Non-contact detection of at least one vital parameter

Abstract

To provide a method for detecting in a non contact type, at least one biological parameter of a creature.SOLUTION: A creature 3 exists in a support unit 1 or on the support unit 1, and in the support unit 1 or below the support unit 1, at least three sensors 2 forming a flat surface E are arranged. The sensors 2 detect time variant change of weight and / or time variant change of a centroid of the creature 3 in the flat surface E, and sensor signals (m1, m2, m3, m4) of the at least three sensors 2 are transferred to a control part and are recorded for a prescribed period, the recorded sensor signals (m1, m2, m3, m4) are pre-processed by the control part, the sensor signals (m1, m2, m3, m4) are converted into two-dimensional intermediate signals, then, from the two-dimensional intermediate signals, one-dimensional signals are generated, then, from the one-dimensional signals, at least one biological parameter of the creature is detected.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method for contactless detection of at least one biological parameter of a living being in or on a supporting device. [Background technology]

[0002] Various approaches are already known from the prior art for detecting biological function indicators non-contact from measurement signals recorded non-contact when a living being, in particular a human being, is lying flat on or on a suitable support device.

[0003] On the one hand, systems and methods are already known in which the signal courses of a number of sensors, preferably force-deformation sensors or strain gauges, arranged at various positions on a support device and at least indirectly detecting the movements of a person on the support device, are transformed into frequency space by means of a Fourier transformation, and on the basis of the evaluation of the signals in frequency space, a biofunction indicator, in particular characteristic frequencies and harmonics of the heartbeat, are detected or identified. The disadvantage of using a Fourier transformation in evaluating the signal courses of a number of sensors is that the more efficient and accurate the Fourier transformation, the longer the recorded signals or the longer the signal courses (in terms of time). As a result, only biofunction indicators with a relatively low repetition rate or frequency can be detected. Furthermore, the Fourier transformation is computationally complex, so that the implementation of such a method places high demands on the system, in particular on the computing power. One approach for detecting a biofunction indicator using a Fourier transformation can be seen, for example, from the publication EP 2040614.

[0004] Another approach to avoid the conversion of the signal course into frequency space can be seen, for example, from WO 2017 / 056476, in which the force applied by the person to a support device, in particular a hospital bed or a nursing bed, based on the measurement signal or from the measurement signal is determined on the basis of the signal course of a number of sensors, preferably force deformation sensors or strain gauges, in which case a body mass vector is determined on the basis of the signal course, and a body function indicator is identified, for example a heartbeat, based on the change in the body mass vector over time. This approach is also relatively complex and computationally demanding.

[0005] Apparatuses capable of using corresponding processes from the prior art are known, for example, from EP 1937148 or DE Utility Model 202008018439. Summary of the Invention

[0006] The object of the present invention is therefore to solve the problems mainly arising in the prior art and to propose a method for contactlessly detecting at least one vital parameter, in particular the heart rate, of a person in or on a supporting device, in particular a hospital bed or a nursing bed, based on a measurement signal measured or generated contactlessly, which method makes it possible to detect vital parameters in a particularly simple, efficient and resource-saving manner.

[0007] This problem is solved in a method as described at the beginning, in which at least three sensors are arranged in or below the support device, the at least three sensors form a plane, the sensors detect temporal changes in the weight and / or the center of gravity of the living organism in the plane, sensor signals of the at least three sensors are transferred to a control unit and recorded over a predetermined time, the recorded sensor signals are preprocessed by the control unit, the sensor signals are converted into two-dimensional intermediate signals, subsequently a one-dimensional signal is generated from the two-dimensional intermediate signals, and at least one biological parameter of the living organism is detected from the one-dimensional signal.

[0008] A one-dimensional signal is derived from a two-dimensional intermediate signal by the formula

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[0009] The two-dimensional intermediate signal corresponds to the change in weight and / or the change in centre of gravity of the organism.

[0010] Alternatively, a one-dimensional signal can be generated from the curvature of a two-dimensional intermediate signal.

[0011] The method of the present invention achieves signal improvement or signal amplification in the individual signals of the sensors without requiring complex Fourier transformation or detection of the body mass vector, which in general allows at least one biological parameter, in particular heart rate, to be determined or can be determined with greater reliability and greater accuracy.

[0012] This particularly advantageously achieves a contactless detection of vital parameters, such as the heart rate, in a short time and therefore with a high achievable reproducibility, in a simple, efficient and reliable manner, which in particular allows observation or monitoring of a person lying flat on or on a support device, without requiring special effort for the observation or monitoring and without the need for a monitor to be located on or in the immediate vicinity of the person being monitored on or on the support device.

