected to an element (3ag) which connects several or preferably all of the transparent parts. This makes insertion easier, for example, because each transparent part does not have to be inserted individually. In an advantageous variant, the parts (5b) and (3) are connected, e.g. by gluing, welding or locking. In an alternative variant, the elements (5b) and (3) can also be glued to the circuit board. In an alternative variant, (5b) is connected to the circuit board by elements (5p) being pushed through openings in the circuit board. These elements can preferably hook into the circuit board.In an alternative, advantageous variant, such elements can also be deformed after insertion to establish a connection with the circuit board. Preferably, the elements (5p) are deformed by heat and / or force.

[0089] Fig. 44 shows an advantageous variant of the structure of the transparent and non-transparent components of the sensor surface. On the left in the image, an opaque component (5b) is shown. On the right in the image, transparent elements (3) are shown. The center of the image shows the connection between the transparent and non-transparent elements. In an advantageous embodiment, the element (5b) is shaped so that it can be manufactured by milling. Preferably, element (5b) is made of metal. Preferably, the metal is aluminum. Preferably, the transparent elements (3) are made of plastic. In a preferred variant, the elements (3) are made of a duroplastic. In an alternative variant, the elements (3) are made of a thermoplastic. In a preferred variant, the elements (3) are made of epoxy resin or silicone. In a preferred method, the opaque element (5b) is manufactured first.Subsequently, a plastic is preferably introduced in liquid form into the cavities (5k) of the non-transparent element (5b). In a preferred variant, the plastic is prevented from occupying the space of the cavities (3k) by a mold. In a particularly preferred variant, the mold displaces the plastic from the area in which the cavities (3k) are to be created. In an advantageous variant, the molding has elements (3st) and / or (5st) that bring about a positive connection in at least one direction of force. In an advantageous variant, the transparent elements are shaped such that they completely enclose electronic components arranged on the circuit board, together with the circuit board. In an advantageous embodiment, the electronics are protected from moisture by waterproof bonding of the transparent component (3) and the circuit board. Fig. 45 shows an example of the prediction quality of the body mass index BMI.The subjects' actual BMI is plotted on the horizontal axis (x). The vertical axis (y) shows the value determined from the inventive, non-invasive, optical analysis of human tissue on the palm of the hand. A good correlation between the values ​​is demonstrated. In an advantageous variant, the value determined by the non-invasive sensor corresponds better to the amount of body fat than the BMI.

[0090] Description

[0091] It is pointed out that all features as they become apparent to a person skilled in the art from the present description, the drawings, and the claims, even if they were specifically described only in connection with certain other features, can be combined both individually and in any combination with other features or groups of features disclosed herein, unless this has been expressly excluded or technical circumstances make such combinations impossible or pointless. A comprehensive, explicit presentation of all conceivable combinations of features has been omitted here solely for the sake of brevity and readability of the description.

[0092] The system consists of at least one or more sensor components, one or more data processing devices, and, in an advantageous variant, one or more display devices. In an advantageous variant, the system also includes at least one data storage device.

[0093] The above-mentioned system components can be integrated into a single device. However, their functionality can also be distributed across multiple devices. Particularly with regard to data processing and display, it is advantageous to use systems that users are already equipped with. These could be smartphones, smartwatches, computers, or similar devices. In particular, data processing functions can also be performed in the cloud. In an advantageous variant, data is stored on a server accessible via the Internet. In an advantageous variant, data from various users can be used to calculate recommendations for a specific user. In an advantageous variant, statistical data can be automatically incorporated to optimize the recommendations.

[0094] In an advantageous embodiment, the system according to the invention can be designed as a standalone measuring device that serves exclusively to measure specific parameters and / or substances and / or physiological states of humans. In a further preferred embodiment, the device according to the invention or parts of the device, such as the sensor components, can be integrated into other technical systems that have their own functionality and that the user uses in various contexts. For example, during cooking, hygiene, sports, communication, hiking, locomotion, locomotion with the aid of technical devices such as airplanes, cars, bicycles, or in the work process.The integration can, for example, take place in the following technical system objects or materials: smartphones, smart watches, fitness trackers, pedometers, wristbands, compasses, altimeters, walking aids, clothing, gloves, computer mice, telephone handsets, armrests, handles, steering wheels, kitchen appliances, bathroom scales, kitchen scales, toilet seats, glasses, gearshifts, dashboards, and machines used to produce goods. In a particularly advantageous variant, the sensor components are integrated into surfaces of devices that come into direct contact with human skin. In a particularly advantageous variant, they are integrated into handles or operating elements. Integration into devices that serve at least one other function besides measuring the user is particularly advantageous, so that the user of these devices can be measured without having to spend time on the measurement that they would not otherwise need to use another function of the device.The advantage here is the integration into a surface of the device that the user touches with the skin when using the additional function.

[0095] In an advantageous variant of the system, the measurements and / or measurement results and / or recommendations performed with the system can be made available not only to the system user, but can also be forwarded digitally to third parties or, after printing them out in paper form, handed over to third parties. Third parties can include natural persons, legal entities, or institutions.

[0096] The digital forwarding can occur automatically or on the individual instigation of the user, by a person authorized by the user or by the owner of the system. Natural persons can be, for example, medical personnel such as doctors or alternative practitioners or even nutritionists. For example, the person or institution receiving the data can supplement or comment on the measurement results and / or recommendations with their own data, save measurement results and / or recommendations and / or additions and / or comments on a medium and / or transmit them to the person being measured, e.g. digitally. If the measurement results are commented on or supplemented, this data can also be used to subsequently optimize the advice given to the individual user or to improve the advice given to an individual user by summarizing and / or analyzing comments or additions from various people.The transmitted data can also be stored on a medium belonging to the person being measured, for example, which is presented during a doctor's visit. This could be a storage medium on which the person's medical data is stored, such as an electronic health card. Alternatively, it can be stored on the person's smartphone. This does not have to be stored immediately after the digital transmission; it can be done subsequently by downloading it from a server, accessible via the internet, for example.

[0097] The institutions can be, for example, hospitals, health insurance companies or public institutions such as health authorities, state or federal ministries, statistical offices or, in the context of a survey, the institution conducting the survey.

[0098] The measurement results and / or recommendations can be forwarded to third parties in encrypted or unencrypted form. In a preferred variant, the results are anonymized or pseudonymized.

[0099] Examples of parameters and body parts that can be measured with the system

[0100] In an advantageous embodiment, for example, the measuring system can measure one or more of the following parameters in a single measurement process: body fat, water, blood sugar, and carotenoids. Each of these parameters can be measured in tissue and / or blood.

[0101] In a further technical embodiment, the invention enables the simultaneous or alternative measurement of cortisol, alpha-linolenic acid (omega-3 fatty acid), arachidonic acid (omega-6 fatty acid), linoleic acid (omega-6 fatty acid), riboflavin (vitamin B2) and C-reactive protein.

[0102] In an embodiment going beyond the aforementioned embodiments, the invention enables the simultaneous or alternative measurement of telomeres or advanced glycation end products (AGE). In a further preferred embodiment, the system detects one or more of the following parameters: inflammation, local inflammation of the skin, sunburn, the skin's sensitivity to sunlight, applied sunscreen, and the skin's antioxidant protective potential. In a further advantageous embodiment, the measuring device can be used to detect malaria, for example, by measuring plasmodia in the blood. Alternatively, the pathogens of other diseases or their effects can be detected. In an advantageous variant, the substance or disease is not detected directly by the optical measurement, but rather a variable affecting the optical properties of the skin that correlates with the disease of interest is recorded.This allows substances and conditions to be detected that cannot be determined directly, or can only be determined very imprecisely. In a particularly advantageous embodiment, the device can determine or at least estimate at least two, preferably three, and especially preferably four or more of these parameters. In a particularly advantageous embodiment, it is possible to determine at least several of the parameters in a single measurement.

[0103] The measurement of parameters and / or substances with which a person's physiological state can be assessed is advantageously carried out transcutaneously and can be performed on different parts of the body. In a preferred variant, the measurement is taken on parts of the body that are not normally covered by clothing. In a further preferred variant, the measurement is taken on parts of the body with less pigmentation. For example, this could be the inside of the hand in the area of ​​the ball of the thumb or the sole of the foot of the person to be measured. The measurement is also possible, for example, on the wrist, in the area of ​​the cheek, arm, thigh, buttocks or on any other part of the body that can be brought into contact with the sensor. In an advantageous variant, the measurement is taken on parts of the skin with little hair, for example on the hand, foot or face.

[0104] Surprisingly, it was discovered that, in a preferred embodiment, when measuring with the device, the body part to be measured does not need to be pretreated for the measurement by washing, disinfecting, preheating, cooling, rubbing dry, removing hardened or dead skin, or evaporating the uppermost skin layer in order to produce accurate and repeatable measurement results. Surprisingly, it was discovered that, in a further preferred embodiment, the body part to be measured can be pretreated in various ways in the aforementioned sense without affecting the accuracy of the measurement results, and that, for example, the type of pretreatment can be determined from the measurement results.An advantageous method of performing the measurement is that the measurement is not taken on parts of the body where there is a tattoo and / or a scar and / or a wound and / or an injury and / or an sebaceous gland and / or a sweat gland and / or a blood vessel and / or dirt and / or moisture and / or sweat and / or blood and / or hair and / or moles and / or age spots and / or wrinkles and / or skin dimpling and / or skin cream and / or sunscreen or sun milk and / or skin lotion and / or perfume.

[0105] In an advantageous embodiment of the invention, it was surprisingly found that the measurement leads to exact and repeatable measurement results, even when the measurement takes place on parts of the body where there is part of a tattoo and / or a scar and / or a wound and / or an injury and / or a sebaceous gland and / or a sweat gland and / or a blood vessel and / or dirt and / or moisture and / or sweat and / or blood and / or hair and / or moles and / or age spots and / or wrinkles and / or skin dents and / or skin cream and / or sunscreen or sun milk and / or skin lotion and / or perfume. This is possible with an advantageous design of the sensor, as shown in the embodiments. Embodiments that use more light paths over a larger area are particularly advantageous.

[0106] Surprisingly, it was found in a preferred embodiment that measurements at the aforementioned body locations yield precise and repeatable measurement results from which, for example, the respective measuring location can be determined.

[0107] Sensor components

[0108] Preferably, an optical system that measures various parameters and / or substances and / or physiological states of the individual uses emitters (1) and detectors (2) as sensor components, which emit and detect photons in wavelength ranges that are matched to the respective parameters, substances, or physiological states. Depending on the parameter, substance, or physiological state and / or the number of parameters, substances, or physiological states to be measured, the systems have a different number of emitters (1) and detectors (2). Together, they cover wavelength ranges that enable the measurement of the parameters and / or substances and / or physiological states. For example, one wavelength is used at which the substance to be measured absorbs the light and a second wavelength at which the substance does not absorb the light.By comparing the measurement results from both wavelengths, the substance concentration can be determined. However, more complex arrangements are usually advantageous. This means using multiple wavelengths at which a substance absorbs light and multiple wavelengths at which the substance does not absorb light or absorbs less. This allows a substance to be detected more reliably and also takes into account the influence of other substances that absorb light. For this reason, it is advantageous to use light emitters with different wavelengths and / or light detectors with different wavelength sensitivities. In an advantageous variant, the arrangement is designed so that there are multiple light paths of one wavelength. This means, for example, that there are multiple emitters with the same or almost the same wavelength and / or that there are multiple detectors with the same or almost the same detection wavelength range.The advantage of such an arrangement is that deviations affecting a light path, for example because the skin at the irradiation site has a special characteristic or because contact with the skin was not optimal, can be detected and compensated for. To illustrate a simple variant, one can say that several measuring sections with comparable wavelengths are compared for light paths from an emitter to a detector. In a simple, advantageous variant, outliers in the measured values ​​can be detected and excluded from the evaluation, which makes the overall measurement result more accurate. For this reason, it is advantageous to use several light emitters with the same or almost the same wavelength and / or light detectors with the same or almost the same wavelength sensitivity.It should be noted here that the simple direct comparison of measured values ​​with the same wavelength is only a highly simplified example, which illustrates the motivation for using emitters of the same wavelength. More sophisticated and powerful data processing approaches are possible, which will be explained later.

[0109] It was explained that it is advantageous to use emitters and / or detectors with the same as well as with different wavelengths. In the already known prior art, for example, there are arrangements in which several groups of emitters are used which have the same color. For example, there are arrangements with four red LEDs as emitters and four green LEDs as emitters. In such arrangements there is a clear difference in the wavelength between the two groups red and green, but within a group an attempt is made to keep the emitted wavelength as constant as possible in order to ensure direct comparability between the measurement signals obtained using different emitters of the same color. In an advantageous variant according to the invention, however, a significant improvement in measurement accuracy is achieved by selecting the emitters so that they do not have exactly the same wavelength.In an advantageous variant, the emitters are only approximately identical, and the differences between the emitters are deliberately exploited. This means that the system includes sensor components such as emitters and detectors, which can be identical, approximately identical, and / or not identical and / or not approximately identical in their technical properties.

[0110] The emitters can be, for example, LEDs, incandescent lamps or generally components that emit photons at approximately the same or different wavelengths.

[0111] Detectors can be, for example, photodiodes, phototransistors or other light-sensitive electronic components, in particular semiconductors or, in general, components that can capture photons emitted or radiated by emitters and, for example, convert them into signals in order to measure parameters, substances and / or physiological states of the individual.

[0112] Approximately identical sensor components In an advantageous variant, the system comprises emitters in which approximately identical emitters and / or emitters of the same type exhibit fluctuations in at least one of their optical properties compared to one another. This applies, for example, to optical properties such as the emitted wavelength spectrum (lowest wavelength to highest wavelength), the peak wavelength, the centroid wavelength, the peak half-width, the full width at half maximum (FWHM), the half width at half maximum (HWHM), the radiation characteristic, the temperature dependence, the brightness (luminance and radiance), and the power consumption. In an advantageous variant, the system comprises detectors in which approximately identical detectors exhibit fluctuations in at least one of their optical and / or electrical properties compared to one another and / or detectors of the same type exhibit fluctuations in at least one of their optical and / or electrical properties. This applies, for example, tofor the peak wavelength and center wavelength of the wavelength range in which the detectors record photons and the amplification factor with which the recorded photons are converted into electrical signals, the signal response, the responsiveness, the signal-to-noise ratio.

[0113] By fluctuations of approximately identical sensor components, i.e. fluctuations of emitters or emitters of the same type and fluctuations of approximately identical detectors or detectors of the same type, we mean limited differences in at least one optical and / or electrical property of the emitters and detectors.

[0114] In order for different values ​​of a technical property to be considered fluctuations of approximately identical sensor components or sensor components of the same type, the respective values ​​must lie within the limits of a defined interval. The intervals can vary depending on the technical property. In a preferred variant, a sensor can have several intervals with different interval lengths related to a property, e.g., the peak wavelength of the sensor components. In a preferred variant, the sensor of a measuring device can only have one interval of approximately identical emitters and / or one interval of approximately identical detectors.

[0115] In a particularly advantageous variant, the distribution of the values ​​of the optical and / or electrical properties of approximately identical sensor components in series-produced measuring devices is not the same for every measuring device produced. The distribution of the fluctuation can be introduced into the measuring device in various ways. One advantageous method is to select sensor components and, when equipping the measuring device with emitters and detectors, to specifically use some components with higher and some with lower values ​​of the respective property. In an alternative variant, the fluctuation in the optical properties of approximately identical sensor components is created by forming a set of sensor components in which the value of the optical and / or electrical property lies within a selected interval.When equipping the measuring device with emitters and detectors, a random selection of one component from this set can be made for each assembly position, so that the fluctuation is statistical in nature. In an advantageous variant, this statistical method is cost-effective and functional when the number of approximately identical components is large enough. This is particularly true when at least four components belong to a group with similar properties, but preferably at least five, six, or even more preferably at least eight components are approximately identical.

[0116] The advantage of using approximately identical emitters and / or detectors that exhibit fluctuations within certain limits in at least one property is that, as a result of the fluctuation, more information is collected about the parameter to be measured and / or the substance to be measured and / or the physiological state to be measured than with a device that does not exhibit these fluctuations with identical emitters or detectors. Due to the greater range of information achieved in this way, the measurement accuracy of the measuring device is increased. It is particularly advantageous if the dependence of the optical signal on the varying parameter is highly informative about the substance to be detected. This is advantageous, for example, when the peak wavelength of the emitters varies, since it allows the wavelength-dependent gradient of the absorption of a substance to be determined.In an advantageous variant, this gradient can also be compensated if it could distort the results. This is particularly relevant because there are substances that one would like to distinguish, but whose absorption only differs in ranges with strong absorption gradients. However, measurements in ranges where absorption changes significantly with wavelength are often not possible with the desired accuracy using existing methods.

[0117] Surprisingly, it was discovered that it is possible to transfer the increased measurement accuracy to all devices produced during the production process, to reduce the standard measurement error of the devices and to calibrate the devices so that, for example, when measuring the same person, the measurement results of the devices deviate less from one another. For example, measurements can be taken on test specimens during the production process and the larger amount of data resulting from the fluctuation of approximately identical sensor components can be analyzed using algorithms. The result is, for example, device-specific algorithms for determining the concentration of parameters, substances or physiological states in humans. In an advantageous variant, device-specific algorithms are understood to mean that the algorithms of several devices of the same device type are different.In an alternative variant, the algorithms of multiple devices of the same device type have different parameters for the algorithms used. In a particularly advantageous variant, these parameters include more than just the correction of the zero point of the result and the gain factor. In an advantageous variant, the number of parameters used is at least as large as the number of components in at least one group of components of the same type.

[0118] Algorithms can also be understood as artificial intelligence methods. Furthermore, cost advantages arise because the use of such sensor components can reduce the requirements for the manufacture of emitters and detectors, or their selection after production.

[0119] Description of the intervals of approximately equal sensory components

[0120] Depending on the substances or physiological states to be measured, the measuring device is ideally equipped with emitters that can radiate photons at specific wavelengths into the skin and detectors that detect these. If more than one emitter is required for the measurement range to determine the concentration of a substance or the physiological state, the emitters and the detectors suitable for detecting the photons can be assigned to wavelength intervals.

[0121] In this patent specification, the size of the interval (interval length) is determined as the value between the lower and upper limits of the interval.

[0122] In a preferred embodiment, individual emitters or detectors may belong to only one interval. In a likewise preferred solution, the boundaries of the intervals must not overlap. In a likewise preferred solution, the difference between the upper boundary of one interval and the lower boundary of another interval is up to 1 nm. In further preferred variants, the difference is up to 2 nm, up to 5 nm, up to 10 nm, up to 20 nm, up to 50 nm, up to 100 nm, up to 200 nm, up to 500 nm, up to 1000 nm. In a preferred embodiment, the difference between the upper boundary of the interval and the lower boundary of each interval above it is at least one of the specified values.

[0123] In a preferred solution, the measuring device can also have emitters or detectors that cannot be assigned to an interval. These sensor components are considered non-approximately identical sensor components. In another preferred solution, the measuring device can have several such emitters or detectors.

[0124] The wavelength range covered by all intervals with approximately identical sensor components of a measuring device is defined as follows: When comparing all intervals of a measuring device with each other, the wavelength range covered by all intervals results from the lowest lower limit and the highest upper limit of all intervals. Figures 14 and 14a show corresponding examples.

[0125] In a preferred embodiment, this difference between the lowest lowest value and the highest upper value of all intervals is a maximum of 10nm. In likewise preferred embodiments, it is a maximum of 20nm, up to 50nm, up to 100nm, up to 200nm, up to 500nm, up to 1000nm, up to 1500nm or up to 3000nm. In an alternative preferred embodiment, the wavelength range between the lowest lowest and the highest upper value is at least 50nm, preferably at least 150nm and in a further preferred variant at least 400nm. In a particularly preferred variant, for example, the intervals of a measuring device are distributed over at least 2, preferably at least 3 and alternatively preferably all frequency ranges of blue, green, red and near infrared (NIR) light.

[0126] Fig. 14 illustrates this by way of example for the technical property of the peak wavelengths of emitters. In a preferred variant, the interval lengths of the various intervals of a technical property can be identical, as shown in Fig. 14 using the example of the peak wavelength of emitters. The interval lengths for the various intervals in the blue, green, red, and NIR ranges of light are, for example, 10nm each.

[0127] In a further preferred variant, there are differences in the interval lengths of a technical property, as shown for the half-width of emitters (see Fig.14a).

[0128] Note: The wavelength intervals covered by the half-width are not understood as the half-width of a single emitter, but as the interval within which the wavelengths of all emitters of the interval lie that are emitted by the respective emitter with at least 50% of the intensity of its peak wavelength.

[0129] In a particularly preferred variant, the measuring device can have intervals whose interval boundaries are designed such that there are no gaps between the intervals over the entire frequency range covered, for example, by the emitters of a measuring device.

[0130] Figures 14 and 14a, using the example of emitters, clearly demonstrate that using approximately identical sensor components that fluctuate within interval limits generates more information because the bandwidth of the emitted light is larger. Measuring devices with approximately identical sensor components that do not exhibit these fluctuations necessarily have a narrower bandwidth of emitted light. The range of information generated by the measurement is consequently smaller.

