Apparatus and method for estimating biological information

Abstract

Devices and methods for estimating biological information are provided. A device for estimating biological information can include a sensor portion including a pixel array of pixels each having a light source and a detector, and a processor configured to drive the sensor portion based on a first sensor configuration based on an object being in contact with the sensor portion, obtain contact information of the object based on an amount of light received by each pixel according to the first sensor configuration, determine a second sensor configuration based on the contact information, drive the sensor portion based on the second sensor configuration, and estimate biological information based on light signals obtained according to the second sensor configuration.

Description

[0001] This application claims priority to Korean Patent Application No. 10-2020-0111847, filed on September 2, 2020, with the Korean Intellectual Property Office, the entire disclosure of which is incorporated herein by reference for all purposes. Technical Field

[0002] Example embodiments of this disclosure relate to apparatus and methods for non-invasively estimating biological information. Background Technology

[0003] According to general methods for non-invasive triglyceride measurement, the concentration of triglycerides in the blood is estimated by placing a measuring device with a light source and optical sensors on the blood vessel and measuring the scattered light signal transmitted through the blood. Changes in blood triglyceride concentration lead to changes in the scattering coefficient, allowing the change in the scattering coefficient to be obtained from the change in the scattered light signal, and the blood triglyceride concentration can be estimated based on the change in the scattering coefficient. Summary of the Invention

[0004] According to one aspect of an example embodiment, an apparatus for estimating biological information may include: a sensor unit including a pixel array of pixels, each pixel having a light source and a detector; and a processor configured to: drive the sensor unit based on a first sensor configuration based on contact between an object and the sensor unit; obtain contact information of the object based on the amount of light received through each pixel according to the first sensor configuration; determine a second sensor configuration based on the contact information; drive the sensor unit based on the second sensor configuration; and estimate biological information based on light signals obtained according to the second sensor configuration.

[0005] The first sensor configuration may include at least one of the following: time-division driving method, sequential driving method, simultaneous driving method, driving order, light source intensity, and duration.

[0006] The processor can obtain contact information based on at least one of the following: pixels with light intensity greater than or equal to a predetermined threshold, pixels with light intensity greater than or equal to a predetermined percentage of the average of the total light intensity, pixels with light intensity greater than or equal to a predetermined percentage of the maximum light intensity, and pixels with light intensity greater than or equal to a predetermined percentage of the average of the light intensity falling within a predetermined range of the maximum light intensity.

[0007] The processor can obtain contact information including at least one of the following: the contact area of ​​the object, the center point of the contact area, the center point of the fingerprint, and the contact direction.

[0008] The processor can determine the light source pixels and detector pixels of the second sensor configuration based on the contact information.

[0009] The processor can identify one or more pixels located at a predetermined position in the contact direction among the pixels in the contact area as light source pixels configured for the second sensor; and identify one or more pixels located within a predetermined range from the center point of the contact area or the center point of the fingerprint as detector pixels configured for the second sensor.

[0010] The processor can map the reference area, reference direction, and reference center point of a predefined reference sensor configuration to the contact area, contact direction, and center point of the contact area; and based on the mapping, determine the pixel corresponding to the light source pixel of the predefined reference sensor configuration as the light source pixel of the second sensor configuration, and determine the pixel corresponding to the detector pixel of the predefined reference sensor configuration as the detector pixel of the second sensor configuration.

[0011] The sensor unit can obtain a fingerprint image based on the contact between the object and the sensor unit, and the processor can obtain contact information based on the fingerprint image.

[0012] The processor can respond to the fact that the center point of the fingerprint is not within the predetermined range of the sensor unit, and control the output interface to guide the user to place the object on the sensor unit.

[0013] The processor can calculate the scattering coefficient based on the light signal obtained according to the configuration of the second sensor; and estimate biological information based on the scattering coefficient.

[0014] The processor can, in response to acquiring light signals according to the configuration of the second sensor, calculate the similarity between the light signals; and select light signals with a similarity greater than or equal to a first threshold as light signals for estimating biological information.

[0015] The processor can, in response to acquiring light signals according to the configuration of the second sensor, calculate the similarity between the light signals; and exclude light signals with a similarity less than or equal to a second threshold as light signals for estimating biological information.

[0016] Bioinformation may include at least one of the following: triglycerides, body fat percentage, body water, blood glucose, cholesterol, carotenoids, protein, and uric acid.

[0017] According to one aspect of an example embodiment, a method for estimating biometric information may include: driving a sensor unit based on a first sensor configuration based on contact between an object and a sensor unit; obtaining contact information of the object based on the amount of light received through each pixel of the sensor unit according to the first sensor configuration; determining a second sensor configuration based on the contact information; driving the sensor unit based on the second sensor configuration; and estimating biometric information based on an optical signal obtained according to the second sensor configuration.

[0018] The step of obtaining contact information may include obtaining contact information based on at least one of the following: a pixel having a light amount greater than or equal to a predetermined threshold, a pixel having a light amount greater than or equal to a predetermined percentage of the average of the total light amount, a pixel having a light amount greater than or equal to a predetermined percentage of the maximum light amount, and a pixel having a light amount greater than or equal to a predetermined percentage of the average of the light amount falling within a predetermined range of the maximum light amount.

[0019] The steps of obtaining contact information may include obtaining contact information including at least one of the following: the contact area of ​​the object, the center point of the contact area, the center point of the fingerprint, and the contact direction.