[0013] According to another configuration of the method, in the one-dimensional signal, there is a repeating signal sequence corresponding to a biological parameter, and the control unit performs a pattern recognition to identify the repeating signal sequence, where the repeating signal sequence can correspond to a biological parameter per time unit, in particular heart beats per minute. For example, for this purpose, the control unit can perform an autocorrelation.

[0014] According to another configuration of the method, the sensors form a plane, on which the living being is placed. The two-dimensional intermediate signal includes or represents the time change in the weight and / or the time change in the center of gravity of the living being along the longitudinal and transverse axes of the plane. Preferably, the two-dimensional intermediate signal corresponds to the movement of the center of gravity of the living being in the plane. This allows to detect very small changes in the center of gravity of the living being. In particular, the change in the center of gravity of the living being detected by the preferably four sensors arranged in or below the plane of the support device is the amount of blood ejected during myocardial contraction or heartbeat. Based on the amount of blood ejected, the center of gravity of the living being on the support device changes, and this change is detected by the sensors. Here, the center of gravity of the living being does not change only in one direction of the plane, but along the longitudinal and transverse axes of the plane.

[0015] In particular, the control unit detects the center of gravity of the living thing by the following formula:

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[0016] The change in the center of gravity of an organism over time is expressed along the vertical axis of the plane by the formula

number

[0017] The change in time of the center of mass of an organism along the horizontal axis of the plane is given by the formula

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[0018] According to another configuration of the method, the control unit detects the center of gravity and / or the total weight of the living being on the support device. The detection of the total weight and / or the center of gravity of the living being is performed before the actual measurement of the biological parameters. If the center of gravity and / or the total weight of the living being is greater than a predefined boundary value, the detection of the biological parameters can be terminated. In particular, the control unit can interrupt the detection of the biological parameters when the center of gravity and / or the total weight of the living being changes by at least 2%. Based on the boundary value, a movement of the living being can be detected and a presence identification can also be performed to detect the occupancy of the support device. For example, the support device can be a bed and biological parameters, in particular the heart rate, can be determined from a living being, in particular a human being who should lie on the bed. As soon as a second person sits on the bed, a reliable identification of the heart rate can no longer be guaranteed, because two heart rates would be detected, which could lead to erroneous results.

[0019] According to another configuration of the method, the sensor signals of at least three sensors are recorded in a time-synchronous manner, which allows accurate detection of changes in weight and / or centre of gravity.

[0020] According to a further configuration of the method, the pre-processing of the signal curves of the individual sensors can further comprise the removal of a direct current voltage offset (DC offset) and / or the application of a high-pass filter and / or the application of a low-pass filter.

[0021] The above-mentioned pre-processing step of each individual signal course can provide a better basis for creating a two-dimensional intermediate signal. For example, the DC voltage offset can be removed from each individual signal of a number of sensors, preferably four sensors. The DC voltage offset reproduces or represents the weight of the support device as well as the human body without the movement of the human body. In particular, the four sensors are arranged in or under the support device.

[0022] It should be noted here that a DC voltage offset can be used to perform presence identification and / or detection of a person on the supporting device or the weight or mass of a person on the supporting device, with the known characteristics of the supporting device itself and its degradation in the signal of the sensor being taken into account, i.e., for example, the specific weight of the supporting device must be excluded from the calculation. Presence identification can be used, for example, as an initiator or interrupt criterion for carrying out the method according to the invention. Mass detection or weight detection can be further used or can be used within the framework of monitoring or observation of a person on or at the supporting device.

[0023] Then, the individual signals can be prefiltered, preferably the signals of a single sensor are further processed or filtered by different filters, where the filtering is not performed sequentially but independently of each other. That is, in the preprocessing of the signals, it is particularly preferable that the individual signals of the sensors are subjected to different filtering processes. For example, after removing the DC voltage offset, the signal of at least one sensor or the signal curve of the sensor is fed to a high-pass filter on the one hand and independently to a low-pass filter or filtered with a corresponding filter, followed by combining the filtered signal curves within the framework of forming the difference between the two filtered signal curves.

[0024] Alternatively, however, the filtering of the signal course can be performed continuously or sequentially on the signal course of one sensor or one channel, for example, first a low-pass filter can be applied to the signal course and then a high-pass filter can be applied to the signal course.