[0131] As can be seen in the example of the wavelength intervals covered by the half-width in Fig. 14a, the emitters in an interval all have the same half-width, but the wavelength range covered by the respective half-width differs from emitter to emitter. In Fig. 14a, the dashed line (1b) shows the intensity limit of the half-width. It applies to all emitters in the four intervals. In the "green" interval, the interval length covers the wavelength range from 520 nm to 547 nm. However, the wavelength intervals covered by the half-width of the four emitters in this interval together cover a wavelength range that is smaller than the wavelength range determined by the length of the green interval (1 0cg). In the "blue" interval (1 0cb), this is different.The wavelength intervals covered by the half-width of the six emitters together cover exactly the interval from 454nm to 476nm, since the half-width coverage of the first emitter starts at 454nm and the half-width coverage of the sixth emitter ends at 476nm.

[0132] In an advantageous embodiment, the accuracy of a substance's measurement is influenced by the design of the intervals for approximately identical sensor components whose technical properties fluctuate within an interval. The following principle applies: the shorter the interval length and the greater the number of sensor components in an interval, the higher the spectral resolution when measuring the substance or a physiological state. In many applications, this allows for a more precise determination of the corresponding concentration. Particularly advantageous, however, is the method of inferring the slope of the function of measured light intensity as a function of wavelength from the measurement data obtained using multiple emitters located within an interval.Advantageously, it is not necessary to use emitters with precisely predefined peak wavelengths; instead, a sufficient number of emitters that differ in peak wavelength and whose peak wavelength is known or determinable is sufficient. Furthermore, known information about the sample can be included. For example, if it is known that the aforementioned slope can be regarded as almost constant in the wavelength interval. The described method can also be applied to other parameters, in particular to other wavelength units. Particularly advantageous in this case is the centroid wavelength of an emitter, which can optionally be weighted, e.g., with the wavelength-dependent sensitivity of the detector. In a further preferred solution, individual emitters or detectors can belong to more than one interval.

[0133] In a preferred solution, there may be overlaps between the upper limit of one interval and the lower limit of another interval. In an equally preferred variant, the overlap may be up to 2 nm, up to 5 nm, up to 10 nm, up to 20 nm, or up to 50 nm. In a preferred variant, the overlaps do not have to be the same for the respective range; combinations of different overlap widths can exist. In another preferred variant, there are gaps between the intervals as well as intervals directly adjacent to an interval and overlaps between the intervals. This will be illustrated using the peak wavelength of emitters for the wavelength range from 250 nm to 460 nm as an example:

[0134] An interval with an interval length of 50 nm covers the range from 250 nm to 300 nm, a directly adjacent interval with an interval length of 10 nm covers the range from 301 nm to 31 nm, another interval with an interval length of 50 nm covers the range from 320 nm to 370 nm, an overlapping interval with an interval length of 30 nm covers the range from 360 nm to 390 nm, and another interval with an interval length of 50 nm covers the range from 410 nm to 460 nm. In a preferred embodiment, the wavelength range that all intervals of approximately identical sensor components together cover for one property is a maximum of 50 nm. In further preferred variants, it is a maximum of 100 nm, up to 200 nm, up to 400 nm, up to 600 nm, up to 800 nm, or more than 800 nm. In a preferred embodiment, the wavelength range covered by all intervals of approximately identical sensor components for one property is at least 50 nm.In further preferred variants, it is at least 100 nm, up to 200 nm, up to 400 nm, up to 600 nm, up to 800 nm, or more than 800 nm. In another preferred variant, the wavelength range covered by all intervals of approximately identical sensor components for one property begins between 200 nm and 250 nm. In further preferred variants, it begins between 250 nm and 350 nm, between 350 nm and 450 nm, between 450 nm and 550 nm, between 550 nm and 800 nm, or between 800 nm and 1400 nm.

[0135] In a further preferred variant, the wavelength range covered by all intervals of approximately identical sensor components for one property ends below 2000 nm. In further preferred variants, it ends between 1500 nm and 2000 nm, between 1000 nm and 1500 nm, between 500 nm and 1000 nm, or between 200 nm and 500 nm.

[0136] Emitter

[0137] To assign emitters to a group of approximately identical emitters, an interval length of the peak wavelength and / or the center wavelength of the emitters is advantageously selected in the following size ranges: 1 nm to 5 nm, 2 nm to 20 nm, 10 nm to 50 nm, 20 nm to 150 nm. In an advantageous variant, at least two emitters must be located in each interval. In other advantageous variants, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least ten emitters must be located in an interval.

[0138] In a preferred variant, there are at least two emitters in an interval whose peak wavelength and / or center wavelength differ by at least 0.5 nm. In further preferred embodiments, the difference is at least 1 nm, at least 2 nm, at least 4 nm, at least 8 nm, or at least 10 nm. In an alternative advantageous variant, the above-described difference in the peak wavelength and / or center wavelength of the emitters occurs only in a portion of the measuring devices produced. Preferably, at least 1%, particularly preferably at least 10%, and particularly preferably at least 90% of the measuring devices.

[0139] The wavelength range covered by the half-width of an emitter can also be used to assign emitters to a group. An example is shown in Fig. 14d. In an advantageous variant, the measuring device in the aforementioned sense has a number of emitters of at least 2, preferably at least 3, preferably at least 4, preferably at least 5, preferably at least 6, preferably at least 7, preferably at least 8, preferably at least 9, preferably more than 10 emitters for at least one property of the emitters within a group of approximately identical emitters.

[0140] Fig. 14e shows five groups with two emitters each, using the peak wavelength as an example. Fig. 14b shows an example of four emitters in a group, and Fig. 14 shows an example of six emitters in a group for the intervals blue (10cb), red (10s), and NIR (10cir). In a preferred variant, the measuring device contains, in the aforementioned sense, some groups of approximately identical emitters with a larger number of emitters, while other groups have a smaller number of emitters. For example, Fig. 14 shows three groups with six approximately identical emitters and one group with four approximately identical emitters.

[0141] For an emitter property, it is advantageous to form a group number of at least two, but better still three, four, five, six, or more than six groups, with each group having an interval for the corresponding property. Advantageously, for at least one emitter property, the measuring device has at least a first group number of approximately equal emitters from the above set of advantageous numbers, which contain at least one emitter number of the advantageous emitter numbers specified above. Based on the peak wavelength, Fig. 14, for example, shows three groups with 6 emitters each.

[0142] Advantageously, in the measuring device, if at least one further emitter property has at least one further group number from the above set of advantageous group numbers, which contain at least one emitter number of the advantageous emitter numbers specified above. Particularly advantageously, in the measuring device, if at least one emitter property has, for example, at least 3 groups of approximately identical emitters with at least 4 emitters each. In an advantageous variant, if at least one emitter property has, there is additionally at least one group of approximately identical emitters with at least 5 emitters. In a further advantageous variant, if at least one emitter property has, there are at least 4 groups of approximately identical emitters with at least 2 emitters each. An example of such an arrangement is shown in Fig. 14e. The previously introduced term “group or groups” is often used synonymously with the term “interval” in a corresponding context.For a measuring device, for example, the terms "number of intervals" and "number of groups" refer to the same thing in the corresponding context. However, the term "interval" is always used in the figures, as this also allows the lower and upper interval limits of the wavelength range in which approximately identical emitters or approximately identical detectors are located to be determined.

[0143] In preferred variants, a measuring device has at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 intervals with approximately identical emitters, whereby the intervals each cover different wavelength ranges that do not overlap and the intervals each contain at least 2 approximately identical emitters. In a likewise preferred variant, there is also a measuring device which, analogous to the aforementioned measuring device, has the same number of intervals with approximately identical emitters, but in which at least two intervals overlap. In a preferred variant, the emitters of an interval do not cover the entire width of the interval. This means that for emitters assigned to an interval, the values ​​of the property do not scatter so greatly, or the values ​​do not differ so greatly, that the full bandwidth of the interval is required for these emitters to be assigned to the interval. Fig.14b and 14e show, using the example of the peak wavelength, that the emitters of an interval are not distributed over the entire interval length.

[0144] In a likewise preferred variant, there are no gaps between the intervals of approximately identical emitters for an optical property of the emitters. In an advantageous variant, the method used during production of a device according to the invention involves measuring at least one optical property of at least some of the emitters. In an alternative advantageous variant, the measurement during production can be omitted by inferring at least one optical property of the emitters from the measured values ​​of several measurements performed by the user. This can be done, for example, using mathematical or statistical methods or KL algorithms.

[0145] In an advantageous variant, numerous product units of the device according to the invention are produced and marketed. The marketed product units are used to perform numerous measurements. It is particularly advantageous to record a large number of measured values ​​and, in an advantageous variant, to store them, e.g., by transferring the measured values ​​to one or more external servers, e.g., using an internet connection.

[0146] In an advantageous variant, the measured values ​​collected in this way are used, for example, to gain insights into potential product improvements. In an alternative advantageous variant, the accuracy of the devices in the field can be improved either based on their individual measured values ​​or based on statistical values ​​from all devices, or through a combination of both.

[0147] In an advantageous embodiment, the device is designed so that the optical raw data can be recorded individually. In a particularly preferred embodiment, the individually recorded data can be stored. This allows subsequent optimization of the device using the aforementioned methods, even if these are not yet in use at the time of market launch, for example. In this context, optical raw data is understood to be information from which the properties of individual emitters can be deduced. In a particularly advantageous variant, information is stored that is recorded by one or more detectors when only one of the emitters is activated.

[0148] In an advantageous manner, therefore, not only information is recorded in which several emitters in an interval located in spatial proximity to one another and having approximately identical optical properties are activated simultaneously, meaning that no conclusions can be drawn about the optical properties of the individual emitters. In an advantageous variant, only one emitter of the measuring device is activated. In an alternative advantageous variant, several emitters are activated simultaneously, the emitters being selected such that when only the first emitter is activated, the measured value at a first detector increases by less than 50%, preferably less than 20%, alternatively preferably less than 8%, and in the best case less than 2%, when the emitters that are to be activated simultaneously are activated.

[0149] Approximately equal detectors

[0150] For example, to assign detectors to a group of approximately identical detectors, their sensitivity is selected. Sensitivity in the spectral range of interest is an important criterion when selecting detectors. In this document, this refers to the ability of a detector to detect incident photons at a specific wavelength with a specific probability. To be able to compare detectors with one another, the maximum sensitivity of detectors is normalized to 1. The resulting scale from 0.0 to 1.0 is referred to as the relative sensitivity. In a preferred variant, the relative sensitivities of two approximately identical detectors at the same wavelength, e.g. the peak wavelength, should not differ by more than 0.02 within an interval.In likewise preferred variants, the relative sensitivities of two approximately identical detectors at the same wavelength, e.g., the peak wavelength, within an interval should not differ by more than 0.04, 0.0, 0.15, 0.2, 0.4, 0.8. In a further preferred variant, the relative sensitivities of three approximately identical detectors at the same wavelength, e.g., the peak wavelength, within an interval should not differ by more than 0.04, 0.06, 0.08, 0.1, 0.15, 0.2, 0.4, 0.8. With regard to relative sensitivity differences, in an advantageous variant, for example, there are at least two detectors in each interval of approximately identical detectors. In further advantageous variants there are at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 detectors in an interval.

[0151] To assign detectors to a group of approximately identical detectors, the peak wavelength and / or centroid wavelength of the wavelength range in which the detectors detect photons from emitters is selected. With regard to the peak wavelength and / or centroid wavelength, intervals with approximately identical detectors advantageously have, for example, at least the following interval lengths: 5 nm, 10 nm, 20 nm, 50 nm, 100 nm, 300 nm. With regard to the peak wavelength, approximately identical detectors advantageously have intervals with, for example, at most the following interval lengths: 10 nm, 20 nm, 50 nm, 100 nm, 200 nm, 350 nm.

[0152] In an advantageous variant, there are at least 2 detectors in each interval with approximately the same detectors in terms of peak wavelength. In further advantageous variants, there are at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10 detectors in an interval. In a preferred variant, there are at least 2 detectors in an interval of approximately the same detectors whose peak wavelengths differ by at least 0.5 nm. In further preferred embodiments, the difference is at least 1 nm, at least 2 nm, at least 4 nm, at least 8 nm, at least 10 nm, at least 50 nm, at least 100 nm, or at least 200 nm. In an alternative advantageous variant, the difference in the peak wavelength and / or center of gravity wavelength of the detectors described above only occurs in some of the measuring devices produced. Preferably in at least1%, particularly preferably up to 10% and particularly preferably up to 90% of the measuring devices.

[0153] For the assignment of detectors to a group of approximately identical detectors, the current (in mA) that the detector emits as a result of detected photons (in mW / cm 2 ). Detectors are considered to be approximately equal if the current they emit at a specific wavelength lies within a common interval. Fig. 15 shows a corresponding example. In a preferred variant, the interval length (10) is defined as a range for the emitted current (in mA), which results when detecting photons at 10 mW / cm 2 In the example, the lower limit of the interval (10a) is 0.2 mA and the upper limit (10b) is 10 mA. The interval length (10) is 10 mW / cm 2is then 9.8mA. For a detector to be considered as approximately equal, its emitted current must be at a certain wavelength and a received power of 10mW / cm 2 between 0.2 mA and 10 mA. The received power of the detectors is plotted as a logarithmic value on the x-axis, and the delivered current is plotted as a logarithmic value on the y-axis. As the figure shows, the three detectors lie within the interval limits. Detector 2.1 delivers 0.6 mA at 10 mW received power, detector 2.2 delivers 3 mA, and detector 2.3 delivers 7.5 mA, all at the same wavelength.

[0154] In relation to the current intensity delivered at a specific wavelength, in preferred variants the interval length (10) is, for example, between 0.1 mA and 1 mA, between 1 mA and 2 mA, between 2 mA and 5 mA, between 5 mA and 7.5 mA, between 7.5 mA and 10 mA, between 10 mA and 20 mA, between 20 mA and 50 mA, between 50 mA and 100 mA. In relation to the current intensity delivered at a specific wavelength, in preferred variants there are at least 2 detectors, at least 3 detectors, at least 4 detectors, at least 5 detectors, at least 6 detectors, at least 7 detectors, at least 8 detectors, at least 9 detectors, at least 10 detectors, between 10 and 20 detectors or more than 20 detectors in an interval of approximately equal detectors.In a preferred variant, at a certain wavelength, the differences in the emitted current strength of two approximately equal detectors of a common interval are up to 2 times, up to 4 times, up to 8 times, up to 12 times, up to 16 times, up to 20 times, up to 30 times, up to 50 times or up to 100 times.

[0155] An example is shown in Fig. 15a. The output current of detector 2.2 is 3 mA and is thus 5 times the output current of detector 2.1, which is 0.6 mA. Detector 2.3 has the highest conversion of received power to current. It delivers 7.5 mA. The output current with the same received power and wavelength is thus 2.5 times higher than that of detector 2.2 and 12.5 times higher than that of detector 2.1. This makes it clear that the three detectors are approximately identical, since both the interval length and the conversion of received power to output current are within the previously defined limits for approximately identical detectors. In a preferred variant, there are at least two detectors in an interval of approximately identical detectors, whose conversion of received power into mW / m 2to current in mA differ by up to a maximum of 10%. In further preferred embodiments, the difference is max. up to 20%, max. up to 50%, max. up to 100%, max. up to 200%, max. up to 500%, max. up to 1000%. Fig. 15 shows an interval in which the conversion factors of the three detectors included differ by up to 500%.

[0156] The detectors used in the above advantageous example have integrated amplifiers. In an alternative variant, detectors without amplification are used. These generate a lower current flow for the same light irradiation. For an alternative variant without amplification, absolute currents are therefore to be expected that are a factor of 10, a factor of 100, or some other factor lower. However, the relationships otherwise apply accordingly. In an alternative advantageous variant, the difference in the conversion factor of the detectors described above only occurs in a portion of the measuring devices produced. Preferably in at least 1%, particularly preferably in at least 10%, and especially preferably in at least 90% of the measuring devices.

[0157] The following discusses variants that speak of advantageous properties of the measuring device. In these variants, however, multiple measuring devices can also be used in the system. In this case, "the measuring device" refers to one or more of the measuring devices used. In an advantageous variant, the measuring device, as defined above, has at least one group of approximately identical detectors for at least one property of the detectors. In a preferred variant, the measuring device has a number of groups of at least 2, at least 4, at least 8, at least 16, or more such groups.

[0158] In a preferred variant, the measuring device in the aforementioned sense contains, for at least one property of the detectors, some groups of approximately identical detectors which have a larger number of detectors, while other groups have a smaller number of detectors. Advantageously, in the measuring device, for at least one property of the detectors, there is at least a first number of groups of approximately identical detectors from the above set of advantageous group numbers, which contain at least one number of detectors among the advantageous numbers of detectors specified above. Advantageously, in the measuring device, for at least one property of the detectors, there is at least a further number of groups from the above set of advantageous group numbers, which contain at least one number of detectors among the advantageous numbers of detectors specified above. Particularly advantageously, in the measuring device, for at least one property of the detectors, for example at least.3 groups of approximately identical detectors with at least 4 detectors each. In an advantageous variant, if at least one property of the detectors is present, there is also at least one group of approximately identical detectors with at least 5 detectors. In a further advantageous variant, if at least one property of the detectors is present, there are also at least 4 groups of approximately identical detectors with 2 detectors each. In a preferred variant, the detectors of an interval do not cover the entire width of the interval. This means that for detectors assigned to an interval, the values ​​of the property do not scatter so widely, or the values ​​do not differ so greatly, that the full bandwidth of the interval is required for these detectors to be assigned to the interval. Fig. 15 shows an example with three detectors whose conversion factors are above the lower limit of the interval and below the upper limit of the interval.In a more preferred variant, the detectors of an interval cover the entire width of the interval. This means that for detectors assigned to an interval, the values ​​of the property are so scattered, or the values ​​differ so greatly, that the full bandwidth of the interval is required so that all detectors can be assigned to the interval. In a preferred variant, the measuring device has at least two detectors in total. In further preferred variants, the measuring device has, for example, at least four, up to eight, up to 16, up to 20, or more than 20 detectors.

[0159] Explanation of the terms "sensor components with approximately identical properties" and "sensor components with not approximately identical properties." Sensor components are understood to be components of the measuring device or sensor. Emitters and detectors are, in particular, components of the sensor. The measuring device claimed here for measuring substances or parameters to determine physiological states in humans can, in a preferred embodiment, contain, in addition to the sensor components previously described as identical, also sensor components that differ from these approximately identical sensor components in at least one technical property.Sensor components are considered non-approximately identical sensor components if the value of a technical property does not lie within the interval length of an interval of approximately identical sensor components, but rather outside the interval, for example, in an interval gap. An example of a non-approximately identical emitter in a gap of approximately identical emitters is shown in Fig. 14c, where the non-approximately identical emitter has a peak wavelength of 580 nm.

[0160] For example, in a preferred variant, the measuring device claimed here has, with at least one property, both approximately identical sensor components and sensor components that differ in the aforementioned sense from the approximately identical sensor components with at least one property. Examples of this are shown in Figures 14c and 14d using the peak wavelength and half-width of emitters. Figure 14c shows a single non-approximately identical emitter between two intervals of approximately identical emitters, and Figure 14d shows two single non-approximately identical emitters, between which there is an interval with approximately identical emitters. In a further preferred variant, the measuring device has, with at least one property, only approximately identical emitters and approximately identical detectors in the aforementioned sense.In a further preferred variant, the measuring device in the aforementioned sense, for example, has approximately identical emitters and not approximately identical detectors, or approximately identical detectors and not approximately identical emitters, in at least one property. An example of the combination of approximately identical emitters and not approximately identical detectors is shown in Fig. 16a.

[0161] Fig. 16a shows two non-approximately identical detectors (2.4 and 2.5) that differ in their peak wavelength (2b). The peak wavelengths of the two detectors are shown as dotted lines at 580 nm and 940 nm. The dashed areas in Fig. 16a represent the four intervals for the half-widths (1b) of approximately identical emitters, as shown in Fig. 14a. The advantages of this combination are clearly evident. The relative sensitivity with which the photons of the approximately identical emitters are detected is high for all emitters, since the wavelength ranges for absorbing photons are so broad that they still overlap despite the different peak wavelengths (2b) of the two detectors (2.4 and 2.5). The photons of the first interval of the approximately identical emitters are detected with a relative sensitivity of at least 0.72, the photons of the second interval with at least.0.9, the photons of the third interval with 0.7, and the photons of the fourth interval with at least 0.98. In a further preferred variant, the measuring device in the aforementioned sense has, for example, with at least one property, approximately identical emitters and approximately identical detectors and / or with a further property, approximately identical emitters and / or not approximately identical detectors and / or with the further property, not approximately identical emitters and approximately identical detectors.

[0162] It is clear to the person skilled in the art from the description that, in the aforementioned sense, the combination of approximately identical and not approximately identical sensor components, for example with regard to the number of respective properties, the interval length for approximately identical sensor components, the combination of intervals to cover a range or the complete wavelength range from UV to infrared, results in a multitude of variants which have approximately identical and / or not approximately identical sensor components and which, for the respective application, improve the measurement accuracy and / or repeatability and / or comparability of the results when measuring parameters and / or substances and / or physiological states of humans.