[0020] The step of determining the second sensor configuration may include: determining one or more pixels located at a predetermined position in the contact direction among the pixels in the contact area as light source pixels of the second sensor configuration; and determining one or more pixels located within a predetermined range from the center point of the contact area or the center point of the fingerprint as detector pixels of the second sensor configuration.

[0021] The step of determining the second sensor configuration may include: mapping the reference area, reference direction, and reference center point of a predefined reference sensor configuration to the contact area, contact direction, and center point of the contact area; and based on the mapping, determining the pixel corresponding to the light source pixel of the predefined reference sensor configuration as the light source pixel of the second sensor configuration, and determining the pixel corresponding to the detector pixel of the predefined reference sensor configuration as the detector pixel of the second sensor configuration.

[0022] The method may include obtaining a fingerprint image based on contact between an object and a sensor.

[0023] The steps to obtain contact information may include: obtaining contact information based on fingerprint images.

[0024] The method may include: in response to the fingerprint center point being outside a predetermined range of the sensor unit, controlling the output interface to guide the user to place the object on the sensor unit.

[0025] The steps for estimating biological information may include: calculating a scattering coefficient based on two or more optical signals obtained through a sensor unit; and estimating biological information based on the scattering coefficient.

[0026] The steps for estimating biological information may include: calculating the similarity between light signals in response to light signals being acquired by a sensor unit; and selecting light signals having a similarity greater than or equal to a first threshold as light signals for estimating biological information.

[0027] The steps for estimating biological information may include: calculating the similarity between light signals in response to light signals obtained through a sensor unit; and excluding light signals with a similarity less than or equal to a second threshold as light signals for estimating biological information. Attached Figure Description

[0028] The above and other aspects, features, and advantages of specific exemplary embodiments of the present disclosure will become clearer from the following description taken in conjunction with the accompanying drawings, in which:

[0029] Figure 1 This is a block diagram illustrating an apparatus for estimating biological information according to an example embodiment;

[0030] Figure 2 This is a block diagram illustrating an apparatus for estimating biological information according to another example embodiment;

[0031] Figure 3 This is a block diagram illustrating the configuration of a processor according to an example embodiment;

[0032] Figure 4A and Figure 4B This is a diagram illustrating an example of obtaining contact information of an object;

[0033] Figure 4C , Figure 4D and Figure 4E This is a diagram illustrating an example of obtaining the configuration of the second sensor;

[0034] Figure 5A and 5B This is a diagram illustrating an example of estimating biological information;

[0035] Figure 6 This is a flowchart illustrating a method for estimating biological information according to an example embodiment;

[0036] Figure 7 This is an illustration showing an example of a wearable device; and

[0037] Figure 8 This is a diagram showing an example of a smart device. Detailed Implementation

[0038] Details of exemplary embodiments are provided in the following detailed description and accompanying drawings. The advantages and features of this disclosure, as well as methods for implementing this disclosure, will become clearer from the exemplary embodiments described in detail below with reference to the accompanying drawings. Throughout the drawings and detailed description, the same reference numerals will be understood to denote the same elements, features, and structures, unless otherwise described.

[0039] It will be understood that although the terms “first,” “second,” etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. Furthermore, unless the context clearly indicates otherwise, the singular form of a term is intended to include the plural form as well. It will also be understood that, unless explicitly stated otherwise, when an element is referred to as “including” another element, that element is not intended to exclude one or more other elements, but rather to include one or more other elements. In the following description, terms (such as “unit” and “module”) indicate units used to perform at least one function or operation, and they may be implemented using hardware, software, or a combination thereof. As used herein, when an expression such as “at least one of…” follows a list of elements, it modifies the entire list of elements, not a single element within the list. For example, the expression “at least one of a, b, and c” should be understood to include only a, only b, only c, both a and b, both a and c, both b and c, or all of a, b, and c.

[0040] In the following, exemplary embodiments of devices and methods for estimating biological information will be described in detail with reference to the accompanying drawings. Various exemplary embodiments of devices for estimating biological information can be installed in terminals (such as smartphones, tablet PCs, desktop computers, laptop computers, etc.), wearable devices, etc. In this case, examples of wearable devices may include wristwatch-type wearable devices, bracelet-type wearable devices, wristband-type wearable devices, ring-type wearable devices, glasses-type wearable devices, headband-type wearable devices, etc., but wearable devices are not limited to these.

[0041] Figure 1 This is a block diagram illustrating a device for estimating biological information according to an example embodiment.

[0042] Reference Figure 1 The device 100 for estimating biological information includes a sensor unit 110 and a processor 120.

[0043] The sensor unit 110 includes a pixel array having multiple pixels. Each pixel may include one or more light sources for emitting light onto an object and one or more detectors for detecting light scattered or reflected from the object. Furthermore, partitions for blocking light may be disposed between pixels and / or between the light source and detector of each pixel.

[0044] Light sources may include light-emitting diodes (LEDs), laser diodes (LDs), phosphors, etc. If each pixel includes multiple light sources, these multiple light sources can emit light of different wavelengths. Detectors can detect light emitted by the light sources after it has been absorbed into the object OBJ or reflected or scattered from the object OBJ. Detectors may include photodiodes, phototransistors (PTr), image sensors, etc.