[0025] Furthermore, the automatically detected biological parameters, in particular the heart rate, can be automatically classified into a standardized interval classification, preferably the international classification of the American Heart Association (AHA), so that the heart rate is classified into the corresponding intervals, which can also be evaluated very well within the framework of observation or monitoring and particularly intuitively with respect to possible existing processing or reaction demands, especially when the heart rate is classified into the correspondingly high or correspondingly low interval class.

[0026] According to another particularly advantageous embodiment of the method, an adaptive sensitivity of the discrimination algorithm can be applied within the scope of peak or maximum value detection. This means, in other words, that within the scope of peak value detection, adaptive boundary values ​​can be defined, which adaptive boundary values ​​change with the course of the signal, in particular after the detection of a local maximum, and which are influenced by various factors, so as to ensure that only successive or adjacent maxima are identified or detected, respectively. As factors or influencing characteristic values ​​for the adaptive sensitivity or adaptive boundary value, for example, the following can be used: the (normalized) value of the last detected maximum, the width of the last detected peak or maximum value taking into account the zero crossing, the inflection point or special rising characteristic, a time factor or delay factor for a linear or non-linear lowering of the threshold or boundary value with a larger interval or time course from the time of the last detected peak, etc.

[0027] In particular, the signal course of the sensor can be recorded over a period of from 2 to 60 seconds, preferably from 5 to 30 seconds, particularly preferably from 7 to 15 seconds, and can be stored in an intermediate memory for pre-processing and / or further processing.

[0028] In another configuration of the method, the at least three sensors are force sensors and / or weight sensors and / or acceleration sensors, which are arranged in and / or below the support device, in particular in the immediate vicinity of the living being. [Brief description of the drawings]

[0029] Further advantageous aspects will become apparent from the following description of preferred embodiments which refers to the accompanying drawings.

[0030] [Figure 1] FIG. [Diagram 2] The sensor signal recorded over a period of time. [Diagram 3] It is a one-dimensional signal. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0031] FIG. 1 shows a very schematic plan view of a support device 1, for example a hospital or nursing bed. FIG. 1 suggests that four sensors 2 are arranged at the four corners of the support device 1, for example in the region of the four bedposts, which sensors 2 are preferably configured as force or weight sensors or strain gauges and detect or measure forces on the support members of the platform of the support device 1. The support device 1 has a plane E. Across the plane E, a living being 3 or a human being 3 is arranged. The human being 3 is therefore arranged parallel to the plane E. Furthermore, the longitudinal axis Y and the transverse axis X of the plane E particularly preferably correspond to the longitudinal and transverse axes of the human being 3. The sensors 2, which supply the measurements to the four input channels of the control used in the method, can measure measurement or sensor signals m1, m2, m3, m4 that reflect parts of the support device 1 itself and the static load of the support device 1 by the human being 3 or the weight of the support device 1. At the same time, however, the sensor signals m1, m2, m3, m4 of the sensors 2 also contain signal components resulting from the one-time or repeated movements of the person 3 and the associated changes in the load on the support device 1.

[0032] Furthermore, the support device 1 can be a seat, in particular a seating surface of a vehicle seat. In this case, the sensor can be arranged under the seating surface or on the rails of the seat. This allows possible slight movements of the person 3 to be detected, and also the weight of the driver or passenger and some signals important for the life. This also allows the detection of the seating position, in which case it is possible to distinguish whether the object is a living being or an object placed on the seat. This allows the seat identification to be identified based on at least one bio-parameter without being linked to a boundary value, whether a living being or an object is present on the seating surface. Furthermore, the bio-parameters of the driver, in particular the heart rate, can be detected, and whether the driver can continue driving, for example a myocardial infarction of the driver, which causes the driver to no longer be able to control the vehicle. This identification can be linked to further driving assistance systems, so that the control unit can, for example, move the vehicle to the side of the road in the event of a myocardial infarction of the driver, slow it down until it stops, issue an emergency call and activate the hazard lights. This allows serious accidents to be avoided.

[0033] For further improvement, the driver's reaction to vibrations caused by all the movements and driving of the vehicle can also be detected by sensors that give a lot of information about the health of the driver or passengers. The airbag settings can also be adapted, for example, by combining the determined weight with size information from a camera additionally installed in the vehicle interior.