[0163] In a preferred variant, for a specific width of the wavelength range or the entire wavelength range from UV to infrared in the above-mentioned sense, the intervals of approximately identical emitters and the intervals of approximately identical detectors are combined. In a preferred embodiment, the measuring device has a total of up to 6 emitters and detectors in terms of the sum of emitters and detectors, and in a further preferred variant, a total of up to 9 emitters and detectors, which are either considered approximately identical sensor components in the above-mentioned sense and / or differ in at least one technical property from the sensor components considered identical. In other preferred embodiments, the measuring device has a total of 10 to 16, 17 to 30, 31 to 50, 51 to 70, 71 to 100, or more than 100 emitters and detectors in the above-mentioned sense.In the aforementioned designs, emitters that can emit multiple wavelengths are counted as the number of emitters they emit. For example, RGB emitters are counted as 3 emitters. In the above, "sum of emitters and detectors" means that when the number of emitters is added to the number of detectors, the total value of both components is, for example, 10. It is therefore expressly not meant that the sum of the emitters equals 10 and the sum of the number of detectors also equals 10. Which design is preferable can also depend on the chosen application. For example, devices can be designed to have a larger number of functions or higher accuracy and therefore fetch somewhat higher prices. Such devices advantageously have more components integrated. Other devices should be designed to be as small, power-efficient or as cost-effective as possible.In such cases, variants with a smaller number of emitters and detectors may be advantageous.

[0164] In an advantageous embodiment, the number of emitters is greater than the number of detectors. This approach allows for better measurement quality in advantageous variants with the same technical effort. Advantageously, the number of emitters is at least twice as large as the number of detectors. In an alternative, more advantageous embodiment, the number of emitters is at least three times as large as the number of detectors. In an alternative, more advantageous embodiment, the number of emitters is at least four times as large as the number of detectors.

[0165] In an advantageous variant, at least some detectors are designed to be sensitive to multiple wavelength intervals of groups of approximately identical emitters. An advantageous variant has a number of emitters within the wavelength intervals for which the said detectors are sensitive that is greater than half the number of wavelength intervals of the emitters multiplied by the number of detectors sensitive to these wavelength intervals. In an alternative advantageous variant, the number of emitters is at least equal to the number of wavelength intervals of the emitters multiplied by the number of detectors sensitive to these wavelength intervals. In an alternative advantageous variant, the number of emitters is at least equal to twice or three times the number of wavelength intervals of the emitters multiplied by the number of detectors sensitive to these wavelength intervals.The optimal ratio between emitters and detectors depends, among other things, on the spatial conditions and the technical complexity of the emitters and detectors. In an advantageous variant of a design, the technical complexity of an emitter is lower than that of a detector.

[0166] In many cases, it is advantageous if the number of emitters does not exceed the number of detectors by too much. In an advantageous embodiment, the number of detectors is less than the number of emitters divided by 20. In an alternative advantageous embodiment, the number of detectors is less than the number of emitters divided by 10. In an alternative advantageous embodiment, the number of detectors is less than the number of emitters divided by 7. In an alternative advantageous embodiment, the number of detectors is less than the number of emitters divided by 5. In an alternative advantageous embodiment, the number of detectors is less than the number of emitters divided by 4. In an alternative advantageous embodiment, the number of detectors is less than the number of emitters divided by 3.In an advantageous variant, at least one subgroup of approximately identical detectors is designed to be sensitive to multiple wavelength intervals of groups of approximately identical emitters. In an advantageous embodiment, the number of emitters lying in a wavelength interval to which the detector is sensitive is less than the number of detectors in this subgroup multiplied by the number of wavelength intervals to which the detectors in the subgroup are sensitive. In an alternative advantageous variant, the number of emitters lying in a wavelength interval to which the detector is sensitive is less than twice the number of detectors in this subgroup multiplied by the number of wavelength intervals to which the detectors in the subgroup are sensitive.The rules for limiting the number of emitters specified above are particularly advantageous for devices that are designed to be wearable or handy portable devices. The rules for limiting the number of emitters specified in this text are particularly advantageous for devices that are designed to be used at measurement points of limited size. Examples of measurement points can be: finger, hand, ball of the hand, palm, back of the hand, wrist, arm, face, cheek, ear, earlobe, forehead, eye, chest, foot, sole of the foot, buttocks, and leg. The rules for limiting the number of emitters specified above are particularly advantageous for devices that are designed to have limited costs, particularly for devices intended for use by end customers or consumers.In an advantageous embodiment, the system described here uses the MSRRS measurement technology described in the patents EP 3013217; EP 3175783; US 10,416,079; US 11,08,5876, US 11,662,309 and the applications US 18 / 203,359, EP 4005469A1 to estimate the physiological state of the individual by measuring various parameters and / or substances with the aid of the sensor components.

[0167] In an advantageous embodiment, the substance concentrations are determined transcutaneously at various depths of the human skin, extending into the blood. Both inhomogeneously distributed and homogeneously distributed substances are detected. In an advantageous embodiment, the concentration of a substance can be determined both in a person's blood and in other parts of the tissue, e.g., in the tissue fluid. In an advantageous embodiment, the concentration measurements of a substance in the blood and in other parts of the tissue allow conclusions to be drawn about changes in concentrations.

[0168] In an advantageous variant, substance concentrations can be determined as a function of depth, i.e., the distance from the skin's surface. In an advantageous variant, differences in substance concentrations as a function of depth can be used to draw conclusions about the dynamics of concentration values ​​or the behavior of the person. In an advantageous variant, for example, the times and effects of individual meals can be recorded, and the user can receive feedback. In an alternative variant, the effects of sports or physical activity, or the effects of exposure to sunlight or other radiation, can be determined.

[0169] Approximately similar properties of emitter-detector pairs

[0170] In a preferred embodiment, not only groups of technical properties of emitters or detectors are formed. It is also advantageous to select certain properties that can only be defined in the pair between emitter and detectors in such a way that groups of approximately identical pairs are created. In a particularly preferred variant, emitter-detector pairs are formed that have an approximately equal distance. In an advantageous variant, emitter-detector pairs are formed that have an approximately identical wavelength characteristic due to the interaction of the emission characteristic of the emitter with the detection characteristic of the detector. In an advantageous variant, emitter-detector pairs are formed that have an approximately identical average photon penetration depth into a sample due to the interaction of the emission directivity of the emitter with the detection directivity of the detector.An average sample or a reference sample is preferably used for this purpose. The advantageous variants and embodiments described for approximately identical emitters and approximately identical detectors can be transferred to approximately identical emitter-detector pairs and then represent advantageous embodiments. An emitter-detector distance (1c) is shown in Fig. 13. In an advantageous variant, a group of approximately identical emitter-detector distances has intervals that lie in the range between 1 mm and 3 mm, or between 2 mm and 4.5 mm, or between 4 mm and 6 mm, or between 5 mm and 10 mm, or between 8 mm and 18 mm. In an advantageous embodiment, there is a second group of approximately identical emitter-detector distances that lie in a second of the above-mentioned ranges. In a particularly preferred variant, there is a third and / or a fourth group of approximately identical emitter-detector distances that lie in a second of the above-mentioned ranges.

[0171] Measurement procedure

[0172] In a preferred embodiment, in order to measure parameters, substances, or physiological states of an individual, the emitters of the measuring device are each switched on individually and in a specific order one after the other. The order can vary. In a likewise preferred embodiment, in order to measure parameters, substances, or physiological states of an individual, two of the emitters of the measuring device are always switched on simultaneously. The order in which two emitters are switched on first and which are switched on next can vary. Analogous to the above, in likewise preferred embodiments, three emitters, four emitters, or five emitters are switched on simultaneously. The order in which three, four, or five emitters are switched on first and which are switched on next can vary.

[0173] In a preferred embodiment, the two, three, four or five emitters that are switched on together are each approximately identical emitters that differ, for example, in their peak wavelength or centroid wavelength but belong to an interval. In a further preferred variant, the two, three, four or five emitters each belong to more than one interval. In a further preferred embodiment, the variants described above are each not approximately identical emitters. The distribution of the emitters across the wavelength range from ultraviolet to infrared is designed such that, in a preferred variant, the differences in the peak wavelength or centroid wavelength are, for example, more than 50 nm. In further preferred variants, the differences are, for example, more than 75 nm, more than 100 nm, more than 150 nm or more than 200 nm.In a preferred embodiment, the described methods for activating the emitters can be combined. In an advantageous variant, an activation sequence results in which there are points in time when only one emitter is activated and points in time when multiple emitters are activated.

[0174] In an advantageous variant, there are points in time in the activation sequence at which no emitter is activated. Such points in time make it possible to detect the influence of light sources that are not part of the emitters. One example is sunlight. In a preferred variant, for emitters with a wavelength that is strongly absorbed by the sample to be measured and therefore does not travel far through the sample, several emitters are activated simultaneously. In an advantageous variant, when measuring human skin, several emitters in the wavelength range below 575nm are activated simultaneously. In an advantageous variant, simultaneously activated emitters in the wavelength range below 575nm have a distance on a common plane relative to the respective center of the emitters of more than 5, or alternatively more than 7, or alternatively more than 9, or alternatively more than 11 millimeters.In a preferred variant, emitters with a wavelength above 600 nm are activated individually at least at one point in the measurement sequence when measuring human tissue. In a preferred variant, several emitters are activated simultaneously. This makes it possible to increase the light intensity measurable at the detector compared to the sequential activation of individual emitters, so that the detector enters a working range in which it operates more precisely. In an advantageous variant, several emitters are activated that are at almost the same distance from a detector. In an advantageous variant, additional emitters are activated that are at a greater distance than the aforementioned emitters. Due to the greater distance, these emitters do not have any disruptive influence on the measurement.In an advantageous variant, it is possible to choose an arrangement so that the advantageous situations described in this section also apply to a second detector or, in an advantageous variant, even to 3, 4 or even more detectors.

[0175] Description of measuring device - distribution of sensor components

[0176] In a preferred embodiment, the measuring device has a sensor surface which, when measuring various parameters and / or substances and / or physiological states of a person, is in direct contact with the outer layer of the skin. In a preferred embodiment, this skin contact does not occur continuously throughout the entire measurement period. In an alternative preferred embodiment, this skin contact occurs throughout the entire measurement period. In a further preferred embodiment, contact and non-contact alternate during a measurement. In a preferred variant, the user is signaled when to establish or interrupt contact. In a further preferred variant, only part of the sensor surface is in continuous contact with the outer layer of the skin throughout the entire measurement period. In a further preferred variant, part of the sensor surface is not in continuous contact with the outer layer of the skin throughout the entire measurement period.

[0177] A sensor surface element is understood to be a three-dimensional component (3) with a specific thickness, which has a surface that makes contact with the sample. The material of the sensor surface element can be transparent, less transparent, translucent, scattering, or, depending on the wavelength range, absorbent. The sensor surface element can consist of one or more individual components, which in a preferred variant can form a unit. Parts of the sensor surface element can be made of non-transparent material. In an advantageous embodiment, the sensor surface element comprises sufficiently transparent materials so that the light from each emitter used for the measurement can penetrate the sample.In an advantageous embodiment, the sensor surface element comprises sufficiently transparent materials so that each detector used to measure light that has passed through the sample can be reached by light emerging from the sample. In an advantageous variant, the sensor surface element comprises sufficiently opaque materials so that light must pass through the sample to be measured in order to get from a selected emitter to a selected detector. In an advantageous embodiment, the above statement applies to over 50% of the possible pairings of emitters and detectors, and even more advantageously to over 80%. In an advantageous variant, however, pairings of emitters and detectors exist in which the light does not have to pass through the sample to get from the emitter to the detector.

[0178] When reference is made to the three-dimensional sensor surface element or just the sensor surface element in some places in this document, this always refers to the component described above. In a preferred embodiment, this three-dimensional component has a curvature towards the side of skin contact. In a more preferred embodiment, the curvature is concave, in a further preferred embodiment, the curvature is convex. Figures 2 and 2a show an example of a convex curvature of the three-dimensional component of the sensor surface (3), while Figures 3 and 3a show examples of a concave curvature of the three-dimensional component of the sensor surface. In a further preferred embodiment, the three-dimensional component has concave and convex curvatures, which, however, are not opposite one another. Relative to the two-dimensional extension (3a) of the sensor surface element (3), shown in Fig.la, this size is determined by the arrangement and / or placement of the emitters and detectors. In a preferred embodiment, the size and shape of the two-dimensional extension of the sensor surface element is determined by the area that the emitters and detectors together require as components, if they are mounted, for example, on a common printed circuit board (PCB) of the measuring device or are located on a common plane (3b). Fig. la shows an example of the differences between the two-dimensional extension of the sensor surface element (3a) and the two-dimensional extension of the area that the emitter and detector have on a common plane (e.g. PCB) (3b). In a preferred variant, the printed circuit board or the common plane on which the emitters and / or detectors are mounted is impassable or almost impassable for photons. In a likewise preferred variant, the printed circuit board or the common plane can be completely or partially, e.g.be electrically heated or cooled, e.g., by having heating or cooling coils on the circuit board. Alternatively, this can be achieved using Peltier elements. In a preferred embodiment, the circuit board is designed to be opaque to light by shielding the light with metal layers, preferably made of copper, gold, or solder. Alternatively, the circuit board is made opaque by using non-transparent solder mask or non-transparent printing. In an alternative variant, the base material of the circuit board is non-transparent. In a particularly advantageous variant, the above methods are combined, so that some metallic surfaces are present, and where metallic surfaces cannot be present for insulation reasons, the other methods are used. In an advantageous embodiment, the surface of the circuit board is black. In an alternative advantageous embodiment, the surface of the circuit board is white, e.g.,to increase the light output.

[0179] In further preferred variants, the two-dimensional extent of the sensor surface element (3a) is up to 5% larger, up to 15% larger, up to 30% larger, up to 100% larger, up to 200% larger, up to 400% larger or up to 800% larger than the area (3b) required by the emitters and detectors as components when they are mounted, for example, on a common printed circuit board (6) (PCB). In a preferred variant, the three-dimensional sensor surface element is designed such that the emitters and detectors are not in direct contact with the skin during measurement. In a preferred embodiment, this is achieved in that the three-dimensional sensor surface element has through-openings (3.2) in the area of ​​the emitters and detectors. The shape of these openings can be different. In a preferred variant, the openings are rectangular; in further preferred variants, they are square or round, or have square orRectangular openings with chamfered corners or a combination of the aforementioned openings. Figures 4 and 4a show examples of the geometric shapes of the opening (3.2) as well as the chamfering of an opening in section and plan view. Openings for light can also be closed with transparent elements.

[0180] In a preferred variant, the three-dimensional sensor surface element (3) is designed such that the emission and detection of photons can take place through the three-dimensional component. The volume can be transparent, so that photons can pass through the volume almost unhindered and without noticeable scattering. In a preferred embodiment, this volume is less transparent or diffuse, and photons are scattered by the material of the volume such that when they leave the volume they penetrate the skin in almost all possible spatial directions, i.e. without a preferred direction. This can be achieved, for example, by scattering bodies that are part of the volume or are deliberately introduced into it. However, other methods for influencing the direction of movement of the photons are also known to those skilled in the art (see, for example, patent EP 3175783B1 or EP 3013217B1).

[0181] In another preferred embodiment, the material for the sensor surface element is selected such that only photons of specific wavelength ranges can pass through this material. A material can be selected which has different absorption and / or scattering properties for different wavelengths. In another preferred embodiment, the photons are bundled as they pass through the volume by the design and the choice of material, so that when they leave the volume they enter the outer layer of the skin, for example in one or more preferred directions. The material can, for example, be designed in a correspondingly lens-shaped manner. Alternative possibilities for influencing the direction of the emitted photons include the use of reflective surfaces, prisms, optical gratings, curved surfaces, particularly at transitions between materials of different optical density.Further possibilities include restricting the direction of movement of photons by using material that is not transparent. In an advantageous embodiment, this can also be achieved using several non-transparent materials. In particular, an arrangement is also possible in which not just one, but several paths exist for photons to reach the sample from their point of origin. For example, by creating several channels for the photons from an arrangement that may consist of several transparent elements and possibly several non-transparent elements. In an advantageous variant, the transparent elements and the non-transparent elements are connected in such a way that they form a structured solid. In an advantageous variant, structured materials can be used, such as those known from privacy films for laptop screens, which restrict the viewing angle.However, materials and arrangements as known from light field displays can also be used. In a more preferred embodiment, the three-dimensional sensor surface element (3) contains three-dimensional components (5), the material of which is selected such that it is impassable or at least almost impassable for photons. Fig. 5 and Fig. 5a show such components (5) in section and plan view. It is also shown that the components (5) can also have bevels. Other shapes are also possible. The individual components (5) can be connected to form a monolithic, coherent component (5b), as shown in Fig. 9b. Possible materials for the components include metals, aluminum, ceramics, glass or plastics. Likewise preferably, these components can be present in all versions of the measuring device. In Fig.Figures 1a, 4a, 5a, and 6a show arrangements in which emitters and detectors are arranged in a regular rectangular arrangement. However, other arrangements are also possible. These can be regular or irregular. An advantageous arrangement positions emitters and / or detectors on one or more circular paths. In a preferred embodiment, the thickness and placement of the impassable or almost impassable parts are selected such that they spatially separate the emitters and detectors located beneath the sensor surface element from one another in such a way that emitted photons cannot reach the detectors within the measuring device. Figures 6, 7, and 8 show examples of how the emitters and detectors are separated from one another by the components (5).In a preferred embodiment, the spatial separation of emitter and detector can be designed such that, in conjunction with the three-dimensional sensor surface element, enclosed spaces are created which, in their basic geometric shape, correspond to round, rectangular, or square volumes which, as described above, can have beveled corners or edges. In an alternative embodiment, the volumes can contain additional bulges or have a different shape, even an irregular one. Figure 5 shows the combination of component (3) with component (5), which leads to completely enclosed spaces in which emitters (1) and detectors (2) are located. In this case, cavities (8) can be created above the respective sensor components, which are filled with air, for example. In a preferred embodiment, the width of the parts (5) impassable for photons is greater than the width of the transparent parts of the sensor surface element (3).The step resulting from the difference in width between the two bodies can, in a preferred embodiment, be located on the side of the sensor surface that faces the skin during measurement. Fig. 6b shows a corresponding example. In a further embodiment, the step can be located on the underside. This means the side of the three-dimensional component (3) that does not face the skin. The step can ensure advantageous form-fitting force transmission and thus divert forces that occur when the sample is placed on the transparent parts to the non-transparent parts. In this variant, for example, the transparent parts of the sensor surface element (3) and the components (5) that are impassable for photons can form a smooth or almost smooth surface on the side facing the skin. Fig. 5 shows a corresponding example.

[0182] In a preferred variant, the transparent parts of the sensor surface element (3) and the components (5) impervious to photons form a form-fitting unit, which improves the stability of this unit. In a preferred variant of Figure 6, the transparent sensor surface elements (3) and non-transparent elements (5) are designed in such a way that they do not form any corners or edges on the side facing the skin. This makes the surface easier to clean. In an advantageous variant, such an arrangement ensures that the skin does not come into direct contact with the transparent elements (3) under normal pressure. This reduces contamination and wear on the surfaces of the transparent elements (3). In an advantageous variant, the arrangement is designed in such a way that, for example,when the hand is placed on the sensor, the pressure of the skin on the sensor at the pressure intended for the measuring process acts either substantially or exclusively on the area of ​​the non-transparent elements 5. This results in a higher pressure in the contact area between the skin and the arrangement, which reduces the proportion of light that has not penetrated the sample. This can reduce the proportion of light that has traveled, for example, along a fold of skin from the emitter to the detector without penetrating the skin. In an advantageous variant, the arrangement is designed such that the skin does not come into direct contact with the transparent sensor surface elements (3) under normal pressure. This results in a defined contact situation or type of contact between the skin and the surface of the transparent elements (3). The influence of the type of contact can thus be significantly reduced, which leads to more accurate results.The type of contact refers to whether the skin is in direct contact with the transparent surface or whether this is covered by a thin layer of liquid, which can consist of water, sweat, fat, or a mixture of these substances. Another type of contact is the presence of a thin layer of air. The surface structure of the skin often results in mixed forms of contact, which, for example, have a different type of contact in the grooves and folds of the skin than in other areas of the skin. Since different types of contact have a significant optical influence, particularly in the area of ​​the transparent elements (3), which can disrupt the measurement, the aforementioned design of the measuring arrangement enables a more precise measurement because the disruptive influences caused by the type of contact are reduced.In an advantageous variant, the skin comes into contact with the surfaces of the transparent elements (3) when applying pressure that is greater than the pressure intended for the measurement. This can be detected from the optical measurement data, and the user receives feedback that they are applying too much pressure to the sensor surface.

[0183] In an alternative, advantageous variant, the pressure is estimated using the optically measured amount of blood in the tissue. In an advantageous alternative, both methods can be combined.