[0045] Furthermore, the sensor unit 110 may also include a fingerprint sensor. The fingerprint sensor may be disposed on the top or bottom of the pixel array of the sensor unit 110. The fingerprint sensor can acquire an image of a wrinkle on a body part in contact with the pixel array. However, the wrinkle image is not limited to this, and can be acquired by manufacturing each pixel of the pixel array to a sufficiently small size and by scanning all pixels in the driving pixel array. Here, the body part can be any body part from which a photoplethysmography (PPG) signal can be detected, and the following description will use a finger as an example of a body part, such that a wrinkle on the body part can be designated as a fingerprint, and the "fingerprint center point" described with respect to a fingerprint can be an example of a feature point of a wrinkle on the body part.

[0046] The processor 120 is electrically connected to the sensor unit 110 and can control the sensor unit 110 in response to a request to estimate biological information. Furthermore, the processor 120 can receive light signals from the sensor unit 110 and can estimate biological information based on the received light signals. In this case, the biological information may include at least one of, but is not limited to, triglycerides, body fat percentage, body water, blood glucose, cholesterol, carotenoids, protein, uric acid, etc. The following description will use triglycerides as an example.

[0047] For example, in response to a request to estimate biometric information, the processor 120 may drive the sensor unit 110 based on a first sensor configuration. In this case, the first sensor configuration may include information about the sensor unit 110 (such as driving method, driving order, light source intensity, duration, etc.). Furthermore, the processor 120 may obtain contact information of an object based on the light signal obtained by the sensor unit 110 based on the first sensor configuration. In this case, the contact information may include, but is not limited to, the contact area of ​​the object, the center point of the contact area, the center point of the fingerprint, the contact direction, etc.

[0048] Based on the contact information obtained as described above, the processor 120 can determine a second sensor configuration and drive the sensor unit 110 based on the determined second sensor configuration. The second sensor configuration can be determined as various combinations of light source pixels having a light source to be driven and detector pixels having a detector to be driven, among all pixels of the sensor unit 110, wherein the light source and detector are arranged at different distances from each other, such that the scattered light signal can be obtained via two or more different paths. For example, the pixel combinations may include: a combination of one light source pixel and multiple detector pixels, a combination of multiple light source pixels and one detector pixel, a combination of multiple light source pixels and multiple detector pixels, etc. In this case, the light source pixel may refer to a pixel in the pixel array having a light source to be driven, and the detector pixel may refer to a pixel in the pixel array having a detector to be driven.

[0049] Furthermore, since the sensor unit 110 acquires a light signal based on the second sensor configuration, the processor 120 can estimate biological information based on the acquired light signal. The processor 120 can amplify the light signal acquired by the sensor unit 110 using an amplifier, or convert the signal into a digital signal using an analog-to-digital converter or the like.

[0050] Figure 2 This is a block diagram illustrating a device for estimating biological information according to another example embodiment.

[0051] Reference Figure 2 According to another example embodiment, a device 200 for estimating biological information includes a sensor unit 110, a processor 120, a storage device 210, an output interface 220, and a communication interface 230. The sensor unit 110 and the processor 120 have been described above, so repeated descriptions will be omitted.

[0052] Storage device 210 can store information related to the estimated biometric information. For example, storage device 210 can store light signals and / or estimated biometric information values. Furthermore, storage device 210 can store a first sensor configuration, a reference sensor configuration, a second sensor configuration, a standard for determining the second sensor configuration, a standard for obtaining contact information, user characteristic information, etc. In this case, user characteristic information may include the user's age, gender, health status, etc.

[0053] Storage device 210 may include at least one of the following storage media: flash memory, hard disk memory, multimedia card micro memory, card-type memory (e.g., Secure Digital (SD) memory, Extreme Digital (XD) memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk and optical disk, etc., but is not limited thereto.

[0054] Output interface 220 can provide the user with the processing results of processor 120. For example, output interface 220 can display the estimated biometric value on a display. In this case, if the estimated biometric value falls outside the normal range, output interface 220 can provide a warning message to the user by changing the color, line thickness, etc., or by displaying the abnormal value together with the normal range, so that the user can easily identify the abnormal value. In addition, whether or not a visual display is available, output interface 220 can use a voice output module (such as a speaker) or a haptic module to provide the biometric estimation results in a non-visual manner (such as through voice, vibration, touch, etc.).

[0055] The communication interface 230 can communicate with external devices to send and receive various data related to the estimation of biological information. In this case, the external device may include an information processing device (such as a smartphone, tablet PC, desktop computer, laptop computer, etc.). For example, the communication interface 230 can send the bioinformatics estimation results to the user's smartphone, etc., so that the user can manage and monitor the bioinformatics estimation results using a device with relatively high performance.

[0056] In this context, the communication interface 230 can communicate with external devices using various wired or wireless communication technologies, such as Bluetooth, Bluetooth Low Energy (BLE), Near Field Communication (NFC), Wireless Local Area Network (WLAN), Zigbee, Infrared Data Association (IrDA), Wi-Fi Direct (WFD), Ultra Wideband (UWB), Ant+, Wi-Fi, Radio Frequency Identification (RFID), 3G, 4G, and 5G. However, the aforementioned communication technologies are merely examples and not intended to be limiting.