[0034] FIG. 2 shows the sensor signals m1, m2, m3, m4 of the sensors 2 recorded over a period of time. The a-axis shows the change in the centre of gravity of the living being 3 along the vertical axis, in particular the centre of gravity of the human 3 from the head part of the support apparatus 1, in particular the bed, to the foot part of the support apparatus 1. The b-axis shows the change in the centre of gravity of the living being 3 along the horizontal axis, in particular the centre of gravity of the human 3 from the left side of the body to the right side of the body. The t-axis shows time. From these, a two-dimensional intermediate signal 4 or plane curve 4 is obtained, which represents in two dimensions the change in the centre of gravity of the living being 3 over time. In this case, the temporal change in the centre of gravity of the living being (3) along the vertical axis of the plane (E) is calculated according to the formula

number

[0035] Furthermore, the change in time of the center of gravity of the organism (3) along the horizontal axis of the plane (E) is given by the formula

number

[0036] 3 shows a one-dimensional signal 5 plotted over time. The one-dimensional signal 5 is generated from the two-dimensional intermediate signal 4, where the curvature of the two-dimensional intermediate signal results in the one-dimensional signal 5, or the one-dimensional signal (5) is derived from the two-dimensional intermediate signal (4) according to the formula:

number

[0037] 1 Support device 2 Sensors 3 Humans / Living Things 4. Two-dimensional intermediate signals 5 One-dimensional signals 6 Repeating Signal Sequences E plane m1 Sensor signal m2 Sensor signal m3 sensor signal m4 sensor signal

Claims

1. A method for contactlessly detecting at least one biological parameter of a living being (3), comprising the steps of: The living being (3) is present on or on a support device (1), at least three sensors (2) are arranged in or under the support device (1) forming a plane (E), the sensors (2) detect a temporal change in the weight and / or a temporal change in the center of gravity of the living being (3) in the plane (E), sensor signals (m1, m2, m3, m4) of the at least three sensors (2) are transferred to a control unit and recorded for a predetermined time, the recorded sensor signals (m1, m2, m3, m4) are pre-processed by the control unit, the sensor signals (m1, m2, m3, m4) are converted into two-dimensional intermediate signals (4), a one-dimensional signal (5) is then generated from the two-dimensional intermediate signals (4), and at least one biological parameter of the living being is detected from the one-dimensional signal (5), A method, characterized in that said one-dimensional signal (5) is generated from the curvature of said two-dimensional intermediate signal (4).

2. 2. The method of claim 1, wherein repetitive signal sequences (6) are present in the one-dimensional signal (5) and the control unit performs pattern recognition to identify the repetitive signal sequences (6).

3. 3. A method according to claim 2, characterized in that said repetitive signal sequence (6) corresponds to said biological parameter per time unit.

4. 4. The method according to claim 1, wherein the living being (3) is arranged on the plane (E).

5. 5. The method according to claim 1, wherein the control unit detects the center of gravity and / or the total weight of the living being (3) on the support device (1).

6. 6. The method according to claim 5, characterized in that the detection of the biological parameters is terminated if the change in the centre of gravity and / or the total weight of the living being (3) is greater than a predefined boundary value.

7. 7. Method according to any one of claims 1 to 6, characterized in that four sensors (2) are arranged in or beneath the supporting device (1).

8. The control unit calculates the center of gravity of the living thing (3) by the formula [0010] The method according to claim 7, characterized in that the detection is performed by:

9. 9. The method according to claim 7 or 8, characterized in that the two-dimensional intermediate signal (4) represents the temporal variation of the weight and / or the temporal variation of the centre of gravity of the living being (3) along the longitudinal and transverse axes of the plane (E).

10. The change in time of the center of gravity of the organism (3) along the longitudinal axis of the plane (E) is expressed by the formula [0025] The method according to claim 9, characterized in that the detection is performed by

11. The change in time of the center of gravity of the organism (3) along the horizontal axis of the plane (E) is expressed by the formula [0030] The method according to claim 9 or 10, characterized in that the detection is performed by

12. The one-dimensional signal (5) is obtained from the two-dimensional intermediate signal (4) by the formula [0045] 12. The method according to claim 10 or 11, characterized in that it is calculated by:

13. 13. The method according to any one of the preceding claims, characterized in that the sensor signals (m1, m2, m3, m4) of the at least three sensors (2) are recorded time-synchronously.

14. 14. The method according to claim 1, characterized in that the pre-processing of the sensor signals (m1, m2, m3, m4) comprises removing a DC voltage offset and / or applying a high-pass filter and / or applying a low-pass filter.

15. 15. Method according to any one of the preceding claims, characterized in that the at least three sensors (2) are force sensors and / or weight sensors and / or acceleration sensors.

16. 16. The method according to any one of the preceding claims, characterized in that the biological parameter is the heart rate of the living being (3).

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