[0184] In a further preferred embodiment, the thickness of the parts (5) impassable for photons is so great that a step (3.3) is created on the side facing the skin and the side facing away from the skin compared to the three-dimensional volume of the sensor surface (3). The two steps can be seen in Fig. 6. Depending on the thickness of (3), a cavity (8) can again be created above the sensor components, which is filled with air, for example. In a preferred variant, the resulting enclosed spaces can each contain an emitter or a detector. In a further preferred variant, more than one emitter and / or more than one detector are located in each of the individual spaces, in several of the spaces, or in all of the spaces. Fig. 7 shows an example of two emitters (1) and two detectors (2) in each of a common space formed from the components (5) and the sensor surface element (3).In an advantageous view, an RGB emitter or another emitter that can emit photons in multiple wavelength ranges is not considered as a single emitter, but as multiple emitters. Figures 7 and 7a show an example of two emitters and two detectors, respectively, in an enclosed space. Multiple emitters and / or multiple detectors can be arranged in an enclosed space. The enclosed spaces can have single or multiple openings (3.2) in the sensor surface element (3). Figure 7 shows an example of an opening (3.2) in the sensor surface element.

[0185] In an advantageous variant, an enclosed space can also be understood as a spatial area that is enclosed by non-transparent material or skin. Such a spatial area can be important for sensor design, since photons can only leave or enter this space if they pass through the skin. Since this is an important aspect for a measuring device that measures the optical properties of skin, emitters and / or detectors are advantageously arranged in such enclosed spaces. Fig. 9b shows a variant in which the components (5) are connected to form a unit (5b) that does not have any transparent parts of the sensor surface element (3). This results in three-dimensional openings (3.2) in component (5b). The unit with the three-dimensional openings (3.2) can be subsequently applied to the circuit board (6). The advantage of such a solution is that there are no light losses, e.g.as a result of absorption by the transparent sensor surface element. In a preferred embodiment, the unit (5b) can also be part of the housing of the measuring device. In an advantageous variant, the circuit board (6) is inserted into the housing and connected to the unit (5) or (5b) in such a way that photons cannot migrate from one space enclosed by the circuit board (6) and component (5) and the applied skin (4) to the other without passing through the skin. The advantage of this solution is that the housing and sensor surface element can be manufactured in one production step, which reduces production costs. Fig. 8 shows that, for example, the openings (3.2) from Fig. 9b can also be filled or potted with transparent material of the three-dimensional sensor surface element (3) in a second production step, so that the sensor components are enclosed by this material and a flat, homogeneous surface towards the skin (4) is created.Due to the surface tension of the potting material, the surfaces of the potted openings can, for example, be concavely curved. Other curvatures or waviness of the surfaces are also possible.

[0186] It should be noted that the sensor surface element can also consist of one or more transparent elements (3) and one or more non-transparent elements. Likewise, the non-transparent elements (5) can be separate or a single connected element. This makes the linguistically correct use of singular and plural in the description difficult. The use of the singular should therefore not be seen as restrictive in the context of this description. It is clear to a person skilled in the art that the function according to the invention can generally also be provided by several elements. Conversely, when the plural is used, the several elements can often be combined into one and that the function according to the invention can be provided with the then resulting single element. In this respect, the use of the plural should not be seen as a restriction that a single element cannot also be used.

[0187] In another preferred variant, the enclosed spaces each contain a cavity (8) filled with gas, for example, air (cf. Figs. 5, 6, 7). In a particularly preferred embodiment, a unit (9) is produced, for example, by injection molding. This unit consists of the three-dimensional volume of the sensor surface element (3), which has a certain thickness (3.1), and the components (5) that are at least virtually impassable for photons. This unit (9) can be subsequently applied to the circuit board with the emitters and detectors in such a way that the emitters and detectors are located in enclosed spaces. The components (5) and the thickness of the three-dimensional sensor surface element (3.1) are then dimensioned such that collisions with the emitters (1) and detectors (2) do not occur when the unit (9) is placed on the circuit board. Figs. 9 and 9a show a corresponding example.The advantage of this solution is that the unit (9) can be manufactured as a 2k component in a single work step and, unlike with potting, there is no warping of the volume of the sensor surface element (3) as a result of potting. In a preferred embodiment, the unit (9) is connected to the circuit board in such a way that the contact point (6.1) between the circuit board (6) and the unit (9) is almost impassable for photons. The connection between the circuit board (6) and the unit (9) can be made, for example, by liquid adhesive or by double-sided adhesive tape or by melting and pressing the material that is almost impassable for photons onto the circuit board or by screwing it to the circuit board.

[0188] In Fig. 7, the dashed lines show the emission of photons, their migration through the skin, and their arrival at the detector. During measurement, a portion of the photons emitted by the emitters (1) passes through the three-dimensional component of the sensor surface element (3), penetrates the skin (4) via the outer layer of the skin (4.1), migrates within it, and exits it, e.g., at another location on the skin. They then overcome or pass through the three-dimensional component of the sensor surface element (3) again in the aforementioned manner. This occurs either through openings in the sensor surface element (3.2) or by passing through the material of the three-dimensional sensor surface element (3). A portion of the photons then reaches a detector (2) of the measuring device and is detected there.The optical properties of the measured sample can be deduced from the quantity and wavelength of the photons that travel the path described above from the emitter to the detector and are not absorbed or scattered to other locations. From the combination of the measurement results of different combinations of emitters and detectors, with advantageous arrangements, conclusions can be drawn about the substances present in the skin and the underlying tissue and their concentration. In a likewise preferred variant, additional three-dimensional components (5a) that are almost impassable for photons can be located above a unit (5b). These components have openings (3.2) through which photons can pass. These openings can be referred to as windows. Fig. 10 shows an example. In a likewise preferred variant, the windows can contain a material that is passable for photons, e.g. the material of the three-dimensional sensor element (3). Fig.10b shows such a variant. As can be seen in Fig. 10b, in a likewise preferred variant, the thickness of the material (3) through which photons can pass can correspond to the thickness of the additional components (5a) that are almost impermeable to photons, so that the side facing the skin has a smooth and / or flat surface. The windows can, for example, or they can form any desired pattern. As Fig. 10a shows in a preferred variant, the additional components (5a) that have openings (3.2) can be in contact with the three-dimensional sensor surface element (3). In a likewise preferred variant, the components (5a) are located at a defined distance above parts of the sensor surface element (3) made of transparent material. The additional components (5a) can together form a monolithic unit.

[0189] In a preferred variant, this additional monolithic unit can be a separate component that is only placed on the sensor surface for specific measurements. It can rest directly on the sensor surface or be located at a defined distance above the sensor surface. The advantage of this solution is that certain substances that are located at a certain depth within the sample, for example skin or tissue, can be detected more precisely because the geometry of the openings (3.2) means that the photons only penetrate the sample at certain angles and thus, on average, pass through the skin layers in which the substances are primarily located. The accuracy of the detection of these substances is thus improved.

[0190] In a preferred variant, a monolithic unit (5a) specifically tailored to each substance to be detected can exist, which is then placed on the measuring instrument in the sensor area whenever this substance is measured. As previously described, in a preferred embodiment, the windows in the additional components (5a) can be designed and arranged such that photons can only leave the measuring device at limiting angles to penetrate the skin. This applies analogously when photons are detected by the detector. They only reach the detector at limiting angles that are predetermined by the design of the windows in the additional components (5a). In Figs. 10, 10a and 10b, such limiting angles are shown as dashed lines.In a preferred variant, additional components (5a) are designed and arranged such that they are located parallel to one another on the components (5) at a defined distance. Figures 12 and 12a show such a case. The resulting distances between the additional components can be different, resulting in, for example, slit-like windows. The arrangement restricts the directions in which photons are emitted by the measuring device to certain solid angle ranges. In one embodiment, the arrangement reduces the radiation in certain solid angle ranges. Figures 12 and 12a show an example. For clarification, a compass rose with four cardinal directions is drawn there. If the slit-like windows run in a north-south direction, the radiation in east-west solid angle ranges is particularly restricted.If the slit-like windows run in an east-west direction, the restriction particularly affects the solid angle ranges in a north-south direction. It will be clear to a person skilled in the art that, depending on the arrangement of the additional components, the restrictions in radiation can also occur in all other directions in between. In a preferred embodiment, a transparent component (7) can be located above the additional components (5a), which is in contact with the skin (4) during measurement. Figures 11 and 12b to 12e show corresponding examples. The material thickness of the component (7) can be designed such that a common cavity (8) is created, within which the components (5, 5a) impassable for photons and the emitters (1) and detectors (2) are located. This can be seen, for example, in Figures 12b, 12b2, 12c and 12c2. In a further preferred embodiment, the additional components (5a) are integrated into the volume of the component (7).Examples can be seen in Figures 12b1, 12b4 and 12c1, 12c4. In a further preferred variant, a transparent three-dimensional component (3), which is part of the sensor surface element, is located above the emitters (1) and detectors (2), so that the additional components (5a) and the component (7) are located above this part (3) of the sensor surface element. Corresponding examples are shown in Figures 12b3, 12b5 and 12c3, 12c5.

[0191] In an alternative variant, the additional components (5a) are not parallel. In another alternative embodiment, the additional components (5a) have a different shape than the rectangular one shown. A person skilled in the art of optics can easily calculate which shape has which effect on the direction of the photons that can travel through this arrangement and which photon directions cannot travel through such an arrangement. This approach gives rise to numerous alternative embodiments with which the emission direction of the photons can be influenced. By influencing the emission direction, the photons take different paths through the tissue to be measured. In one advantageous variant, this sets particularly advantageous paths for the measurement.In an alternative advantageous variant, paths are also set which do not allow the measured variable to be recorded particularly well, but which allow any interfering effects on the measurement to be assessed. For this reason, it is particularly advantageous if different paths for the photons can be set. In an advantageous variant, this is also achieved by providing different influences on the emission directions. In an advantageous variant, components (5a) are used to influence the emission direction of an emitter, but which have different effects when interacting with two different detectors. For example, an arrangement which can emit photons relatively flatly in a westerly direction, in interaction with a detector located west of the emitter, will receive photons which have mainly passed flatly through the sample.A detector located north of the emitter preferentially receives photons that have penetrated deeper into the tissue. Devices for influencing the radiation characteristics can also be used analogously to influence the reception characteristics of detectors. The physical relationships and advantageous embodiments are accordingly considered to be in accordance with the invention, without being explicitly described here.

[0192] In a preferred embodiment, the component (5a) can penetrate the transparent component (7) in such a way that it is impossible or virtually impossible for photons to migrate within the material thickness of the component (7) and thus reach the detectors without first passing through the skin. Figures 12d, 12d1, and 12d2 show corresponding examples.

[0193] The component (7) can be made of, for example, plastic or glass or any other material that photons can pass through. It can have optical properties that, for example, only allow photons to pass through in certain preferred directions and / or at certain wavelengths. It can be a lens that specifically directs the photons. The material can be opaque or scattering. The component can have thermal properties and, for example, be electrically heatable or have a temperature-compensating effect, for example to create comparable temperatures between the skin and the measuring device during measurement. The component (7) can also be located above all other described variants of the measuring device.

[0194] In a preferred variant, component (7) can have a concave, three-dimensional curvature in the direction of the sample, e.g. the skin, which in its shape acts, for example, as a positioning aid for a hand, so that a user who wants to have skin contact with the sensor for measuring always carries out the measurement on the same area of ​​skin, or at least almost on the same area of ​​skin, if they align their hand with the positioning aid in a predetermined manner, e.g. pictorially and / or in writing, communicated to the user. The shape of component (7) in Figures 12c to 12c5 indicates this bulge. In a preferred variant, the three-dimensional curvature not only serves as a positioning aid, but also prevents the sensor from being scratched due to the concave bulge, for example, when the measuring instrument rests with the sensor side on a table or is stored in such a way. In a preferred variant, the sensor has a convex bulge.This is shown in Figures 12d and 12dl to 12d5.

[0195] In an equally preferred variant, a positioning aid consisting of transparent and / or photon-impermeable material can be located as a separate component on component 7 or component 5, 5a or 5b. In a preferred variant, the positioning aid is three-dimensionally shaped in such a way that it prevents ambient light from penetrating the sample laterally during measurement, e.g., into the skin in the area of ​​the edge of the hand, from penetrating skin and tissue, reaching the detectors and thus influencing the measurement result. In an equally preferred variant, the positioning aid is removable and can be applied by the user, e.g., to the sensor side of the measuring instrument housing before a measurement and can be removed again after the measurement. Fig. 35 shows an example. In a preferred variant, with a removable positioning aid, the fixation on the sensor side of the measuring instrument is such that the positioning aid, e.g.,has domes that are inserted into small openings in the measuring instrument and click into place there, for example reversibly. It will be clear to a person skilled in the art that other types of reversible fixing of the positioning aid on the sensor side are also possible, for example fixing using magnets. In a preferred variant, the positioning aid can, in contrast to that shown in Fig. 35, also have a curved contour that is at least approximate to the contour of the hand, for example, and it can also have laterally sloping and / or rising flanks. In a preferred variant, the three-dimensional positioning aid is not a separate component that is placed, for example, on components (5) or (5a), but is an integral part of components (5) or (5a). In a preferred variant, the three-dimensional positioning aid is an integral part of the housing of the measuring instrument.Due to the photon-impermeable or nearly impermeable components (5) and (5a), detectors in an advantageous design can only detect photons from an emitter that have passed through the skin or the human body at a certain depth and in a certain direction. The photon light paths vary depending on the wavelength of the emitted photons, the geometric or spatial placement of the emitters and detectors, their number, and the respective direction of entry of the photons into the measuring point / contact point on the skin.

[0196] The light paths also depend on the skin being measured. Measuring devices are typically designed to include light paths that provide sufficient measurement accuracy for all or average skin types. In particularly advantageous designs, the sensor has additional light paths that optimize the measurement of specific skin types. In particularly advantageous designs, the sensor has additional light paths that enable measurement accuracy at particularly high concentrations of a specific substance.

[0197] In a further advantageous embodiment, the sensor has additional light paths that enable measurement accuracy at particularly low concentrations of a specific substance.

[0198] For the purposes described in the three preceding sections, the arrangement can be designed such that particularly short light paths and / or light paths with particularly high detection intensity are provided for wavelength ranges of substances in which the substance exhibits strong absorption and / or for wavelength ranges in which a certain skin type exhibits stronger absorption. In previously described variants, the components (5, 5a) that are at least virtually impassable for photons can be arranged and designed such that the angle of the photons upon entering the contact surface of the skin, and thus the direction of travel of the photons in the skin, is specifically influenced.In this way, it is possible to influence the number of photons that enter the skin steeply or shallowly and, on average, travel through the skin at shallow or greater depths before exiting it, and, if present, pass through the three-dimensional component of the sensor surface element again and are then recorded by the sensor's detectors. Due to this influence, the detector (2) can only detect photons that exit the skin at certain solid angles and pass the sensor surface elements at certain angles and reach the detector. The respective angles for emission and detection can be different. An example is shown in Figs. 10, 10a and 10b. In addition to the previously described influence on the angle during emission, the influence on the angle of entry of the photons into the skin can result from component (7). This can, for example,with the lens function or possible scattering bodies in this component. During detection, the influence of component (7) on the angle has an impact on the amount of detectable photons that reach the detector at a certain angle. Components (5) and (5a) limit the angular ranges from which a large percentage of the incoming photons can be detected. Examples of the steepest angle are shown in Figures 10 and 10a as a dashed line. In Figures 10, 10a and 10b it is assumed that photons that strike components 5 or 5a are absorbed. This is the case for an advantageous design variant in which components 5 and 5a are made of strongly absorbing material, e.g. black. In an alternative design, materials can also be used in which photons that strike component 5 or component 5a are reflected.This results in different angular ranges for the emitted photons.

[0199] Distribution of emitters and detectors

[0200] In a preferred technical embodiment, the emitters (1) and detectors (2) are distributed approximately evenly in the region of the sensor surface, resulting in both different emitter-detector distances and redundant emitter-detector distances. In an advantageous variant, emitter-detector distances are measured on the plane of the sensor surface as a direct line from the center point of one of these components to the center point of the other component. Fig. 13a shows different distances between emitter and detector. They are drawn as distance arrows lei to lc4. The distances lei and lc4 are identical and can be referred to as redundant distances. In the case of a curved sensor surface, the curvature is not taken into account when determining the distance in an advantageous, simplified variant.As shown in Figure 13, in this variant the distance (1c) between emitter and detector is calculated as follows: A perpendicular falls through the center of an emitter onto the circuit board (6), or the common plane on which the emitter and detector are located. A second perpendicular falls through the center of a detector onto the circuit board (6) or the common plane on which the emitter and detector are located. The distance is determined by the distance between these two parallel perpendicular lines. In an advantageous view, the emitter-detector distance (1c) is a characteristic value for the path that the photons travel from the emitter to the detector. The term light path can therefore be used in this document to refer to the distance from the emitter to the detector in a corresponding context.

[0201] In an alternative, advantageous variant, the distance from emitter to detector is defined as the shortest line from the transparent area of ​​the contact surface to the sample to be measured, which is acted upon by the emitter, to the transparent area of ​​the contact surface to the sample to be measured, which is acted upon by the detector. In an alternative, advantageous variant, the distance from emitter to detector is defined via the spatial extent of the light paths of an average or typical sample. This spatial extent results from the paths taken by the photons that make it from the emitter to the detector. Each photon follows its own path, which can be simulated using statistical methods. The light path length is then determined from the average length of these paths.Alternatively, the light path length is determined for each emitter-detector pair based on the distance between the center of gravity of the photon exit points from the measuring device, which make it from the emitter to the detector, and the center of gravity of the photon entry points, which make it from the emitter to the detector, into the measuring device. The use of the various definitions allows for a more precise physical representation in some cases and a more easily comprehensible, but also physically more simplified, consideration in other cases. Such variation in the distance definitions for the design of comparable sensors is known and has already been published elsewhere and is common practice. The advantageous arrangements described can be usefully applied under several of these definitions.

[0202] In a further preferred embodiment, emitters and detectors, which preferably serve to detect a specific substance, are distributed such that the distance lengths between emitter and detector are predominant, in each case the distance lengths which make the greatest contribution to the detection of this substance. In a preferred technical embodiment, the advantageous distance lengths are up to 10% higher, in another preferred embodiment up to 20% higher, in a further embodiment up to 30% higher, and in a particularly preferred embodiment up to 40% higher, and in very particularly preferred embodiments up to 50% higher, up to 100% higher, up to 200% higher, and up to 400% higher than the less important distance lengths. In a preferred embodiment, the number and distribution of the emitters and detectors result in a total of at least 50 light paths, and in a further preferred embodiment at least 100 light paths.In more preferred embodiments, at least 200, at least 400, at least 800, or at least 1600 light paths result, whereby more than one emitter can be located in a previously described enclosed space. In a preferred embodiment, the measuring device has a total of up to 6 emitters and detectors, and in another preferred variant, a total of up to 9 emitters and detectors, which, in the aforementioned sense, are either considered to be approximately identical sensor components and / or differ in at least one technical property from the sensor components considered to be approximately identical.In the aforementioned sense, in other preferred embodiments the measuring device has a total of 10 to 16, in further preferred embodiments the sum of emitter and detector is between 17 and 30, in other particularly preferred embodiments the sum of emitter and detector is between 31 and 50, in further preferred embodiments the sum of emitter and detector is between 51 and 70, in further preferred embodiments the sum of emitter and detector is between 71 and 100, in additionally preferred embodiments the sum of emitter and detector is over 100. In the aforementioned embodiments, RGB emitters are counted as 3 emitters. The same applies to other emitters that can emit different wavelengths. Through targeted design and targeted combination of the above-mentioned influencing factors, the sensor can be specifically aligned to the substances to be measured.In a particularly advantageous embodiment, the combination of emitters, detectors and their wavelength ranges and their emitter-detector distances is selected such that at least 2, preferably 3, even more advantageously 4 or 5 or more than 5 different substances can be measured. In an advantageous embodiment, some of the light paths provided for one substance are also used to determine or to improve the accuracy of the determination of at least one further substance. In a preferred embodiment, the emitters are switched on one after the other in a specific order for the measurement, so that only one emitter emits photons at a time. In an equally preferred embodiment, more than one emitter can be switched on simultaneously to measure a substance.The composition of the emitter groups, which are switched on one after the other, as well as the number of emitters belonging to a group, can vary. Surprisingly, it was found that the following factors influence the accuracy of the detection of a substance concentration within a measurement sequence: order, duration, light intensity, and frequency of switching on the respective emitters. In an advantageous variant, a measurement sequence is selected in which the same combination of an emitter and a detector is activated multiple times, and the same light path is measured. In an advantageous variant, a temporal progression of temporally variable substance concentrations, such as those caused by the human pulse or heartbeat, is also recorded.In a further advantageous embodiment, multiple measurements of the same light path are performed in order to determine it under changing conditions and to incorporate the measurement results from the different conditions into an optimized calculation of a result. For example, the light path is first measured at one temperature and then at least a second time at a different temperature. This measure allows the temperature dependence of the emitters and detectors to be specifically exploited. A particularly advantageous variant exploits the fact that some emitters have temperature-dependent wavelength characteristics. This method allows more information to be determined in a targeted manner. A particularly advantageous variant uses this method to determine the wavelength-dependent change in the measurement results of a light path.The resulting absorption gradient as a function of wavelength can be used to correct and optimize measurement results.