[0057] Figure 3 This is a block diagram illustrating the configuration of a processor according to an example embodiment. Figure 4A and Figure 4B This is a diagram illustrating an example of obtaining contact information of an object. Figure 4C , Figure 4D and Figure 4E This is a diagram illustrating an example of obtaining a second sensor configuration. Figure 5A and Figure 5B This is a diagram illustrating an example of estimating biological information.

[0058] Reference Figure 3 The processor 300 according to the embodiment includes a sensor driver 310, a contact information acquirer 320, a sensor configuration determiner 330, and an estimator 340.

[0059] Reference Figure 4A The sensor unit 110 may include a pixel array 40 having a plurality of pixels 41. Each pixel 41 may include one or more light sources L1 and L2 and a detector PD. In this case, partition walls 42 may be provided between the plurality of pixels 41 and / or between the light sources L1 and L2 and the detector PD of each pixel 41.

[0060] When a finger is placed on the sensor unit 110, the sensor driver 310 can drive the pixel array 40 by referring to a first sensor configuration for obtaining contact information of the finger. The first sensor configuration may include information about the pixels to be driven (e.g., information relating to the pixels in the entire pixel array 40 that are to be driven to obtain contact information). In this case, the pixels to be driven may be set to all pixels in the pixel array 40. However, the pixels to be driven are not limited to this, and the pixels to be driven may be set to pixels in some rows / columns (e.g., pixels in odd / even rows / columns, for example) by taking into account power consumption, required estimation accuracy, etc. Furthermore, the first sensor configuration may include a driving method, driving order, light source intensity, duration, etc. The driving method may be set to any of, for example, sequential driving, time-division driving, and simultaneous driving.

[0061] By driving all the pixels to be driven under the control of the sensor driver 310, and by turning on the light source of the specific driven pixel and detecting the light using the detector of the specific driven pixel, the sensor unit 110 can scan the finger and obtain the light signal of all the driven pixels.

[0062] Reference Figure 4B When the finger OBJ comes into contact with the pixel array 40 of the sensor unit 110, the pixel array 40 of the sensor unit 110 can be divided into a contact area (CA) that comes into contact with the finger OBJ and a non-contact area (NA) that does not come into contact with the finger OBJ.

[0063] like Figure 4BAs shown, based on the light signal obtained by the sensor unit 110 through scanning a finger, the contact information acquirer 320 can acquire the contact information of the finger based on the obtained light signal. In one exemplary embodiment, the contact information acquirer 320 can acquire the contact information based on the amount of light received by each pixel according to the first sensor configuration. For example, the contact information acquirer 320 can acquire the area of pixels where the amount of light received by each pixel is greater than or equal to a predetermined threshold as the contact area CA. Optionally, the contact information acquirer 320 can acquire the following area as the contact area CA: the area of pixels having an amount of light greater than or equal to a predetermined percentage of the average of the total amount of light received by all pixels, the area of pixels having an amount of light greater than or equal to a predetermined percentage of the maximum amount of light, and / or the area of pixels having an amount of light greater than or equal to a predetermined percentage of the average of the amount of light of pixels having an amount of light falling within a predetermined percentage range of the maximum amount of light (e.g., A% to B% of the maximum amount of light, where 0 ≤ A < B ≤ 100) among multiple pixels. However, these are only examples. In addition, the contact information acquirer 320 can acquire the center point and / or the contact direction of the obtained contact area CA. In one example, the contact direction can represent the direction in which the object is placed relative to the sensor unit 110 on the sensor unit 110.

[0064] In addition, if the sensor unit 110 acquires a fingerprint image, the contact information acquirer 320 can analyze the fingerprint image to acquire the fingerprint center point, the contact area, and / or the contact direction.

[0065] The sensor configuration determiner 330 can determine a second sensor configuration for estimating biometric information based on the contact information. In this case, the second sensor configuration can include information related to light source pixels and detector pixels, where the light source pixels have a light source to be driven to emit light onto the object, and the detector pixels have a detector to be driven to detect the light signal from the object. In this case, the light source pixels can be different from the detector pixels. The light source pixels can include at least one pixel, and the detector pixels can include multiple pixels for detecting light scattered from different positions of the object.

[0066] Referring to Figure 4C , the sensor configuration determiner 330 can determine the pixel 11 at a predetermined position in the contact direction D among the pixels in the contact area CA in the pixel array 40 as the light source pixel LP. In this case, the criteria for determining the light source pixel (such as taking the example of determining the pixel at the forefront of the contact area CA) can be preset.

[0067] Furthermore, the sensor configuration determiner 330 can determine pixels 9, 10, 14, 15, 16, 17, 19, 20, 21, 22, 23, 27, and 28 located within a predetermined range including the center point C of the contact area as detector pixels DP. In this case, the criteria used to determine the detector pixels DP (such as a predetermined range, the shape of the predetermined range (e.g., circle, ellipse, polygon, etc.)) can be preset. However, the criteria are not limited to this, and the detector pixels DP can be limited to various pixels (e.g., all pixels, all pixels except the light source pixel LP, or all pixels located below the light source pixel LP, etc.).

[0068] Reference Figure 4D The sensor configuration determiner 330 can determine the light source pixels and detector pixels of the second sensor configuration based on a predefined reference sensor configuration. For example, the reference sensor configuration may include light source pixel LP1, detector pixel DP1, and / or information about a reference center point in a reference region of pixel array 40. In this case, the reference region may be, for example, the entire region of pixel array 40, and the reference center point may be, but is not limited to, the center point of pixel array 40.