[0203] In one advantageous variant, the temperature change is brought about by activation of the emitter. In another advantageous variant, the temperature increase is achieved by multiple activation of the emitter and / or another emitter in close proximity. In an alternative, particularly energy-saving, advantageous variant, the heating is generated by placing a body with an approximately known temperature on the surface. In one advantageous variant, the temperature increase is generated by placing the sample on the surface, which, as living human tissue, has temperatures of over 30 and typically under 40 degrees Celsius. In one advantageous variant, this results in an analyzable gradient, at least for measurements that begin at normal room temperature. In another advantageous variant, the temperature change is achieved by waste heat from other electronic components. In one advantageous variant, the emitter is increased by a temperature of at least 0.1 degrees Celsius.Even more advantageously, by at least 1 degree Celsius, by at least 10 degrees Celsius, by at least 50 degrees Celsius.

[0204] In an advantageous variant, a defined part of a measurement is considered a measurement sequence. This means that measurements can consist of one or more measurement sequences between which contact between the sensor and the skin is not interrupted. For the precise determination of substances, it may be necessary to carry out several measurements with their respective measurement sequences one after the other. The measurement sequences can be designed so that a sequence is only used to detect one substance and, for example, only certain emitters are switched on one after the other for a certain duration with a selected light intensity and in a certain order. The measurement sequence can be designed differently for each substance. An advantageous variant is to use a measurement sequence that can measure several substances.

[0205] When performing multiple measurement sequences or even complete measurements, bleaching effects can occur, which impact the accuracy of substance concentration determination. This effect can vary between substances. If the concentration of a substance is low at a certain depth of the skin area being measured by the measuring device, the bleaching effect on the signal-to-noise ratio is more pronounced and, in contrast to a higher concentration, also reduces the accuracy of the measurement more significantly or makes correct detection of the substance impossible. Another reason for the difficulty in measuring a concentration can be that substances are predominantly distributed in certain layers of the skin or in the blood.If deeper layers of skin or even blood vessels have to be analyzed, it may be necessary to improve the signal-to-noise ratio for the long light paths so that even low concentrations can be easily detected.

[0206] Surprisingly, it was found that by specifically adjusting and / or combining the switching-on duration and / or light intensity and / or frequency of switching on specific emitters within a measurement sequence, as well as the order in which the emitters are switched on within a measurement sequence, the bleaching effect has no negative or only a slightly negative impact on the detection of substances. If the targeted adjustment of a measurement sequence influences the accuracy of the concentration determination of another substance to be detected in a subsequent measurement sequence, the adjusted measurement sequence is preferably carried out as the last sequence of a measurement. In an advantageous variant, targeted bleaching can also be used for the precise determination of substances that decompose under the influence of specific wavelengths. In this case, at least one light path is specifically measured multiple times.At least once before activating the bleaching sequence and then again after the bleaching sequence. In a more advantageous variant, even once or several times in between. During the bleaching sequence, emitters of a suitable wavelength are used to partially decompose a specific substance in the skin.

[0207] Most substances are distributed inhomogeneously throughout the human body. This applies not only to concentration differences within a single skin area, but also to comparisons between different skin areas. In a preferred design, the duration of the emitters' activation, their light intensity, as well as the order and frequency of activation of the emitters, can therefore be individually determined for each user and each skin area.

[0208] An advantageous variant is to individually determine the influencing factors by first determining how much a skin area or a person deviates from an empirically determined standard setting. Therefore, the first measurement sequence within a measurement should ideally correspond to this standard setting. By analyzing the individual light paths, the ratio of the amount of light detectable at the detector between light paths of different lengths is determined in an advantageous variant and the deviation from the empirical standard is determined. In a preferred variant, all emitters and detectors of the measuring device are used in this measurement sequence. In accordance with the previous definitions, the light path is understood here to be, for example, the distance between emitter and detector or the most probable path that a photon takes from the emitter to the detector.In a preferred variant, a second measurement sequence is used to individually adjust the influencing factors, depending on the deviation, for the measurement area or the individual. This adjustment can be the same for all substances to be detected. However, it is also possible that the adjustment is different for each substance, and the detection of each substance must be performed using a separate measurement sequence, in which, for example, only certain emitters are activated. The order of the substance-specific measurement sequences is then determined, for example, with a view to achieving the lowest possible bleaching effect.

[0209] In an advantageous variant, the measurement is controlled via an app, which runs on a smartphone or smartwatch, for example. As soon as the app has received the individualized settings, it prompts the user, for example, to re-establish skin contact with the sensor. The subsequent measurement with the individualized measurement sequences starts automatically, for example, as soon as the app has registered the re-established skin contact. In a preferred variant, the app can determine the individualized settings itself. By individualizing the measurement with regard to the measurement sequences it contains, a measurement optimized for the correct concentration determination is possible for each user. It is possible that the computing effort required for the individualization does not take place on the measuring device itself, but on an external server. In a preferred variant, the measuring device sends, for examplewith the help of a special app, the spectral data of the standard measurement sequence is sent to a server and receives from the server the settings for the individually tailored measurement sequences, which were determined there, for example, with the help of AI. The data can be sent via the internet to the external server from the measuring device itself, for example. In an alternative, advantageous variant, the measuring device transmits data to the server by transferring it to an app. The app can advantageously run on a smartphone, a smartwatch, or another device with internet access. The data can advantageously be sent via a cellular network. In an alternative, advantageous variant, the data can be transported to the server via WLAN, LAN, or other communication channels that are currently common or that will become available in the future.

[0210] In a particularly preferred variant, the measuring device sends the data via WiFi or Bluetooth, for example, to a mobile device (e.g. smartphone or tablet), which then sends it to the external server via mobile communications (e.g. 4G, 5G) over the Internet or uses an existing WiFi network to send the data. In a preferred embodiment, the data is encrypted before being sent. In an equally preferred variant, the server sends the settings for the individually tailored measurement sequences back in encrypted form via the same route to an app on the mobile device. In an advantageous embodiment, the server only ever sends the settings to the device that sent it the data.

[0211] In a preferred variant, the influence of certain skin characteristics on the measurement result can also be compensated for by individualizing the measurement. This applies, for example, to skin type, skin spots, wrinkles, scars or roughness of the skin. In a likewise preferred variant, the correct recording of the concentration of a substance is improved by changing the number of repetitions of at least parts of the individual measurement procedure within a measurement. In an advantageous variant, a standard setting is initially selected which, for example, includes 1, 2, 3, 4, 5 or more repetitions of the measurement procedure. In an advantageous embodiment, the concentration of the substance is then calculated for each individual measurement procedure and the deviation between the individual results is determined. If the deviation is too great, the user is prompted to carry out another measurement with a specific number of measurement procedures.As those skilled in the art will know, measurement errors can be partially reduced by taking more measurements, i.e. more measurements lead to a lower standard deviation of the overall measurement result obtained from all partial measurements. For this reason, the number of measurement procedures or even the number of measurements could be increased from the outset to ensure a correct result. The advantage of the aforementioned procedure, however, is that no more measurement sequences or complete measurements have to be performed than is necessary for the individual case. The number of measurement sequences required within a measurement can vary between individuals. This advantageous procedure saves the user time. At the same time, however, this advantageous procedure reduces measurement errors that can arise from bleaching as a result of an excessive number of measurements.In an advantageous variant, the number of measurements taken is calculated in such a way that a sufficient number of measurements is achieved to achieve the desired accuracy, but at the same time bleaching is avoided.

[0212] In an advantageous variant, at least a number of repeated measurements per light path is carried out that exceeds 1, 2, 4, 8, 16, 32 or, in the most advantageous variant, 64. In an advantageous variant, the number of repetitions per light path is limited to a value such that it does not exceed the value of 2, 4, 8, 16, 32, 64, 128, 256 or 1024. Since almost all substances in skin and tissue are inhomogeneously distributed, the concentration can fluctuate from measuring point to measuring point. In a preferred embodiment, the size of the sensor and the placement of the emitters and detectors are therefore selected within the scope of this invention such that the sensor size can capture a representative section of the inhomogeneous distribution, so that the same measurement results are obtained when the sensor is brought into contact with the skin again, provided the concentration of the substance has not changed for physiological reasons.

[0213] For everyday use, an appropriately selected sensor / sensor surface size is a great advantage because, during repeated measurements, the measured concentration level is almost unaffected by the inhomogeneous distribution, so that, within the measurement error tolerance, a changed measurement result can be attributed to physiological changes. In an advantageous variant, the measurement setup therefore has a mounting area for optoelectronic components of at least 100 mm. 2 In an alternative advantageous variant, the measuring arrangement therefore has a size of the mounting area of ​​optoelectronic components of at least 225 mm 2 In an alternative advantageous variant, the measuring arrangement therefore has a mounting area of ​​optoelectronic components of at least 400 mm 2The size of the mounting area for optoelectronic components is defined as the area of ​​the smallest circle or smallest square into which all of the emitter and detector chips projected onto the circuit board of the measuring device fit. In an advantageous variant, the area of ​​the smallest circle or smallest square takes into account the necessary wiring for controlling the emitter and detector chips and / or the necessary contact surfaces on the circuit board for attaching the emitter and detector chips. Surprisingly, it was found that with a certain sensor area size and through targeted design of the aforementioned measurement sequence adaptation, in conjunction with the selection of the time for the first repeat measurement, the dynamics of the change in a substance concentration can already be determined. This means that future values ​​of the substance concentration can be predicted with advantageous variants of the invention.

[0214] The sensor surface that comes into contact with the skin during a measurement should, in an advantageous variant, be between 0.5 cm 2 and 10cm 2 In a preferred embodiment, the sensor surface has a size of max. 1cm 2 , in a further preferred embodiment a size of at least 1.5cm 2 , in a preferred version of at least 2cm 2 , in a more preferred version of at least 2.25cm 2 and in more preferred versions at least 4cm 2The size of the sensor surface (3a) of the measuring device is therefore, in a preferred embodiment, for example, max. 10 mm x 10 mm, in another preferred embodiment, at least 12 mm x 12 mm, in a highly preferred technical embodiment, at least 15 mm x 15 mm, and in a particularly highly preferred technical embodiment, at least 20 mm x 20 mm. Depending on the detection task, it can also be at least 25 mm x 25 mm. Fig. 1a shows an example of what is meant by the size of the sensor surface (3a). For special applications, the preferred sensor surface can also be max. 8 mm x 8 mm; in a particularly preferred embodiment, it can be max. 6 mm x 6 mm or a maximum of 25 mm x 25 mm. It is clear to those skilled in the art that the sensor surface does not have to be square. It can be, for example, rectangular, round, or approximately round, but it can also have any other desired shape. Measurement of substances

[0215] It has been established that the measuring device described above, with an advantageous design, enables the differentiated analysis of various substances. This includes, for example, the measurement of carotenoid concentrations in human tissue and blood, whereby a distinction can be made between the concentrations of lutein, zeaxanthin, ß-cryptoxanthin, α-carotene, ß-carotene, and lycopene. When measuring in humans, the individual measurement of carotenoids is important because, for example, the absorption of ß-carotene and lutein can mutually inhibit each other. For any transmission of information to the user, for example, the communication of measurement results, this information is preferably presented as a numerical value and / or as a graphic and / or as text information, e.g.combined with appropriate advice, can be displayed on the display of the measuring device or a device that communicates with the measuring device and / or read out to the user as audio information and / or presented as a video. Signaling to the user can also be done in other known ways. This also applies to the other parts of the text that address communication with the user. This includes, among other things, the use of symbols and colors, light signals or any other signal that can be perceived by the human senses. It is particularly advantageous to use a signal that is visible, audible, tangible, smellable or tasteable. Direct transmission of information to the brain or nervous system would also be conceivable as soon as this is technically advanced enough.

[0216] With regard to nutrition, a connection to a device for influencing the appetite center would be particularly advantageous, as soon as this is technically feasible. Indirect communication is also possible, for example, by having objects in the user's environment exhibit a certain automatic behavior. Examples include:

[0217] Refrigerator or cabinet doors that open or lock

[0218] A fruit bowl that turns the optimal fruit towards the user or turns away or covers the less optimal fruit

[0219] A kitchen machine with recipes that preferentially presents particularly suitable recipes

[0220] A shopping app that suggests particularly suitable recipes. This functionality can also be implemented, for example, as an online shop or as an add-on service for such an online shop. As an alternative to influencing food in one of the ways mentioned above, medications or nutritional supplements can also be processed, for example, by automatically dispensing them in individually measured doses from a dispenser. Also conceivable are beverage or smoothie vending machines, or other food vending machines that control the automatic addition of ingredients or substances based on calculated recommendations.

[0221] It is also conceivable to give the user small electric shocks if he behaves contrary to the recommendations

[0222] It is also conceivable to have indirect communication, e.g. with a life partner or a family member or a trusted person in the circle of friends or a trusted medical person such as the family doctor or the nutritionist in one of the ways mentioned.

[0223] The above-mentioned variants can be understood as indirect signaling to the user. They can also be viewed as support systems for behavior change.

[0224] In an advantageous variant, the communication, signaling and / or behavior change support methods or their components can be integrated into all variants of the device that communicates a result or a recommendation or other information to the user or to a person associated with the user.

[0225] Individual metabolism

[0226] With the help of spectroscopic measurements, it was surprisingly discovered that, with an advantageous design, the measuring device described here can be used to determine the individual metabolism of food. In order to determine the physiologically determined individual metabolism from the concentration measurement of substances that are also contained in a food, additional information is collected from the user and processed using IT.

[0227] In a preferred variant, for example, information is recorded from the user which can influence the measured concentration of a substance in the body independently of metabolism or at least partially independently of metabolism. In a preferred embodiment, the information can be, for example, one or more of the following: lifestyle or habits such as smoking, alcohol consumption, length of sleep, length of time spent in the sun, use of a tanning bed, intensity as well as frequency and duration of physical exertion, e.g. through sport, private and professional stress. Information that is also useful to record is, for example, the way in which food is consumed by the user, whether it is raw, cooked, boiled, pureed, or whether fruit and vegetables were consumed, for example, in the form of a smoothie, e.g. with oil, etc.In a preferred embodiment, the strength of their influence on the concentration determination is determined, for example, by comparing the measurement results of a large number of users under the aforementioned aspects, in order to determine an average influence on the concentration determination, for example, with the help of artificial intelligence. In a preferred variant, general scientific findings on metabolic processes in the human body are also taken into account.

[0228] If the individual metabolism of a certain substance is to be determined for a specific user, in a preferred embodiment they are first asked to provide the amount of food or substance consumed, e.g. in grams, to the app, which communicates with the measuring device. In a preferred variant, this can be done, for example, by manual entry, voice input or uploading a photo of the amount consumed. Scanning codes on packaging is also an advantageous variant. Transferring data from scales is also an advantageous embodiment. In an advantageous variant, the amount of food consumed can be weighed and / or the change in body weight due to food intake can be determined, e.g. using scales. The data can be stored and / or processed, e.g. in the app itself or by means of data transfer, e.g. to a server.In a preferred variant, the user is also asked to enter as much of the additional information mentioned above as possible.

[0229] In a preferred embodiment, after eating, the patient is asked to take skin measurements using the measuring device described here to determine the concentration of this substance in the blood and tissue, and to repeat these measurements at specific intervals. In a preferred variant, the measurements are taken at intervals of max. 2 hours, max. 4 hours, max. 6 hours, max. 8 hours, max. 12 hours. In other, equally preferred variants, the intervals between regular recommended measurements are max. 24 hours, max. 36 hours, max. 2 days, max. 4 days, max. 1 week, max. 2 weeks, and more than 2 weeks. In a preferred embodiment, a series of multiple measurements is taken at intervals after eating. Preferably, any interim ingestion of the substance is taken into account. Using the measurement results from several of the time intervals mentioned in the previous paragraphs, it is also possible to detect, for example, a delayed accumulation in the tissue.In order to improve the measurement accuracy, in a preferred variant, several measurements are carried out one after the other at each measurement time and evaluated in order to improve the accuracy of the measurement, for example by averaging and / or outlier detection. In a further preferred variant, the measurement accuracy is improved by using the previously described individual measurement sequences. In a preferred variant, at least 3, at least 5 or at least 10 consecutive repeated measurements are carried out at the respective measurement times, whereby the measurement times have, for example, the intervals mentioned above. In further preferred variants, a maximum of 20 repeated measurements, a maximum of 30 repeated measurements or more than 30 repeated measurements are carried out at the respective measurement times in order to, for example, further improve the measurement accuracy. In a preferred variant, for exampleFor a specific user, the individual metabolism of the substance is calculated using various mathematical methods based on the user's information on the amount of the measured substance consumed and / or the additional information provided by the user and / or the measurement results obtained at different measurement times and / or taking into account the average influence of metabolism on the measurement result determined with the help of a large number of users. In a preferred variant, the amounts, e.g. in grams, that the user should consume in order for the substance to accumulate in the body at a desired concentration can be calculated from this. In a preferred variant, the calculation is carried out again as soon as the database for the calculation changes, e.g. if the user saves additional and / or new information, e.g. via the app, or e.g.new scientific findings on metabolic processes are available.

[0230] In a preferred solution, the calculations for the individual metabolism of a substance also take into account whether substances that impede the absorption of another substance have been ingested at the same time. In a preferred variant, a user-specific model is created that allows at least a rough, and in a preferred variant, a good, prediction of which foods affect the concentrations of at least one desired substance in the user's tissue.

[0231] The following sections describe advantageous embodiments in which information useful to the user is obtained from measurements taken with the described device about one or more substances in the user's body and their temporal progression determined from multiple measurements, and if necessary with the addition of further information. In an advantageous variant, this information can be a behavioral recommendation and / or a nutritional recommendation. In a further preferred variant, by comparing measurement results from different measurement times, it is determined whether there is an individual saturation curve with repeated intake of a substance and what gradient exists between intake and measured concentration in the tissue and blood. The result is improved calculability and thus predictability of the individual metabolism of dietary substances.In a preferred solution, a comparison is made between the concentrations of two or more substances in conjunction with the calculated individual metabolism if their ratio is relevant to health. An example of this is the desired ratio of omega-3 fatty acids to omega-6 fatty acids, the effect of foods on their glycemic load, or, more generally, the reduction of health risks when certain dietary components are present in the body in sufficient quantities.

[0232] The results of the concentration determination of the various substances, whether as a result of joint measurement or through individual measurements of the various substances of this substance class, are in a preferred variant stored on the measuring device and / or transmitted via the Internet to an external server, stored and calculated with each other in such a way that an individual degree of mutual hindrance in their absorption or metabolism, e.g. of carotenoids, can be determined for the user.

[0233] Mutual interference in metabolism can involve two substances, such as two carotenoids, or even more than two. Their mutual influence can significantly influence the absorption or metabolism of certain other substances. This functional relationship applies not only to carotenoids, but also to other dietary substances.

[0234] In a preferred variant, the individual degree of the respective impairment is determined, for example, by first comparing the measured concentrations with health recommendations for the concentration level in the human body. If deficiencies or excessively high concentrations are detected, in an advantageous embodiment, for example, the concentrations of the substances that mutually hinder absorption and metabolism are first compared and, for example, evaluated mathematically. In an advantageous embodiment, the individual degree of mutual impairment can be determined from this. This could be the carotenoids, for example. In a preferred embodiment, a calculation formula is used which includes the health target values ​​for the substances in question. The result of the formula can be an indicator for the balance of the individual diet.In particular, a carotenoid diet or the intake of one of the other substances mentioned above. In an advantageous variant, this method can also be applied analogously to other dietary substances that interfere with each other's metabolism.

[0235] Using this metric, in a preferred embodiment, individuals can be compared with each other, taking their individual metabolism into account. This comparison is displayed to the user, for example, in graphic form on their mobile device, which receives the measurement results, for example, from the server. This information helps them assess where they stand compared to a reference group. It is generally known that such comparisons encourage people to make behavioral changes that minimize their risk of disease.

[0236] A change in the composition of the fruits and vegetables consumed can, as a result of individual metabolism, be sufficient to improve the ratio of mutually hindering substances, e.g. two carotenoids, to each other, without the total amount of fruit and vegetables consumed having to be changed. In an advantageous variant, such a change in diet is determined from the measured values ​​and user inputs and suggested to the user. In a preferred variant, for example, the user of the measuring device can be informed, together with the display of the result, which fruits and vegetables they should consume alternatively, so that a better ratio of the concentrations, e.g. of carotenoids, is achieved with the same total amount of fruit and vegetables.

[0237] The different types of information that can be provided to the user of the measuring device in addition to the communication of the measurement result and how this can be done are discussed in more detail below.

[0238] In a further preferred variant, the user can also be suggested, for example, a temporal separation for the intake of the mutually hindering substances. For example, in a preferred variant, recipes can be suggested for their lunch that contain vegetables or fruit with high concentrations of a particular carotenoid (e.g., carrots / beta carotene or tomatoes / lycopene), while for dinner or the following day's lunch, they can be suggested recipes that contain this carotenoid only in low concentrations but contain a high concentration of the other carotenoid, e.g., lutein. In an advantageous embodiment, these can alternatively also be corresponding dietary supplements.In a preferred embodiment, the temporal separation in the intake of interfering substances is maintained over a period of at least 4 weeks, with the user being provided with appropriate recipe suggestions for the respective meals over the selected period. In a preferred variant, after consumption, several measurements are carried out using the measuring device claimed here to determine the concentration of, for example, beta carotene and lycopene. In a preferred variant, there is a definable time interval between the measurements. In preferred variants, this is a maximum of 2 hours, a maximum of 4 hours, a maximum of 8 hours or a maximum of 12 hours. The measurement results are saved and the concentration level for both substances, e.g. beta carotene and lycopene, is determined over a period of at least 4 weeks in order to determine the effect of the staggered intake. In an advantageous variant, the user is shown the concentration profile, e.g.B. shown in a graphic and output via an app, for example. Depending on the result, in a preferred variant the amount of food or food supplement containing the two substances can be increased and / or the time interval between consumption can be changed in order to best bring the concentration of the two substances, e.g. beta carotene and lycopene, to a level that has the greatest possible health benefit. In a further preferred variant the time interval between the consumption of food and / or food supplements that contain substances that hinder each other's metabolism can be stretched over more than 12 hours, for example. In other variants, for example, over more than 24 hours, over more than 36 hours or over 48 hours.

[0239] With regard to the varying health effects of certain substances, e.g., carotenoids, individuals have different preferences when it comes to compensating for deficiencies by consuming corresponding foods / dietary supplements. For example, users may be desperate to increase the concentration of a certain substance because this influences the development of a specific disease, regardless of whether it reduces the absorption of other substances. This applies, for example, to the disease pattern of macular degeneration, where sufficient lutein and zeaxanthin must be consumed in order to adequately combat the disease pattern. An advantageous variant of the system can therefore be configured so that the recommendations issued take disease patterns into account or that individually adjustable targets for substance concentrations can be specified.

[0240] In a preferred variant, the support given to the user, such as the selection of fruit and vegetables containing the substances, the amount of fruit and vegetables to be consumed and the suggestion of corresponding recipes and / or nutritional supplements, are generated using algorithms. In a preferred variant, the number of concentration measurements required to determine the amounts actually metabolized and their time interval are also calculated using these algorithms. In a preferred variant, this algorithm also uses comparable data from other users, which was transmitted, for example, to an external server using an app and stored there anonymously, in order to be able to carry out this calculation. In an advantageous variant, certain forms of artificial intelligence (AI) are used for the algorithms in order to be able to make these suggestions to the user.In a preferred variant, a forecast is created based on the consumed amounts of fruit and vegetables or dietary supplements and the measurement results and communicated to the user. This forecast shows how high the concentrations will be at a future point in time. Based on the processed data, alternative forecasts can be calculated by adjusting the amount consumed and the timing of the delayed intake of any interfering substances.

[0241] Measurement of the water content of skin and tissue

[0242] In a preferred variant of the measuring device described above, it was surprisingly discovered that the water content in the skin or tissue can be measured non-invasively upon contact of the measuring device with the skin. Surprisingly, in a preferred embodiment, it was discovered that, for example, it can be determined when a person should drink to enable optimal cognitive performance or to prevent negative consequences for other bodily functions (e.g., bowel movements) and / or organs (e.g., kidneys). In an alternative, advantageous variant, the effect of moisturizers on skin firming can be tested.

[0243] Measurement of body fat percentage and BMI

[0244] In a preferred variant, it was surprisingly found that the body fat percentage can be measured using the measuring device described above. The measurement can be performed on different parts of the body. In a preferred embodiment, the measurement is taken on the inside of the hand in the area of ​​the ball of the hand. With the help of this measurement, it is possible, for example, to detect the effects of diets very early on. This is of great advantage to the user, as they can check the quality of a diet before any weight loss is visible on the scales. Noticeable successes of a diet increase motivation to continue it, whereas in the other case the diet does not have to be continued. Based on the measurement result, users can also be supported in putting together their diet, for example. This will be discussed in more detail elsewhere in this document.

[0245] In an advantageous variant, the measurement can provide a value that correlates with the BMI. For example, the following statement can be made: The measured fat percentage corresponds to an average person with a BMI of X. Where x represents the numerical value of the comparison group. The body mass index (BMI) is a common measure for classifying a person's body weight in relation to their height. It allows one to assign one's own body weight to the following categories: underweight, normal weight, overweight, extreme overweight (obesity), and severe obesity. A disadvantage of the BMI is that it does not differentiate between fat and muscle mass.

[0246] Surprisingly, in a preferred version, it was discovered that the measuring device described here allows for a measurement on the ball of the hand, the results of which are indicators that correlate with, for example, BMI, and better account for muscle mass and body weight due to fat. This allows for the first time a quick and easy determination of fat storage, which is important for weight management, because people who are dieting, for example, want to lose fat, not muscle mass. In a preferred version, this new BMI determination is called "BMI 2.0."

[0247] In a preferred embodiment, the basis for the spectroscopic determination of BMI are algorithms developed, for example, on the basis of neural networks with the help of AI. Fig. 45 shows, for example, a correlation of R=0.61 between the traditionally calculated BMI (kg / m 2= Body weight (in kg) divided by height (in meters squared) and the BMI predicted by spectroscopic measurement. A known disadvantage of BMI is that high muscle mass leads to a high BMI. Therefore, BMI is not an ideal indicator for detecting an excessively high energy diet. Measuring the proportion of fatty tissue in the subcutaneous tissue and in muscle tissue using a non-invasive optical method eliminates this disadvantage in an advantageous embodiment. An advantageous measuring device according to the invention can therefore be used very advantageously for observing the effects of energy intake and energy consumption of the body.

[0248] Surprisingly, in another preferred variant, it was found that with the help of AI it is possible to generate algorithms with which the visceral fat (in cm 2 ) and skeletal muscle mass (in kg / m 2) can be determined separately from each other if optical measurement data are collected using the measuring device claimed here, for example on the ball of the hand.

[0249] Measurement of glucose

[0250] In a preferred variant of the measuring device described above, it was surprisingly found that the glucose concentration in the blood can be measured non-invasively when the measuring device comes into contact with the skin.

[0251] In a further preferred variant, it was surprisingly found that the glucose concentration can also be measured in the tissue, e.g. in the intercellular fluid of the subcutaneous fat tissue.

[0252] Surprisingly, the determination of glucose concentration in the blood and tissue can be carried out by measuring the ball of the hand. Surprisingly, it was found that, in an advantageous embodiment, the development of inflammations, e.g. skin inflammations, can be predicted with the help of glucose measurement. In a preferred solution, the ups and downs of glucose values ​​are determined over a certain period of time by measurements before and after meals in order to record the minimum and maximum of the individual glucose level, including the time period between the occurrence of the minimum and maximum glucose values ​​and / or the course between the minimum and maximum glucose values. Using this data and the corresponding data from other users, the user is assigned to a risk class for the development of inflammations, e.g. skin inflammations, using the Classification method. Additional criteria such asAge and gender are taken into account.

[0253] In order to improve the accuracy of the measurement, in a preferred variant, several consecutive repeated measurements are carried out before and immediately after meals. In a preferred variant, at least 2, 3, 4 or 8 repeated measurements are carried out. In a further preferred variant, at least 2 measurements, at least 4 measurements, at least 8 measurements, or at least 12 measurements are carried out directly after meals at specific intervals. In an equally preferred variant, the interval between the measurements is a maximum of 1 minute, a maximum of 2 minutes, a maximum of 4 minutes, a maximum of 6 minutes, a maximum of 8 minutes, or a maximum of 10 minutes. In a preferred embodiment, the period over which the rise and fall in the values ​​before and after meals are monitored by measurements is, for example, at least one day. In a further preferred embodiment, this period is, for example, at least 2 days.In a more preferred embodiment, the period is, for example, at least 3 days. In an even more preferred embodiment, the period is, for example, at least 1 week, and in the most preferred embodiment, the period is, for example, at least 2 weeks, in order to determine the average ups and downs in the glucose levels of the person being measured. In an advantageous variant, measures to reduce the maximum fluctuations in the ups and downs in glucose levels are determined for each risk class to which a user can be assigned. Taking into account the method described above for determining individual metabolism, the measures in an advantageous variant include, for example, suggestions regarding the foods to be consumed or the components of the food intake. These can, for example,Based on their glycemic index and / or the time and / or frequency of food intake on a given day, these are calculated and displayed using an algorithm. In a preferred variant, suggestions for the number and timing of meals are determined from the time and result of the glucose measurement. The implementation of these suggestions by the person measuring is checked, for example, based on subsequent glucose measurements. The differences in glucose levels detected can, for example, lead to reassignment to a lower risk category. In this way, the risk of developing inflammation can be gradually reduced.

[0254] Measurement of glucose, C-reactive protein, cortisol, alpha linolenic acid and prognosis for the development of inflammation

[0255] In a preferred embodiment of the measuring device described above, it was found that one or more of the substance concentrations of C-reactive protein, cortisol and alpha linolenic acid can be measured non-invasively with the measuring device if the sensor has direct skin contact at least temporarily during the measurement.

[0256] In another preferred variant, measurements of glucose, C-reactive protein, cortisol and alpha linolenic acid take place in the area of ​​the palm of the hand.

[0257] In a further preferred embodiment, it was surprisingly found that, for example, when glucose and C-reactive protein are measured simultaneously, according to the method described in the chapter "Measurement of Glucose", the assignment to a risk class for the occurrence of future inflammations, e.g. skin inflammations, can be carried out more precisely. In a further preferred embodiment, it was surprisingly found that, for example, when glucose, C-reactive protein and cortisol are measured simultaneously, according to the method described in the chapter "Measurement of Glucose", not only is the assignment to a risk class for the occurrence of future inflammations, e.g. skin inflammations, possible, but an approximate prognosis of the time or period for the occurrence and severity of the inflammation is also possible.In a further preferred embodiment, it was surprisingly found that, for example, when glucose, C-reactive protein, and alpha linolenic acid are measured simultaneously, according to the method described in the chapter "Measurement of glucose", the assignment to a risk class for the occurrence of future inflammations, e.g. skin inflammations, as well as the prognosis of the time or period for the occurrence and severity of the inflammation, can be carried out more precisely.

[0258] In the previously described preferred variants for improving risk classification and predicting the time / period for onset and severity of inflammation, the respective measurements for the individual substances are either performed in quick succession or the corresponding optical data are collected together as part of a single measurement. In an alternative preferred embodiment, the measurement methods described in this chapter are performed non-invasively optically for only some of the substances. Other measurements are performed by other methods.

[0259] In another preferred variant, the measurements of the various substances can also be collected using different measurement methods in close succession, e.g., within a maximum of one month, within a maximum of one week, preferably within a maximum of one day, or even better, within an hour. As previously described, in this case, too, the individual measurement results and the corresponding data from other users form the basis for applying artificial intelligence methods to predict the development and severity of inflammation for a future point in time.

[0260] Measurement of AGE and glucose

[0261] In a preferred embodiment of the measuring device described above, it was found that the concentration of advanced glycation end-products (AGEs) can be measured non-invasively when the measuring device comes into contact with the skin. In an advantageous embodiment, the device is designed so that not only photons emitted by the emitters can be detected by the detectors, but also photons that arise from fluorescence properties in the sample to be measured after the sample has been excited to fluorescence by light. Surprisingly, in a preferred variant it was found that if AGEs and glucose are measured simultaneously, for example, the future concentration of AGEs can be predicted. In a preferred variant, measurements are taken for this purpose, for example, at intervals of a maximum of one week, at intervals of a maximum of two weeks, at intervals of a maximum of three weeks, at intervals of a maximum of four weeks, at intervals of a maximum of six weeks, at intervals of a maximum of nine ...4 weeks, at intervals of max. 2 months or at intervals of more than 2 months. In preferred variants, for example, at least 2 such measurements, at least 4 such measurements, at least 8 such measurements or more than 10 such measurements are carried out at the aforementioned intervals. In a preferred variant, these measurements can, for example, be carried out directly one after the other. In further preferred variants, these measurements can, for example, be carried out at intervals of max. 10 minutes, at intervals of 10 to 30 minutes, at intervals of 30 to 60 minutes, at intervals of 60 to 90 minutes or at intervals of 90 to 120 minutes. In further preferred variants, the measurements can, for example, be carried out before each meal and after each meal, directly after getting up and shortly before going to bed.In a preferred variant, for example, the concentrations of AGEs and glucose generated during the measurements are offset against each other in order to determine the influence of the current glucose concentration on the change in the AGE concentration.

[0262] In a preferred variant, to optimize the calculation method, part of the data set is used to predict the other part of the data set. The calculation method can be modified by comparing the prediction with the actual measured results until a satisfactory prediction of the measured values ​​is achieved. In an advantageous variant, this is done automatically using algorithms. In a particularly advantageous variant, this is done using AI methods such as neural networks.

[0263] In a preferred variant, a prediction quality is determined for the results. This is communicated to the user. The prediction quality indicates, for example, the probability that a predicted value corresponds to a value at a certain point in the future. This can be, for example, AGE values. In an advantageous variant, the result of each new measurement is compared with the result of the predicted value. In a preferred variant, the prediction of a value is optimized by taking into account another measured value. For example, the prediction of an AGE value is optimized by taking into account a temporally related glucose measurement. In a preferred variant, the temporal development of the measured values ​​and the predicted values ​​is displayed in a joint graph. This can be done, for example, for AGE values.As previously described, in a preferred variant, the user is provided with suggestions on how to influence the current glucose level by changing diet and lifestyle (e.g. nutritional components, time of food intake, physical activity), taking into account the individual metabolism, so that the measured AGE values ​​do not exceed health-relevant thresholds.

[0264] Weight management - measurement of glucose, body fat percentage and water content of skin and tissue

[0265] For successful nutrition and weight management, it is useful, among other things, to monitor the glucose concentration in the blood or in the intercellular fluid of the tissue. Body fat is not broken down, or is only partially broken down, if there is sufficient energy in the form of glucose in the blood. Since glucose and insulin rise to a similar extent after a meal and insulin blocks lipolysis, fat is neither burned nor metabolized. As a result, the fat ingested with the meal is at least partially stored in the fat cells. This leads to weight gain and simultaneous expansion of the existing fat cells. If there is little glucose in the blood because insulin previously transported the glucose to the body's cells for energy or because the calorie intake has been stopped, the body first breaks down its glycogen reserves. Glycogen is a form of carbohydrate that is stored in the muscles and liver (approx. 300-400g).When glycogen is used for energy, water is released and flushed out of the body. While this leads to measurable weight loss on the scales, it has nothing to do with successful weight management and the shedding of excess pounds. Despite exercise, depleting glycogen stores results in a reduction in the breakdown of the body's existing fat reserves. Weight loss through fat burning is correspondingly reduced.

[0266] In a preferred embodiment, it was surprisingly discovered that, for example, by simultaneously measuring blood sugar, water, and fat levels (see previous chapter), an individual range can be determined within which a loss of body weight occurs (net weight loss) without the weight reduction subsequently determined on the scale being distorted by water loss. This is of great importance for the user, as they have not yet been able to distinguish between water loss and actual weight loss.

[0267] Furthermore, the weight of the stomach and intestinal contents varies, making body weight determination an inaccurate starting point for a diet aimed at reducing body fat. In an advantageous variant, a non-invasive optical measurement with one of the embodiments according to the invention is used to monitor the progress of a diet.

[0268] At the same time, in a preferred embodiment, a time range can be determined for the time at which it is expedient and effective to initiate fat burning through physical activity, such as exercise. This means that the user is informed when to start a physical activity so that the exercise results in the greatest reduction in body fat.

[0269] In a preferred embodiment, the previously described individual corridor for fat burning is determined, for example, by targeted mathematical calculation using blood glucose levels, which are measured, for example, according to the procedure described in the “Glucose Measurement” chapter. In a preferred variant, the calculation takes into account the water content and / or body fat percentage, which are determined, for example, together with the glucose measurement in joint measurements. Within the corridor, areas in which, for example, net weight loss is particularly advantageous can be identified with the help of further mathematical methods, e.g. based on AI. In a preferred embodiment, the individual areas can be identified, for example, using special key figures that describe the relationship between the individual measured values.

[0270] Surprisingly, it has been found in a preferred embodiment that, by measuring the three substances mentioned above (blood sugar, water content, body fat percentage) using an algorithm, it is possible to predict the actual weight loss that will occur later. In a preferred embodiment, the forecast is particularly accurate if, in addition to the three substances mentioned above, the duration of stay in the corridor is determined, for example, because the longer the body stays in this individual corridor, the greater the net weight loss. In an advantageous variant, the determination of future net weight loss becomes even more precise if, for example, the time spent in the areas for different weight loss is determined and included in the calculation.

[0271] Since body fat percentage changes more slowly than blood sugar and water content, it was surprisingly discovered in a preferred embodiment that the ratio of fat to blood sugar and water content can be used to retrospectively calculate, for example, the period during which the body was within the individual weight loss range. For this purpose, the measured values ​​stored in the measuring device or on an external medium (e.g., a server that receives the data, for example, via an app over the internet) are analyzed. The retrospective calculation of the period is preferably carried out, for example, by including one or more measurements that were previously taken within the range.The possibility of retrospective calculation is an advantageous variant and represents a significant benefit for the customer, as it does not require continuous determination and / or continuous analysis of the three substances and the time spent in the corridor in order to predict the future net weight reduction.

[0272] In a preferred variant, repeated measurements are carried out at intervals of no more than 3 hours. In further preferred variants, they are carried out at intervals of no more than 2 hours, no more than 1 hour, no more than 30 minutes, no more than 20 minutes, no more than 10 minutes, or every minute. If this measurement interval is repeated on several days or over a longer period of time, the net weight loss can, for example, be extrapolated for different periods of time. In a preferred variant, the net weight loss resulting from the user maintaining their current behavior can, for example, be extrapolated for a period of up to 1, 2, 3, or 4 weeks.In further preferred variants for a period of up to 2, 3, 4, 5, 6 months, in further preferred variants for a period of 7, 8, 9, 10, 11 months and in equally preferred variants for a period of up to 1, 2, 3 or more years or analogously for other points in time and time periods. Compared to the state of the art, this offers a significant increase in customer benefit because the physiological states make weight loss quantifiable before it becomes visible on the scales. This is an objective weight loss that does not depend, for example, on the measuring accuracy of the scales or the resolution of the measurement result on the scales. This is a significant advantage because the customer then no longer needs expensive bathroom scales that can display weight differences in the gram range with a very small measuring error in order to notice motivational weight loss at an early stage.

[0273] In a similarly preferred embodiment, it was found that it is also possible to determine the range by measuring blood sugar, water content, and body fat percentage at different times. However, it has been found that this method can only determine the range with less accuracy. The advantage of this embodiment is that the measuring device can be designed more cost-effectively.

[0274] Sharply falling glucose levels

[0275] It is well known that blood sugar levels rise and then fall in the first two hours after a meal. As scientific studies show (e.g., "Postprandial glycemic dips predict appetite and energy intake in healthy individuals," in: Nat Metab. 2021 April 01; 3(4): 523-529. doi: 10.1038 / s42255-021-00383-x), some people experience a sharp drop in blood sugar levels 2-4 hours after a peak, before rising again. Affected individuals feel more hungry and consume an average of 300 calories more throughout the day than individuals whose blood sugar levels do not experience such a sharp drop. This behavior can lead to a weight gain of 10 kg within a year.For sustainable weight management, it is therefore beneficial, for example, to inform individuals whether they belong to the group with sharply declining blood sugar levels and therefore consume more calories than others. To identify this group of individuals, an advantageous variant of the invention is used, which includes a measurement procedure and / or visualization of blood sugar levels optimized for this purpose. A preferred procedure for identifying individuals with sharply declining blood sugar levels is, for example, the following:

[0276] Before performing a glucose measurement, users can enter the time period that has passed since the meal on the user interface of the measuring app. Alternatively, the time at which the last or subsequent meals were consumed is entered or recorded in another way. In a preferred embodiment, this can be done, for example, via a selection menu or by manually or verbally entering the time period. Or by pressing a button in the app shortly before or after the meal. In addition, in another preferred embodiment, there is the option of documenting the components of the previous meal, for example by entering, selecting or taking digital photographs. In a preferred embodiment, the measuring app controls the performance of the measurement using the measuring device described above. It can, for example, be located on a mobile device (e.g.Smartphone, tablet) which, with the help of the app, retrieves the data from the measuring device and forwards it to a central server for calculation and / or data storage. The data can be transferred via the internet, to which the mobile device can connect automatically, for example by dialing into an existing WiFi network or by sending data mobile, for example via cellular data. The measurement data stored on the server for a preferred number of users is analyzed for blood sugar levels that fall over time. With the help of AI, for example, risk levels are defined for belonging to the group of users with sharply falling blood sugar levels. Each user is assigned one of the levels. Since assignment to a level also depends on the number of blood sugar measurements stored for the user, the assignment can change over time. At the same time, the probability of a correct assignment increases with more measurements.In the preferred variant, the user is informed of the probability of a correct assignment. In the alternative variant, the assignment is not based on risk levels, but rather on a continuous basis.

[0277] If the user has stored information about the components of their meal or digital photos of their meals in the app, the preferred configuration for assigning them to a risk level will also include the components of a meal or the photographed meals that made the greatest contribution to the predicted drop in sugar levels.