[0069] Based on the contact area, contact direction, and center point of the contact area obtained by the contact information acquirer 320, the sensor configuration determiner 330 can map the reference center point to the center point of the contact area, and can rotate the reference direction to the right along the contact direction D to map the reference area to the contact area CA, so that the reference area can overlap with the contact area CA. Based on the mapping, the sensor configuration determiner 330 can determine the pixels 11 corresponding to the light source pixel LP1 and the pixels 7, 8, 13, 14, 15, 19, 20, 21, 22, 25, 26, 27, 28, 29, 31, 32, 33, 34, and 35 corresponding to the detector pixel DP1 in the reference sensor configuration as the light source pixel LP2 and the detector pixel DP2 in the second sensor configuration, respectively. However, this is only an example.

[0070] Figure 4E An example is shown where the configuration of the second sensor is determined based on a fingerprint image. For example... Figure 4E As shown, the sensor configuration determiner 330 can adaptively determine the light source pixels LP1 and LP2 and the detector pixels DP1 and DP2 based on the fingerprint region, fingerprint direction, and fingerprint center points C1 and C2. In this case, if the fingerprint center point is not located within the predetermined area of ​​the sensor unit 110, the sensor configuration determiner 330 can guide the user to place their finger on the sensor unit 110 again. In this case, the predetermined range can be preset.

[0071] As described above, according to the exemplary embodiments of this disclosure, even when the contact area and / or contact direction of the finger changes, the light source pixels and detector pixels of the second sensor configuration can be adaptively determined so that light signals can be detected at a predetermined position of the finger or at the actual contact position of the finger, thereby improving the accuracy of estimating biological information.

[0072] Based on the sensor configuration determiner 330 determining the second sensor configuration, the sensor driver 310 can drive the light source pixels and detector pixels of the sensor unit 110 based on the second sensor configuration.

[0073] Based on the sensor unit 110 acquiring multiple optical signals from multiple optical paths based on the second sensor configuration, the estimator 340 can estimate biological information based on the acquired multiple optical signals. Figure 5A This illustrates an example of light intensity maps for each distance when multiple detector pixels are located at different distances from the light source pixel. For example, as shown... Figure 5A As shown, the intensity of light detected by each detector pixel (e.g., 1, 2, 3, ..., N, etc.) is different from each other.

[0074] The estimator 340 can estimate biological information based on multiple optical signals obtained at different distances. For example, the estimator 340 can calculate a scattering coefficient using the optical signals obtained at each distance, and can estimate biological information using the calculated scattering coefficient. In this case, the scattering coefficient indicates the reduction in light intensity due to scattering of light per unit length of propagation by the light emitted from the light source, and can be defined, for example, as a ratio of the intensities of the scattered light signals detected by multiple detectors, or a value proportional to that ratio. Furthermore, the scattering coefficient can be calculated by considering the distance of each detector from the light source. Alternatively, the estimator 340 can calculate the scattering coefficient by obtaining representative values ​​of multiple optical signal intensities. In this case, representative values ​​of multiple optical signal intensities can be calculated based on various criteria (such as the maximum signal intensity value, the average or median signal intensity, etc.).

[0075] For example, when calculating the scattering coefficient using a scattered light signal detected by a detector, the estimator 340 can calculate the scattering coefficient by using, for example, Equations 1 and 2 below.

[0076] Equation 1

[0077]

[0078] Equation 2

[0079]

[0080] Here, R(ρ) represents the intensity of the light detected by the detector located at a distance ρ from the light source; ρ represents the distance between the light source and the detector; μ a μ represents the absorption coefficient. eff S0 represents the effective attenuation coefficient; S0 represents the intensity of the light emitted by the light source; μ s This represents the scattering coefficient.

[0081] In yet another example, when calculating the scattering coefficient by using two scattered light signals detected by two detectors placed at different distances after the light source emits light, the estimator 340 can calculate the scattering coefficient by using Equation 3 below.

[0082] Equation 3

[0083]

[0084] Here, ρ1 represents the distance between the light source and the first detector; ρ2 represents the distance between the light source and the second detector; R(ρ1) represents the intensity of the light detected by the first detector; R(ρ2) represents the intensity of the light detected by the second detector; μ s This represents the scattering coefficient. The equation used to calculate the scattering coefficient can be defined differently depending on the number of detectors used to detect the light emitted by the light source.

[0085] Based on multiple scattered light signals obtained from multiple detectors, the estimator 340 can select some of the obtained light signals and calculate the scattering coefficient using the selected light signals. For example, the estimator 340 can calculate the similarity between the multiple scattered light signals and can select light signals with a calculated similarity greater than or equal to a first threshold. Optionally, the estimator 340 can calculate the similarity between the multiple scattered light signals and can calculate the scattering coefficient using the remaining light signals after excluding light signals with a calculated similarity less than or equal to a second threshold. In this case, the similarity may include at least one of Euclidean distance, Pearson correlation coefficient, Spearman correlation coefficient, and cosine similarity.