[0278] Measurement of alpha linolenic acid, arachidonic acid, linoleic acid

[0279] In a preferred embodiment, the measuring device described here can measure the concentration of one or more of the following substances: alpha-linolenic acid (omega 3), arachidonic acid (omega 6), and / or linoleic acid (omega 6). In a further preferred embodiment, the acids are detected simultaneously within a single measurement, which can consist of multiple measurement sequences.

[0280] In an additional preferred embodiment, the respective acid concentration is measured at different depths of the skin, extending into the blood. In a preferred embodiment, the determination of the different depth concentrations for the individual acids is carried out simultaneously during a measurement, which can have multiple measurement sequences. This is based on the targeted analysis of data originating from emitter-detector pairs with light paths corresponding to the respective depth.

[0281] Measurement of carotenoids

[0282] With the aid of the measuring device described here, it is advantageously possible to measure the concentration of carotenoids in the human body. This has already been described for the MSRRS method in patent US 11,085,876 B2. If the MSRRS method is used in conjunction with the properties of the measuring device according to the invention described here, the concentration of the various carotenoids can be determined more accurately than with the MSRRS method alone. In a preferred embodiment, the measuring device can detect the concentration of alpha-carotene, beta-carotene, lutein, alpha-carotene, gamma-carotene, beta-cryptoxanthin, zeaxanthin, and lycopene. In a further preferred variant, the aforementioned carotenoids in the blood and in the skin (tissue) can be measured individually and / or jointly using appropriate algorithms, and the results can be displayed individually and / or jointly on the display of an output device.

[0283] In a likewise preferred embodiment, when measuring the carotenoids in the blood, the contribution of food intake to increasing the carotenoid level and thus to increasing the antioxidant level in the body can be determined on the same day, e.g. after a few hours, whereas the accumulation of carotenoids in the skin or tissue cannot be measured on the same day, often only after several weeks.

[0284] In a preferred embodiment, for measurements used to determine carotenoid concentrations, which are performed, for example, on the palm of a human hand, the measurement inaccuracy in the concentration determination is reduced by calculating the carotenoid concentrations taking into account the measurement results of C-reactive protein and / or cortisol, which are or were performed simultaneously and / or at different times. In a preferred embodiment, a better repeatability of the carotenoid measurement is achieved by calculating the concentration of the carotenoid measurement taking into account the measurement results of C-reactive protein and / or cortisol.

[0285] In a preferred embodiment, in dietary and behavioral changes intended to improve carotenoid levels, the increase in carotenoid concentration can be detected earlier if, for example, C-reactive protein and / or cortisol are measured simultaneously and taken into account in the carotenoid concentration calculation. Surprisingly, in a preferred variant, it was also found that the deviation between predicted carotenoid concentration and later actually measured carotenoid concentrations is smaller if, for example, the measurement results from the simultaneous measurement of C-reactive protein and / or cortisol are taken into account in the trend determination.With regard to the number of measurements required for trend calculation, the time intervals between the individual measurement times and the time differences between the measurements, the described conditions for calculating the future concentration of fatty acids apply analogously in a preferred embodiment.

[0286] In a preferred variant, the substances mentioned above can also be measured using the transmitted light method during spectroscopic measurement. Unlike with reflection spectroscopy, in this method the emitters and detectors are not on the same plane, so that measurement is only possible at specific parts of the body (e.g. fingertip, earlobe). In an advantageous variant, the user can use the blood measurement to determine the optimal food for them, taking into account their individual metabolism. In a preferred variant, liquids and food supplements containing, for example, carotenoids or antioxidants are also considered food intake in this context. If the user determines, for example, that certain foods have no or only minimal influence on the carotenoid concentration in the blood, they can immediately swap them for others and thus quickly optimize their diet.A beneficial variant of digital and automated nutritional and behavioral counseling is based on algorithms. In a beneficial variant, the algorithms use the results of determining the concentration of one or more biomarkers, e.g., carotenoids. In a beneficial variant, the algorithms calculate individualized nutritional suggestions. These preferably lead to an increase in the user's concentration of at least one biomarker. Nutritional suggestions can preferably include recipes, the method of preparing food, the time of food consumption, and the menu options available in restaurants. The resulting suggestions are preferably supplemented with suggestions for changes to the user's lifestyle.

[0287] In a preferred embodiment, in order to determine the individual metabolism of one or more biomarkers, measurements are carried out on the user's body to determine the influence of at least one first meal and / or food intake and / or behavior on the level of the concentration of the biomarker.

[0288] In a preferred embodiment, to determine the individual metabolism of one or more biomarkers, measurements are carried out on the user's body to determine the influence of at least a second meal and / or food intake and / or behavior on the level of the biomarker concentration. The biomarker can preferably be a single biomarker or multiple biomarkers, for example one or more carotenoids. In an advantageous method, mathematical methods are used to determine whether one of the two meals / behaviors increases the concentration of the biomarker more than the other. In a further preferred variant, the first meal / behavior represents the reference standard with which the second meal / behavior is compared. In a preferred variant, the reference standard can be determined at any time.In a preferred variant, the reference standard can also be determined after the second meal / behavior. In a preferred variant, non-invasive measurements are performed to determine the concentration of the biomarker. Preferably, when using a spectroscopic system, e.g., the measuring instrument described here, only raw data from specific light paths can be evaluated for the concentration determination, whereby, for example, individual light paths can be included in the evaluation in a weighted manner. In a preferred variant, mathematical algorithms are used to evaluate the measurement data collected by measurement and to determine the concentration of the biomarker(s).

[0289] In a preferred embodiment, the algorithms can be developed with the help of artificial intelligence. In a preferred variant, the first meal / behavior can be a meal / behavior that the user themselves selects because, for example, they particularly enjoy the meal and / or eat it more often than other meals and / or because it is a behavior that is typical or frequently performed for them. In a preferred variant, the second meal / behavior can, for example, be suggestions from the automated nutritional and behavioral advice. In a preferred embodiment, these can be meals / behaviors that the user determines and performs independently of the suggestions. In a preferred embodiment, measurements are taken on the user's body before and after the first meal / behavior.In a preferred embodiment, measurements are carried out on the user's body before and after the second meal / behavior. In a preferred variant, the measurements can be in one or more measuring sections, with each measuring section comprising one or more individual measurements. The accuracy of the concentration determination can preferably be increased by the number of measuring sections and individual measurements. In a preferred variant, at least 1 measurement is carried out shortly before the first and shortly before the second meal / behavior. In equally preferred variants, at least 2, at least 4, at least 6 measurements or more than 6 measurements are carried out to determine the concentration of one or more biomarkers. In preferred variants, a maximum of 15 minutes or a maximum of 30 minutes or a maximum ofMeasurements to determine the concentration of one or more biomarkers are taken 1, 2, 3, 4, 5, or more than 5 hours after the first meal / behavior. In preferred variants, measurements to determine the concentration of one or more biomarkers are taken a maximum of 15 minutes or a maximum of 30 minutes or a maximum of 1, 2, 3, 4, 5, or more than 5 hours after the second meal / behavior. In a preferred variant, the number of measurements taken at one of the aforementioned measurement times can correspond to the number of measurements taken before the meal / behavior.

[0290] In a preferred embodiment, the user can be instructed not to consume any other food or drink liquids containing biomarkers whose concentrations are to be determined during the measurement period, apart from the first and / or second meal. Preferably, for the first meal / behavior, the substance concentrations determined by individual measurements, separately for measurements before and after the meal, are calculated using mathematical methods.

[0291] Preferably, for the second meal / behavior, the substance concentration levels determined by individual measurements, separately for measurements before and after the meal, are calculated using mathematical methods. The mathematical calculation can preferably be carried out by calculating, for example, an arithmetic mean or a linear or non-linear regression.

[0292] Preferably, for the first meal / behavior, the calculation results before the meal / behavior are compared with the calculation results after the meal / behavior and mathematically evaluated. In a preferred embodiment, the evaluation determines whether the substance concentration of one or more biomarkers is higher after the first meal / behavior than before the first meal / behavior. This result is preferably called the evaluation result. Preferably, for the second meal / behavior, the calculation results before the meal / behavior are compared with the calculation results after the meal / behavior and mathematically evaluated to determine whether the determined substance concentrations differ in their level.In a preferred embodiment, the assessment determines whether the substance concentration of one or more biomarkers is higher after the second meal / behavior than before the second meal / behavior. This result is preferably referred to as the assessment result. In a preferred variant, the assessment results of the first and second meal / behavior are compared and it is mathematically determined whether the first meal / behavior or the second meal / behavior increased the substance concentration of one or more biomarkers more. In a preferred embodiment, when determining whether the first meal / behavior or the second meal / behavior increased the substance concentration more, the level of the substance concentration before the two meals is also taken into account.In a preferred embodiment, this consideration can compensate for the influence that the level of a substance concentration has on the increase in the substance concentration due to a meal / behavior.

[0293] In a preferred embodiment, the system includes a component that models the influence of the user's behavior on a user's biomarker. In a preferred configuration, the modeling is carried out using a mathematical model. This preferably consists of several mathematical formulas. The model is preferably implemented in software. In an advantageous variant, the model is implemented and / or created using software methods of artificial intelligence. In a preferred embodiment, the system includes a component that models the influence of the intake of certain food on a user's biomarker. In a preferred embodiment, parameters of this model are optimized over time to bring the model into better agreement with reality. This preferably improves the usability of the model for prediction and / or planning purposes.In a preferred embodiment, the model is used to predict the development of biomarkers depending on the user's behavior and / or dietary intake of specific foods. In a preferred embodiment, the model is used to determine which action and / or nutritional suggestions have a desirable effect on the user's biomarkers and / or key figures and / or goals. In a preferred embodiment, the model is used to create a plan of actions and / or dietary intake. In a preferred variant, the plan is created automatically. In an alternative variant, the plan is created by the user and the model shows the user the effects. In an alternative variant, the plan is created interactively. Preferably, the plan is then created partly with automatically generated suggestions and partly through manual input and / or manual requests for alternative automatic suggestions.

[0294] In a preferred embodiment, the model uses data from other users. In a preferred embodiment, the model is initialized with data from other users. The model can preferably thus already be used for planning or forecasting purposes before measurement data from the user is available. The model preferably takes ingredients for recipes into account. Preferably, a model is created for individual ingredients for their effects on biomarkers and / or substance concentrations that can be measured in the user. Preferably, the model also takes into account the preparation of the ingredients and / or their interaction. Preferably, the ingredients of ingested food are stored. Preferably, the time of ingestion is stored. Preferably, the temporal development of at least one parameter is stored. This parameter is preferably a value that can be determined by measurement.Preferably, the model for predicting the parameter is refined from the temporal course of food intake of certain food and the temporal course of the parameter.

[0295] Preferably, models are created that apply to a specific user. Preferably, models are created that apply to specific user groups. Preferably, user groups are formed so that the users of a group can be well represented by a specific model. Preferably, the comparison of user-specific models allows the transfer of information from one user to another. Preferably, recipes that were beneficial for one user can be suggested to another user with a similar model. Preferably, the model allows for prognosis and / or planning that enables the optimization of multiple biomarkers and / or measured values ​​and / or key figures.

[0296] Preferably, the model allows the development of measured values ​​such as carotenoid concentration to be predicted and displayed from the input of recipes planned for consumption in the future and using known information such as current measured values ​​and recently consumed food. The model is preferably user-specific. For example, the model of a user who can absorb carotenoids in these recipes particularly well provides a higher carotenoid concentration forecast than an average user receives. In an advantageous variant, the model also has cross-user components. These components are learned for all users or for specific user groups. Due to the larger number of users, these models can, in an advantageous design, learn faster and have information on a larger number of ingredients and / or recipes.

[0297] In an advantageous variant, cross-user models are combined with user-specific models in order to combine the advantages of individual modeling with those of cross-user modeling. In an advantageous embodiment, this is achieved by learning the deviations from a cross-user model for an individual user. In an advantageous variant, AI algorithms or neural networks are used. In an advantageous embodiment, model parameters are stored for an individual user. In an advantageous embodiment, there are model parameters that characterize how large a user's storage is for certain substances. In an advantageous embodiment, there is a model parameter that records how full the storage is for a storage location. The fill level is preferably substance-specific. Preferably, several storage locations are modeled for substances.Preferably, one storage location is the digestive system, in particular the stomach and intestines. Preferably, another storage location is the blood. Preferably, another storage location is fatty tissue. Preferably, another storage location is the liver. Preferably, not only the storage of fat in fatty tissue is considered. Preferably, the storage of carotenoids in fatty tissue is also considered. Preferably, another storage location is muscle tissue. Preferably, another storage location is tissue fluid. Preferably, one storage location is the skin. In an advantageous embodiment, there are model parameters that characterize how great the maximum absorption rate of a user is for certain substances. In an advantageous embodiment, there are model parameters that characterize how great a user consumes certain substances. Preferably, the consumption is recorded and / or stored depending on the situation.In an advantageous embodiment, there are model parameters that characterize how certain substances interact with a user. Preferably, the degree to which certain substances impede absorption. In an advantageous embodiment, there are model parameters that characterize the influence of a user's food preparation. Preferably, it is determined whether a user exhibits certain deviations from average users when cooking home-cooked meals. Preferably, it is determined whether the user uses more or less oil in the preparation process. Preferably, it is determined whether the user uses longer or shorter cooking times in the preparation process.

[0298] Preferably, the user is given feedback based on the determined model parameters. Preferably, they receive information about the model created for them. Preferably, explanations for key performance indicator developments can be derived from the model. Preferably, recommendations for action are created for the user. Example: Use less oil when cooking to save calories. Preferably, these recommendations are no longer general, as is often the case with the state of the art, but individual and data-based. Preferably, the impact of a behavior change is quantifiable by the model. In a preferred variant, the results obtained based on the first meal / behavior (reference standard) serve as the reference value for assessing all future meals. Example of comparing a meal / behavior with the reference standard

[0299] In a preferred variant, the user tells the app that they would like to check how their next food intake / behavior affects the concentration of one or more biomarkers, e.g. the concentration of carotenoids, in the body, e.g. in the blood. In a preferred variant, this can be done by pressing a button, for example. In another preferred embodiment, the user can also state the exact or approximate time at which the meal should be eaten and / or the behavior should be carried out. In a preferred embodiment, this can be done by an app displaying a timer that the user can use to set the time until the meal / behavior. In another preferred embodiment, the user can also communicate the time verbally by using the microphone of the device on which the app is installed.Depending on how much time is left until the meal / behavior, the app preferably prompts the user to take a certain number of measurements before the meal / behavior in order to determine the current level before the meal / behavior. In a preferred embodiment, the moment the user starts eating, they inform the app that the food intake of the meal has now started. In a preferred embodiment, this information can be used to more precisely determine the time at which the carotenoids appear or arrive in the blood. In a preferred embodiment, the user provides the app with additional information. In a preferred embodiment, this can be one or more pieces of information relating to the food intake of the meal. In another preferred embodiment, the user can enter the information, for example, in writing using the keyboard or verbally using the microphone of the device on which the app is stored.Preferably, the information can be one or more of the following: information about the essential ingredients of the dish, information about the respective quantities of the ingredients, information about whether the food is eaten uncooked, cooked or boiled, information about whether the food is consumed with oil. In a further preferred embodiment, the information about the meal and its components can be provided with the help of photos and / or videos. Preferably, the user uses, for example, the camera of the device on which the app is installed (e.g. a tablet or a smartphone) to take the photos and / or videos. Preferably, the user uses a separate camera which forwards the recordings to the device with the app. Preferably, these photos and / or videos can be evaluated, for example, with the help of image recognition algorithms, and the components of the food and their respective quantities can be determined.In a preferred variant, the photos and / or videos are saved automatically, for example. Preferably, storage takes place on the display device and / or an external server.

[0300] In a further preferred variant, the user has the option of rating the meal after eating according to various predefined and / or their own criteria. In a preferred variant, the rating can be in the form of symbols, e.g. stars and / or in writing and / or by recording verbal statements. Preferably, the data is saved on the device on which the app is saved. In a preferred variant, the data is saved on a separate server. In a preferred variant, this is done with the help of the app. In a preferred variant, measurements are taken on the user's body after the meal. Preferably, the user carries out the measurements themselves. In a further preferred variant, the measurements are taken by a third person. Preferably, the time for carrying out the corresponding measurements is controlled by the app.Preferably, the app gives the user an acoustic, visual or tactile indication, for example, when a measurement should be taken. In a preferred variant, the time for carrying out the individual measurement or measurements is determined with the help of an algorithm. Depending on the nutritional composition of the meal, the algorithm preferably calculates the time period in which metabolism takes place. Preferably, the algorithm calculates when the substance concentration of one or more biomarkers contained in the food reaches the body, for example in the blood, and / or is measurable. In order to expand the database for calculating the time at which the substance concentration arrives in the body, for example in the blood, the algorithm preferably uses not only the user's measurement data, but also corresponding measurement data from other users.In a preferred variant, the algorithm can also use measurement data and / or information that was not collected with the measurement system and comes, for example, from publications.

[0301] Preferably, the user's data and / or measurement data and the data and / or measurement data not originating from the user are treated differently by the algorithm. Preferably, the user's data and / or measurement data can, for example, be weighted and included in the user-specific calculation for the metabolic process and / or the arrival of the substance concentration of one or more biomarkers in the body. In a preferred embodiment, with an increasing amount of user-specific data and / or measurement data, the algorithm can give the user an increasingly precise specification as to when the user should take measurements after a meal. Preferably, the algorithm makes it possible to use the data made available to it to determine when a substance concentration, e.g. that of carotenoids, will rise in the user's body, e.g. in the blood.Preferably, the algorithm makes it possible to calculate from the data provided to it when a substance concentration, e.g. that of carotenoids, in the user's body, e.g. in the blood, reaches its maximum concentration. Preferably, the algorithm makes it possible to calculate from the data provided to it how long a substance concentration, e.g. that of carotenoids, in the user's body, e.g. in the blood, remains at its peak. Preferably, the algorithm makes it possible to calculate from the data provided to it when and / or how strongly a substance concentration, e.g. that of carotenoids, in the user's body, e.g. in the blood, begins to decrease after the peak. Preferably, the algorithm makes it possible to calculate from the data provided to it when a substance concentration, e.g. that of carotenoids, in the user's body, e.g.in the blood, after reaching its peak and beginning to decline, it reaches a level at which it remains. Preferably, the algorithm uses the data provided to calculate the time span that elapses without additional food intake of one or more biomarkers, from the arrival of the substance concentration, through the rise and fall of the substance concentration. In a preferred variant, the number of measurements the user performs after food intake can be gradually reduced based on the aforementioned calculations.

[0302] In a preferred embodiment, the display of information, for example the presentation of measurement results, the presentation of calculation results, the presentation of photos or videos or other previously described information, can take place on the screen of the device on which the app is installed. In a preferred embodiment, the presentation can also take place on other devices. In a preferred embodiment, the user can determine where and / or in what form the results should be presented. In a preferred variant, the user can, for example, choose between graphical and / or tabular representation, whether the respective meals should have images and / or text descriptions, whether the difference between the reference standard and meal 2 should be presented as a qualitative or quantitative result. In a preferred variant, in a simplified representation, for exampleArrows indicate how meal 2 compares to the reference standard. In a preferred variant, for example, an upward-pointing arrow can mean that meal 2 improves the substance concentration in the body, e.g., in the user's blood, more than the reference standard.

[0303] Preferably, the angle of an upward-pointing arrow can indicate the strength of the higher substance concentration compared to the reference standard. In a preferred variant, a downward-pointing arrow can indicate the opposite. In a preferred variant, a horizontal arrow can indicate that no clear difference could be determined between the reference standard and meal 2. Preferably, the result can also be indicated analogously, e.g., using the symbols "+", "+", where multiple plus or minus signs can indicate the degree of difference and the sign is used if no clear difference could be determined. In a further preferred variant, the change in the substance concentration of the comparison standard before and after the meal / behavior and / or the analogous change in meal 2 can be output as an absolute value or as a percentage difference. In a preferred variant, the output can be the percentage by which the change in the comparison standard differs from the change in meal 2. In a preferred variant, the user can be presented with a time-differentiated display of this data based on stored data. In a preferred variant, the information always contains the date of storage. In a preferred embodiment, further information can be made available to the user.In a preferred variant, for example, the following information can be provided: which meal / food did the user eat and when, which meals were suggested by the automated nutrition and behavioral advice, how much did the user enjoy these meals, which meals does the user recommend eating again, what costs are associated with the meals / behaviors, which health-relevant components do meals contain, how much did meals / behaviors increase the substance concentration of biomarkers, e.g. carotenoids, in the body, e.g. in the user's blood, which of the stored data did the user share with third parties, e.g. via social networks.