[0086] Based on the calculated scattering coefficient, estimator 340 can obtain an estimated bioinformation value (e.g., triglyceride value) by using an estimation model that defines the correlation between the scattering coefficient and bioinformation (such as triglycerides). In this case, the estimation model may be represented in the form of a linear / nonlinear function or in the form of a matching table indicating the correlation between the scattering coefficient and the estimated bioinformation value, but this disclosure is not limited thereto. Figure 5B This illustrates the correlation between the values ​​on the left side of Equation 1 above and the distance, based on changes in triglyceride levels. (Example:) Figure 5B As shown, with blood triglycerides (in) Figure 5BAs the concentration of triglycerides (TG) changes, the scattering coefficient of the blood also changes, causing the scattered light signal to vary with the distance between the light source and the detector. As mentioned above, the estimation model can be predefined using the correlation between the scattering coefficient and triglyceride concentration.

[0087] Figure 6 This is a flowchart illustrating a method for estimating biological information according to an example embodiment. Figure 6 The method is based on Figure 1 or Figure 2 The example embodiments are examples of methods for estimating biological information performed by device 100 or 200 for estimating biological information.

[0088] Reference Figure 6 In operation 610, in response to a request to estimate biometric information, the device for estimating biometric information may drive a sensor unit based on a first sensor configuration to detect scattered light signals from the object. In this case, the device for estimating biometric information may control the driving of the sensor unit based on a predefined first sensor configuration. In this case, if the sensor unit includes a fingerprint sensor, the device for estimating biometric information may acquire a fingerprint image.

[0089] Then, in operation 620, the device for estimating biometric information can obtain contact information based on the amount of light received by each pixel and / or a fingerprint image, the amount of light being obtained by scanning the object in contact with the sensor unit based on the configuration of the first sensor. In this case, the contact information may include the contact area, the center point of the contact area, the center point of the fingerprint, the contact direction, etc.

[0090] Subsequently, in operation 630, the device for estimating biological information can determine a second sensor configuration based on the obtained contact information. In this case, the second sensor configuration may include information about the light source pixel and detector pixels disposed at different distances from the light source pixel, such that scattered light signals can be obtained at various locations spaced at different distances from the light source.

[0091] For example, a device for estimating biometric information may identify one or more pixels located at predetermined positions in the contact direction among the pixels in the contact area as light source pixels configured for a second sensor; and may identify all pixels, or pixels located within a predetermined range from the center point of the contact area or the center point of the fingerprint, as detector pixels configured for a second sensor.

[0092] In another example, the device for estimating biological information can map a predefined reference sensor configuration's reference region, reference orientation, and reference center point to a contact region, contact orientation, and the center point of the contact region. Based on this mapping, the device for estimating biological information can determine the pixels corresponding to the light source pixels and the pixels corresponding to the detector pixels in the reference sensor configuration as the light source pixels and detector pixels in the second sensor configuration, respectively.

[0093] Next, in operation 640, the device for estimating biological information can detect multiple scattered light signals by driving the sensor unit based on the second sensor configuration.

[0094] Then, in operation 650, the device for estimating biological information can estimate the biological information based on the light signal obtained according to the configuration of the second sensor. For example, the device for estimating biological information can calculate the scattering coefficient based on the light signal, and can estimate the biological information by using a predefined estimation model. In this case, if multiple light signals are obtained, the device for estimating biological information can calculate the similarity between the light signals, and can calculate the scattering coefficient by using only the light signals with a calculated similarity greater than or equal to a first threshold. Optionally, the device for estimating biological information can calculate the scattering coefficient by using the remaining light signals after excluding the light signals with a calculated similarity less than or equal to a second threshold.

[0095] Figure 7 This is a diagram illustrating an example of a wearable device. The aforementioned embodiments of devices 100 and 200 for estimating biometric information can be installed in the wearable device.

[0096] Reference Figure 7 The wearable device 700 includes a main body 710 and a strap 730.

[0097] The straps 730 connected to both ends of the body 710 can be flexible to wrap around the user's wrist. The straps 730 can consist of a first strap and a second strap, which are separate from each other. Each end of the first and second straps is connected to the body 710, and the other ends of the first and second straps can be connected to each other via a connecting device. In this case, the connecting device can be a magnetic connection, a Velcro connection, a pin connection, etc., but is not limited to these. Furthermore, the straps 730 are not limited to these and can be integrally formed as a non-removable strap.

[0098] In this case, air can be injected into the belt 730, or the belt 730 can be provided with an air bladder to be elastic according to changes in pressure applied to the wrist, and can transmit changes in wrist pressure to the body 710.

[0099] The battery can be embedded in the main body 710 or the band 730 to power the wearable device 700.

[0100] The main body 710 may include a sensor unit 720 mounted on one side of the main body 710. The sensor unit 720 may include a pixel array having multiple pixels, each pixel including a light source and a detector. In addition, the sensor unit 720 may also include a fingerprint sensor for acquiring a fingerprint image when a finger contacts the sensor unit 720.

[0101] The processor can be installed in the main body 710. The processor can be electrically connected to a module installed in the wearable device 700. The processor can estimate bio-information based on the light signal obtained by the sensor unit 720. In this case, by controlling the sensor unit 720 based on the first sensor configuration, the processor can scan an object and obtain contact information of the object. Furthermore, the processor can determine a second sensor configuration based on the contact information and can control the sensor unit 720 based on the determined second sensor configuration. As described above, based on the light signal obtained based on the second sensor configuration, the processor can obtain bio-information by calculating the scattering coefficient based on the obtained light signal.

[0102] In addition, the main body 710 may include a storage device for storing reference information for estimating biological information and information processed by various modules of the main body 710.

[0103] In addition, the main body 710 may include a manipulator 740 disposed on a side surface of the main body 710, which receives control commands from the user and sends the received control commands to a processor. The manipulator 740 may have a power button for inputting commands to turn the wearable device 700 on / off.

[0104] Furthermore, a display for outputting information to the user can be mounted on the front surface of the main body 710. The display may have a touchscreen for receiving touch input. The display can receive touch input from the user and send the touch input to the processor, and can display the processing results of the processor.

[0105] In addition, the main body 710 may include a communication interface for communicating with external devices. The communication interface may send bioinformatics estimation results to external devices (such as a user's smartphone).

[0106] Figure 8 This is a diagram illustrating an example of a smart device. In this case, the smart device may include a smartphone, a tablet PC, etc. The smart device may include the functionality of the aforementioned example embodiments of devices 100 and 200 for estimating biometric information.

[0107] Reference Figure 8 The smart device 800 includes a main body 810 and a sensor unit 830 mounted on a surface of the main body 810. For example, the sensor unit 830 may also include a fingerprint sensor.

[0108] Furthermore, a display can be mounted on the front surface of the main body 810. The display can visually output bioinformation estimation results, health status assessment results, etc. The display may include a touchscreen and can receive information input via the touchscreen and send the information to the processor.

[0109] like Figure 8 As shown, the main body 810 may include an image sensor 820. The image sensor 820 can capture various images and can acquire, for example, a fingerprint image of a finger that is in contact with the sensor section 830.

[0110] The processor can be installed in the main body 810 to be electrically connected to various modules of the main body 810, and can control the operation of the modules. The processor can control the sensor unit based on a first sensor configuration for obtaining contact information, and can obtain contact information based on the light signal obtained according to the first sensor configuration. Furthermore, the processor can adaptively determine a second sensor configuration based on the contact information, and can control the sensor unit according to the determined second sensor configuration. In this way, the processor can obtain the light signal at the contact location of the object, thereby improving the accuracy of estimating biometric information.

[0111] The example embodiments may be implemented by computer-readable code written on a non-transitory computer-readable medium and executed by a processor. The non-transitory computer-readable medium may be any type of recording device that stores data in a computer-readable manner.

[0112] Examples of computer-readable media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage devices, and carrier waves (e.g., data transmission over the Internet). Non-transitory computer-readable media can be distributed across multiple networked computer systems, allowing computer-readable code to be written to and executed from them in a distributed manner. Programmers skilled in the art to which this disclosure pertains can readily derive functional programs, code, and code segments for implementing the exemplary embodiments.

[0113] This disclosure has been described herein with reference to exemplary embodiments. However, it will be apparent to those skilled in the art that various changes and modifications can be made without altering the technical concept and features of this disclosure. Therefore, it is clear that the above exemplary embodiments are illustrative in all respects and are not intended to limit this disclosure.

Claims

1. A device for estimating biological information, the device comprising: The sensor unit includes a pixel array containing multiple pixels, each pixel including a light source and a detector; and The processor is configured as follows: The sensor unit is driven based on the contact between the object and the sensor unit, and based on the first sensor configuration. Contact information of an object is obtained based on the amount of light received by each pixel according to the configuration of the first sensor. The configuration of the second sensor is determined based on contact information. Drive the sensor unit based on the second sensor configuration, and Biological information is estimated based on the light signals obtained according to the configuration of the second sensor. The contact information includes at least one of the following: the contact area of ​​the object, the center point of the contact area, the center point of the fingerprint, and the contact direction. The processor is also configured to: determine the light source pixels and detector pixels of the second sensor configuration based on contact information. The processor is further configured to: map a reference region, reference direction, and reference center point of a predefined reference sensor configuration to a contact region, contact direction, and center point of the contact region; and based on the mapping, determine the pixel corresponding to the light source pixel of the predefined reference sensor configuration as the light source pixel of the second sensor configuration, and determine the pixel corresponding to the detector pixel of the predefined reference sensor configuration as the detector pixel of the second sensor configuration.

2. The device according to claim 1, wherein, The first sensor configuration includes at least one of the following: driving method, driving sequence, light source intensity, and duration, wherein the driving method includes at least one of time-division driving, sequential driving, and simultaneous driving.

3. The device according to claim 1, wherein, The processor is also configured as follows: Contact information is obtained based on at least one of the following: a pixel having a light quantity greater than or equal to a predetermined threshold, a pixel having a light quantity greater than or equal to a predetermined percentage of the average of the total light quantity, a pixel having a light quantity greater than or equal to a predetermined percentage of the maximum light quantity, and a pixel having a light quantity greater than or equal to a predetermined percentage of the average of the light quantities of "a plurality of pixels having light quantities falling within a predetermined percentage range of the maximum light quantity".

4. The device according to claim 1, wherein, The processor is also configured as follows: One or more pixels located at predetermined positions in the contact direction within the contact area are identified as light source pixels configured by the second sensor; and One or more pixels located within a predetermined range, including the center point of the contact area or the center point of the fingerprint, are identified as detector pixels of the second sensor configuration.

5. The device according to claim 1, wherein, The sensor unit is configured to acquire a fingerprint image based on contact between the object and the sensor unit, and The processor is also configured to obtain contact information based on fingerprint images.