[0304] Initialization - Creating a user profile in the app

[0305] As previously described in various places, the measuring device disclosed here and the methods for carrying out the measurement enable the determination of the physiological states of an individual or the measurement of the concentration of substances in the human body. In order to fully fulfill the task of the measuring device to promote the health and well-being of the user, in an advantageous variant the user is presented with additional behavioral suggestions, recommendations, help or support in writing, acoustically or as a video on the basis of the measurement results, which help him, for example, to improve his measurement results and his well-being. In a further advantageous variant, the user can be presented with general behavioral suggestions, recommendations, help or support even without prior measurement. In an advantageous variant, this can be done by the user, for examplethe app that communicates with the measuring device, describes a problem verbally, e.g. colloquially, e.g. in full sentences, after activating a corresponding button in the app. With the help of speech recognition and AI, the behavioral suggestions, recommendations, help, etc. stored in the app's resources are then analyzed and suitable suggestions, recommendations, help, etc. are presented to the user. In an advantageous embodiment, the user can be advised, during the presentation of the general behavioral suggestions, recommendations, etc., to carry out corresponding measurements with the disclosed measuring device in order to validate and adapt the suggestions to the individual condition of the user. In a further advantageous variant, the user can also be advised, in addition or exclusively, to carry out validating measurements with other measuring devices and to evaluate the results, e.g.to be saved in the app, which communicates with the measuring device disclosed here. In an advantageous embodiment, the general or user-specific behavioral suggestions, recommendations, etc. can also involve establishing, initiating, and maintaining a connection to experts or institutions that provide advice and / or physical and / or mental help or support, and if necessary also employ additional aids. In a preferred variant, the user can specify which additional information, support, assistance, etc. he wishes to receive and in which context. In a further advantageous variant, the user can communicate certain preferences, likes, requirements, or needs to the technical system, e.g. the app, by inputting them. These preferences, likes, requirements, or needs alone or together with the measurement results contribute to the very precise definition or implementation of behavioral suggestions, recommendations, help, support, or aids.be used to promote and maintain the user’s long-term health and well-being. In one advantageous embodiment, the user can specify their preferences, likes, needs or requirements via input fields which are organized, for example, in a type of tree structure containing higher- and lower-level subject areas or terms. The preferences, likes, needs or requirements can be entered in writing and / or selected by clicking or marking, for example, checkboxes. This may pose a semantic problem for the user which makes it difficult to find the place to enter the information in the tree structure. For example, in nutrition the term “tomato” belongs to the category “vegetables” or “red vegetables”. However, if a user assigns “tomatoes” to the category “fruit”, they will not find this term under “fruit” in the tree structure in order to store their preference for “tomatoes”, for example.To solve this problem, the term or category "tomato" can exist under both "fruit" and "vegetables." This means that a category or term can appear in more than one branch of the tree structure. As soon as the user makes an entry / selection, this entry / selection is automatically adopted into the other branches of the tree structure in which the category or term also appears. The same applies if the user changes or deletes their preference.

[0306] In another advantageous embodiment, the preference, likes, needs, etc. can also be entered verbally. To do this, the user can, for example, press a button in the app and express their preference verbally, e.g. colloquially, e.g. in full sentences. With the help of AI and speech recognition, the app searches for the corresponding category or creates it if a corresponding category is not yet available, enters the written entry in the input window, or activates the corresponding selection field. In another preferred variant, the user is asked to confirm the entry in order to rule out possible errors in speech recognition and assignment. As with manual entry, the confirmed preference is automatically transferred to the other strands of the tree structure in which the same category or term occurs or is intended to occur in the future.In one advantageous solution, the user can, for example, within the app, make basic settings that permanently impose certain requirements on all future recommendations, help, support, etc. that are given to him. In another advantageous variant, he can specify requirements for recommendations, help, support that only apply for a certain period of time, e.g. for the moment, one or more days, weeks or months. In another preferred variant, permanent basic settings and time-limited settings can be based on the principle of exclusion and / or inclusion. The basic settings also include, for example, the user's socio-demographic data such as age, gender, weight, height, etc. If, for example, the user is presented with nutritional suggestions, e.g. in the form of recipes or dishes offered in a restaurant, he can, for example,Exclusions as well as preferences are permanently specified. For example, they can enter their wheat allergy in the “Allergies” category, or they can enter vegan in the “Dietary principles / dietary style” category, or they can enter garlic and onions in the “General aversion to certain ingredients or parts of a dish”. On the other hand, they can also provide information about specific preferences, for example they could enter spaghetti as a filling side dish in the “Preferences” category. All suggestions made to them must then not contain wheat, meat or fish, products made from animals or animal extracts, garlic or onions. Recipes or dishes with spaghetti as a filling side dish are given priority.

[0307] If the user has a particular appetite on a particular day, for example, for a certain ingredient in a recipe or dish, they can formulate exclusions so that the suggestions must contain one and / or more desired foods, for example carrots and / or spinach. In an advantageous variant, this requirement can be limited to a certain period of time. In a preferred variant, a time-limited requirement can also contradict one or more basic settings, which are then overridden for this period. For example, a vegan could exceptionally enter the preference "fish up to 100g" for a certain food. Despite the "vegan" category selected in the basic setting, they would then only be suggested recipes or dishes that all contain up to 100g of fish, but otherwise meet the "vegan" category. In an equally preferred embodiment, exclusions can be quantitatively limited, so that, for example,only recipe suggestions or dishes are excluded that contain more than, for example, 10g of wheat. Similarly, the user can specify in the inclusions that only recipes or dishes are suggested that contain a minimum amount, e.g. 100g of carrots and / or e.g. 50g of spinach. In another preferred variant, the user can, for example, rate the suggestions made to him after he has implemented them or, in the case of recipes, cooked them and eaten the dish. The rating can, for example, be on an ordinal, interval, or ratio scale of satisfaction, ranging from, for example, "completely unacceptable" or "not suggest again" to "highly acceptable". In another preferred variant, the rating is saved and taken into account for future suggestions. In another preferred variant, the user can, for example,set in the app whether suggestions should also be made to them or only suggestions that they have given a certain rating in the past or whose rating lies within a certain range. As was surprisingly discovered, the well-being of users can be sustainably improved with the aforementioned options. The above-mentioned additional information, recommendations, assistance, etc., which can be provided, initiated or maintained without measurement or on the basis of a measurement that was carried out with the measuring device claimed here or other measuring devices and can be provided, initiated or maintained in an advantageous variant, e.g. via a special app, concern or contain, for example, the following aspects. Several or parts of the mentioned aspects can be applied:.

[0308] • Provision of the history of recommendations, help, etc. and / or measurement results of individual or multiple measurement parameters, e.g. in the form of a list of the corresponding recommendations, help, etc. and / or individual measured values ​​with a time stamp or as a graphical representation of the progression over time,

[0309] • Setting and saving user preferences, e.g. in the app that communicates with the measuring device, e.g. regarding nutrition, health, sports and exercise, leisure activities or professional requirements

[0310] • Presentation of health limits for the concentration of individual measurement parameters or the combination of measurement parameters, evaluation of the preferences that the user can set with regard to certain measurement parameters,

[0311] • Determination and presentation of the fulfillment value that results for the preferences when the user implements recommendations, e.g. selects or consumes individual foods or complete meals,

[0312] • Presentation of trend statements for the development of individual measured values ​​or the combination of several measured values, e.g. based on measurement results.

[0313] • Comparison of the measurement results obtained with, for example, mean values ​​or medians of reference groups (divided, for example, by age and / or gender and / or education and / or occupation) at regional level (e.g. hometown or federal state of the user), national level (national state of the user), international level (e.g. continent, worldwide)), summary of all results to weekly, monthly or annual reports,

[0314] • Possibility of forwarding results and / or recommendations, help etc., e.g. automatically or after confirmation by the user, to user groups in social networks, to followers in social networks, to individuals e.g. family doctor, friends, family members, to national or international institutions e.g. hospital, statistical offices, Ministry of Health, WHO,

[0315] • The user can send explanatory voice messages to selected persons or institutions via the measuring device’s app along with the measurement results and / or recommendations, help, etc.

[0316] • Access to certain databases, e.g. using search algorithms provided, to provide the user with information, e.g. on health-related topics, e.g. recipes, scientific publications, reports from those affected, e.g. by digitally entering search questions or verbally expressed queries,

[0317] • The user can receive a reminder email or WhatsApp message at freely definable intervals, for example, if a repeat measurement is advisable based on existing measurement results or other information. • Information about the availability of experts in the user's vicinity, for example, on health and nutrition-related questions or on legal issues that may arise, for example, from diet, purchasing food, or visiting restaurants.

[0318] • Information on one or more institutions from the following list: from the areas of health and nutrition, e.g. health authorities, ministries, consumer advice centers including possible contact persons.

[0319] • Automatic appointment scheduling with doctors, nutritionists, and health experts, for example. This is particularly useful when measurement results exceed certain limits or other information indicates changes that could affect the user's current or future well-being.

[0320] • Automated provision of one or more current information from the following list: on opening hours and unavailability due to vacation or illness of, for example, doctors, health and / or nutrition-related experts or experts for legal questions that may arise, for example, from nutrition or the purchase of food or visits to restaurants.

[0321] • Automated reminder to carry out and adhere to one or more of the following activities: sporting activities, relaxation exercises or rest periods, initiating a measurement, appointments e.g. with a doctor or advice centre.

[0322] • Providing individualized advice to improve measurement results, taking into account one or more of the following parameters: the user's preferences, tastes, eating habits, measurement history, and regional and seasonal availability of food.

[0323] • Provision of information, for example, on the location and opening hours of shopping options for products, such as food, in grocery stores, at weekly markets, and in farm shops in the user's vicinity. Ideally, this takes into account one or more of the following parameters: quality (e.g., organic products), cost, distance, accessibility, and parking options, e.g., for cars or bicycles.

[0324] • Provision of information about catering options from one or more of the following categories: restaurants, fast food restaurants, snack bars, food supply chains and their offerings • Provision of, for example, a database in which restaurants can post their current dishes in written descriptions, e.g. with all ingredients, and as photos, and which the app accesses, for example, when selecting user-related suggestions.

[0325] • Possibility of integrating photos taken by users of their meals at restaurants into the aforementioned database. These photos are analyzed with regard to ingredients, including calculating the respective quantities (e.g., in grams), energy value, vitamins, and other ingredient-specific properties of the dish. The cost of the dish is displayed and the user is rated for the quality of the meal, possibly with comments. Photos can be uploaded to the database, for example, via the app that communicates with the measuring device.

[0326] • Automated ordering of products and / or services that the user requires, such as ingredients for cooking recipes, which the user selects for his meals and which are brought to his home.

[0327] • Automated monitoring of the user's food stocks, e.g. regarding their expiration date or availability, e.g. by quantifying the food consumed so far

[0328] • Providing up-to-date information about products relevant to the user, for example, regarding special offers from stores in the user's vicinity. The products could be food, for example.

[0329] • Possibility of storing external data, e.g. your own health data such as laboratory reports, measurement results from other measurement methods.

[0330] • Provision of information on relaxation and leisure, for example if the measurement result indicates physical or mental exhaustion or high psychological and / or physical stress. This can include, for example, the presentation of current holiday offers, e.g. last-minute offers for package holidays, unoccupied holiday apartments, free rooms in hotels, private rooms, campsites including all travel options, e.g. by plane, car, train, bicycle, hiking. The term “automated”, e.g. in connection with provision, reminders, ordering or monitoring, is understood in the context of this disclosure to mean an action that the user does not have to trigger through their own actions in a current situation, but which the system, e.g. an app, triggers automatically with the help of a corresponding algorithm. In a preferred embodiment, the user must have authorized the system, e.g. the app, to carry out this “automated action” at an earlier point in time.In an equally preferred variant, the system can always suggest these actions to the user when certain conditions are met, whereby in this case the user must then authorize the execution of the action at that time.

[0331] It is clear to the expert that it is also possible to combine the above-mentioned aspects in order to provide the user with special measures or offers tailored to his preferences and needs, and to test the effectiveness of these offers, for example with the help of subsequent measurements, and to propose new, adapted ones if necessary.

[0332] In order to calculate certain values, generate individual advice on how to improve measurement results or provide additional information, additional information may be required for a specific case, which can be requested via the app, for example. This includes, for example, the user's age, gender, height, weight, occupation, location, but also data on certain diseases that influence the measurement results or their interpretation, such as diabetes. In an advantageous design, the app therefore offers input options for several of these parameters. In a preferred variant, additional information also includes the information previously required in connection with the determination of individual metabolism. This includes, for example, lifestyle orLifestyle habits such as smoking, alcohol consumption, sleep duration, current exposure to the sun, use of a solarium, intensity, frequency and duration of physical exertion, e.g. through sports. The data protection regulations applicable in this context can be taken into account on a country-specific basis during use. In a preferred solution, the user can, if they so wish, enter this information once, for example, when configuring the app that the measuring device uses to fulfil its tasks. This process can take place directly after downloading the app for using the measuring device from the App Store. In another preferred solution, this can also be done later. The user can change, add to or delete the necessary entries at any time. The user can enter such data, for example, in the app that, for example,It displays the necessary keyboard or activates the voice assistant so the user can verbally communicate the data. The app can be stored on a device that communicates with the measuring device and sends measurement data and other information to a central server, for example, for evaluation and storage.

[0333] If a measuring device is used by several people, e.g., other family members, the measurement must be assigned to a specific person. This can be achieved, for example, by creating user profiles that can be selected before each measurement. In the user profile, in addition to the self-selected name (alias), the previously described personal

[0334] Information about the additional users will be stored. In the preferred variant, the measuring device automatically identifies the user based on measured optical properties, which allow the user to be differentiated from other users. In the preferred variant, the sensor reports which user was recognized so that subsequent correction is possible. In the advantageous variant, the system reports if the user could not be recognized and, if necessary, offers possible suitable users to choose from. In general, the more often a person measures themselves, the more accurately physiological states and their changes can be recorded. This means that more targeted advice can be given on this basis, e.g. via the app. In the advantageous variant, the user can therefore select a function in their user profile for which the app prompts them to take a measurement. This setting can be individually tailored to the user and adjusted to their preferences.

[0335] This is particularly advantageous with regard to the analysis of whether a user belongs to the group of people with sharply falling blood sugar levels, because in a preferred variant the user is then prompted to carry out measurements at specific times and at a specific rhythm that makes the detection of sharply falling values ​​most likely. To select the time to carry out a measurement, the app can, in a preferred embodiment, for example, rely on the analysis of previous measurements, as well as on times at which the user typically carries out certain activities, e.g. eating meals. In an equally preferred variant the user can also store the typical times for eating meals, for example, in their user profile. In a preferred variant user activities can be linked to the measurement. For example, the user can carry out a measurement after every meal.This allows the user to tell the system when they have eaten a meal, provided the system knows this connection. If there are enough and / or sufficiently recent measurement results in an assigned database that determine a characteristic of the user, the app can advantageously prevent the measurement of further data. This can be achieved by omitting parts of the measurement sequence. This can be done through communication or even omission of communication. For example, if the user has been assigned to the group with sharply falling blood sugar levels, this function of the app can advantageously no longer prompt them to carry out measurements to clarify this aspect. The request to carry out a measurement can be made directly via the app when the app is open. For example, if the appIf the app is not opened on the smartphone, the server can, for example, send this message to the user via SMS, email, or social networks. Alternatively, a push message can be generated. A preferred variant is for measurement results and / or additional information provided to be appropriately visualized, processed, and enriched with supporting information so that they can be used by the person taking the measurements without specialist knowledge and implemented in everyday activities. In a preferred variant, this can be achieved, for example, by providing the aforementioned results and / or additional information in varying levels of detail, with the user having the option of selecting the level of detail if required.In a particularly preferred variant, the user of the measuring device is also informed of the measured value of a specific substance, for example, certain carotenoids, or how much fruit and vegetables would be consumed daily if the user were to change certain behaviors. In a preferred variant, one or more of the average influences determined in relation to individual metabolism, such as smoking, alcohol consumption, sleep duration, exposure to the sun, etc., are used for this purpose.

[0336] In a preferred variant, the user can contribute to the future measurement of additional measurement parameters, e.g. biomarkers in blood and tissue, using the measuring device. To do this, the user can, for example, select a function in the app via which they can enter measurement values ​​that they have determined using other measurement methods. If the user receives the measurement result from the other measurement method directly after carrying out the measurement, they can promptly carry out a measurement using the measuring device described here. In a preferred variant, it does not matter which biomarker they measure with the measuring device described here. Preferably, such a measurement records optical raw data over a wide spectral range, even if only a specific part is used to determine the biomarker for the specific measurement. Together with the optical raw data, the measurement values ​​entered by the user and determined using other measurement methods, e.g.transmitted to a server and saved as a reference value together with the raw optical data. The external measurement values ​​entered by the user can also be qualitative data, for example data relating to the user's current state of health. If the external data is, for example, laboratory values ​​from a blood draw, the user usually only receives the values ​​a few days after the blood draw. In an advantageous variant, the app offers the option of entering the results retrospectively. However, if the user took a measurement with their own measuring device shortly after the blood draw and tells the measuring app, for example, that they will enter the blood test results retrospectively after receiving them, this data can be assigned to the raw optical data on the server, for example based on their ti...

Claims

Patent claims 1. A device for the optical measurement of substance concentrations or biomarkers in a sample, comprising a contact surface that can be brought into contact with the sample during a measurement process, and optoelectronic components in the form of multiple optical emitters for emitting photons, and multiple detectors for receiving at least a portion of the photons emitted by the emitters and having passed through at least a partial volume of the sample, wherein the emitters and detectors are located on a common plane, and at least nine emitters are provided, and at least three detectors are provided, and the emitters and detectors are mounted at a distance of less than 15 mm from the contact surface, wherein at least three wavelength intervals exist that do not overlap and have an interval length between 2 nm and 20 nm, and in each of the wavelength intervals, at least the peak wavelength of three of the emitters lies,and in each wavelength interval at least two of the emitters, both of which lie within the wavelength interval, have a difference in the peak wavelength of at least 0.5 nm., 2. Device according to claim 1, characterized in that the device is intended for non-invasive measurement on living beings.

3. Device according to one of claims 1 to 2, characterized in that there are pairs of emitters and detectors and for each wavelength interval there are at least two pairs of emitters and detectors in which the distance from the emitter to the detector differs by at least 50% from the distance between the emitter and detector of the other pair.

4. Device according to one of claims 1 to 3, characterized in that the contact surface consists of at least one transparent material and at least one non-transparent material.

5. Device according to one of claims 1 to 4, characterized in that the device is integrated into a smartphone and uses at least one of the cameras of the smartphone as at least one of the detectors.

6. Device according to one of claims 1 to 5, characterized in that it has at least four cavities which are surrounded on all sides except one by non-transparent material and in which either at least one emitter or one detector is located.

7. Device according to one of claims 1 to 6, characterized in that the control of the emitters is designed in such a way that the emitters can be activated successively and individually in a sequence and the brightness detected by each detector for the step of the sequence can be fed to a data processing device 8. A method for the optical measurement of substance concentrations or biomarkers in a sample consisting of human skin, wherein a measuring device has a sensor surface which is a contact surface of the measuring device to the skin, and the contact surface to the skin has partial surfaces that are not transparent, and the contact surface to the skin has partial surfaces that are sufficiently transparent that the emission and detection of photons can occur through the contact surface, and at least nine emitters and at least three detectors are located on a common plane, and the emitters and detectors are mounted at a distance of less than 15 mm from the contact surface, and the emitters are switched on in a measuring sequence, and switched-on emitters emit photons which penetrate the skin through the sensor surface, and a portion of the emitted photons pass through the skin, interact with it, and exit it,pass the sensor surface again and are then detected by one of the detectors of the measuring device, with at least three wavelength intervals of optoelectronic components and / or three distance intervals of the emitter-detector distance of emitter-detector pairs, and in each of these intervals there are at least two optoelectronic components which differ in their wavelength or two emitter-detector pairs which differ in their emitter-detector distance, and the performance of the measurement enables the determination of physiological states of an individual and / or the measurement of the concentration of substances in the human body.

9. The method according to claim 8, characterized in that there are at least three wavelength intervals which do not overlap and which have an interval length between 2 nm and 20 nm, and in each of the wavelength intervals at least the peak wavelength of three of the emitters lies, and in each wavelength interval at least two of the emitters, both of which lie within the wavelength interval, have a difference in the peak wavelength of at least 0.5 nm 10. The method according to claim 8 or 9, characterized in that for a first emitter-detector pair a first measured value for the quantity of detected photons is recorded, and for a second emitter-detector pair a second measured value for the quantity of detected photons is recorded, and the emitter of the first emitter-detector pair lies in the same wavelength interval as the emitter of the second emitter-detector pair, and the emitter of the first emitter-detector pair differs from the emitter of the second emitter-detector pair by the difference in the peak wavelength of the emitter, and the difference in the peak wavelength of the emitter causes a difference between the first measured value and the second measured value, and the measured values ​​are recorded separately so that the difference between the measured values ​​can be evaluated in order to enable an increase in the accuracy of the substance concentration determination.

11. Method according to one of claims 8 to 10, characterized in that the differences in the peak wavelengths of the emitters are included in the calculation of the concentration of the analyte and improve the accuracy of the result.

12. Method according to one of claims 8 to 11, characterized in that data recorded or measured in the production process of the measuring device are used.

13. Method according to one of claims 8 to 12, characterized in that measurement data from measuring devices placed on the market can be stored for evaluation, or that the measuring devices are equipped with at least one data storage device.

14. Method according to one of claims 8 to 13, characterized in that raw optical data from which the properties of individual emitters can be inferred can be recorded and stored, thereby enabling subsequent optimization of the device.

15. Method according to one of claims 8 to 14, characterized in that nutritional recommendations are calculated and issued on the basis of the measured substance concentrations.

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