6. The device according to claim 5, wherein, The processor is also configured to control the output interface to guide the user to place the object on the sensor unit based on the fact that the fingerprint center point is not within a predetermined area of ​​the sensor unit.

7. The device according to any one of claims 1 to 6, wherein, The processor is also configured as follows: The scattering coefficient is determined based on the optical signal obtained according to the configuration of the second sensor; and Estimating biological information based on scattering coefficients.

8. The device according to any one of claims 1 to 6, wherein, The processor is also configured as follows: Based on the optical signals obtained according to the configuration of the second sensor, the similarity between the optical signals is determined; and Light signals with a similarity greater than or equal to a first threshold are selected as light signals for estimating biological information.

9. The device according to any one of claims 1 to 6, wherein, The processor is also configured as follows: Based on the optical signals obtained according to the configuration of the second sensor, the similarity between the optical signals is determined; and The remaining light signals after excluding light signals with similarity less than or equal to the second threshold are selected as the light signals used to estimate biological information.

10. The device according to any one of claims 1 to 6, wherein, Bioinformation includes at least one of the following: triglycerides, body fat percentage, body water, blood glucose, cholesterol, carotenoids, protein, and uric acid.

11. A method for estimating biological information, the method comprising: The sensor unit is driven based on the contact between the object and the sensor unit, and based on the first sensor configuration. Contact information of an object is obtained based on the amount of light received by each pixel of the sensor unit according to the configuration of the first sensor. The configuration of the second sensor is determined based on contact information; The sensor unit is driven based on the second sensor configuration; and Biological information is estimated based on the light signals obtained according to the configuration of the second sensor. The step of obtaining contact information includes obtaining contact information including at least one of the following: the contact area of ​​the object, the center point of the contact area, the center point of the fingerprint, and the contact direction. The step of determining the configuration of the second sensor includes: determining the light source pixels and detector pixels of the second sensor configuration based on contact information. The step of determining the second sensor configuration includes: mapping the reference area, reference direction, and reference center point of the predefined reference sensor configuration to the contact area, contact direction, and center point of the contact area; and based on the mapping, determining the pixel corresponding to the light source pixel of the predefined reference sensor configuration as the light source pixel of the second sensor configuration, and determining the pixel corresponding to the detector pixel of the predefined reference sensor configuration as the detector pixel of the second sensor configuration.

12. The method according to claim 11, wherein, The steps to obtain contact information include: Contact information is obtained based on at least one of the following: a pixel having a light quantity greater than or equal to a predetermined threshold, a pixel having a light quantity greater than or equal to a predetermined percentage of the average of the total light quantity, a pixel having a light quantity greater than or equal to a predetermined percentage of the maximum light quantity, and a pixel having a light quantity greater than or equal to a predetermined percentage of the average of the light quantities of "a plurality of pixels having light quantities falling within a predetermined percentage range of the maximum light quantity".

13. The method according to claim 11, wherein, The steps for determining the configuration of the second sensor include: One or more pixels located at predetermined positions in the contact direction within the contact area are identified as light source pixels configured by the second sensor; and One or more pixels located within a predetermined range, including the center point of the contact area or the center point of the fingerprint, are identified as detector pixels of the second sensor configuration.

14. The method of claim 11, further comprising: Fingerprint images are obtained based on the contact between the object and the sensor. The steps for obtaining contact information include: obtaining contact information based on fingerprint images.

15. The method of claim 14, further comprising: Since the fingerprint center point is not within the predetermined area of ​​the sensor unit, the control output interface guides the user to place the object on the sensor unit.

16. The method according to any one of claims 11 to 15, wherein, The steps for estimating bioinformatics include: The scattering coefficient is determined based on two or more optical signals obtained through the sensor unit; and Estimating biological information based on scattering coefficients.

17. The method according to any one of claims 11 to 15, wherein, The steps for estimating bioinformatics include: Based on the optical signals obtained through the sensor unit, the similarity between the optical signals is determined; and Light signals with a similarity greater than or equal to a first threshold are selected as light signals for estimating biological information.

18. The method according to any one of claims 11 to 15, wherein, The steps for estimating bioinformatics include: Based on the optical signals obtained through the sensor unit, the similarity between the optical signals is determined; and The remaining light signals after excluding light signals with similarity less than or equal to the second threshold are selected as the light signals used to estimate biological information.

19. A method for estimating a user's biometric information, the method comprising: Based on the first sensor configuration, drive the first light source pixel and the first group of detector pixels of the sensor's pixel array; Based on the driving first light source pixel and the first group of detector pixels, the contact area of ​​the pixel array that comes into contact with the user's object is identified; The configuration of the second sensor is determined based on the contact area; Based on the second sensor configuration, drive the second light source pixel and the second group of detector pixels of the sensor's pixel array; The light signal is obtained by driving the second light source pixel and the second group of detector pixels; and Estimating user biometric information based on optical signals The step of determining the second sensor configuration includes: mapping the reference area, reference direction, and reference center point of the predefined reference sensor configuration to the contact area, contact direction, and center point of the contact area; and based on the mapping, determining the pixel corresponding to the light source pixel of the predefined reference sensor configuration as the second light source pixel of the second sensor configuration, and determining the pixel corresponding to the detector pixel of the predefined reference sensor configuration as the second set of detector pixels of the second sensor configuration.

20. A computer-readable storage medium storing instructions, which, when executed by a processor, configure the processor to perform the method according to any one of claims 11 to 19.

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