Apparatus for estimating biological information

Abstract

Disclosed is an apparatus for estimating biological information. An apparatus for estimating biological information of a user includes a pulse wave sensor configured to measure a plurality of pulse wave signals from an object of the user, a position sensor configured to obtain sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on the pulse wave sensor measuring each of the plurality of pulse wave signals, and a processor configured to estimate a first biological information at each sensor position based on each of the plurality of pulse wave signals, and estimate a second biological information based on a blood vessel position of the object, each sensor position, and the biological information at each sensor position.

Description

[0001] This application is based on and claims priority to Korean Patent Application No. 10-2020-0091509, filed on July 23, 2020, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The disclosure relates to an apparatus and method for estimating biological information, and a technology for cuffless blood pressure estimation. BACKGROUND

[0003] A general technology for extracting cardiovascular characteristics such as blood pressure without using a pressure cuff includes a pulse transit time (PTT) method and a pulse wave analysis (PWA) method.

[0004] The pulse transit time (PTT) method is a method of extracting cardiovascular characteristics by analyzing the shape of a photoplethysmography (PPG) signal or a body surface pressure signal from a peripheral part of the body such as a fingertip, a radial artery, etc. Blood ejected from the left ventricle causes a reflection in the region of large branches such as the renal artery and the iliac artery, and the reflection affects the shape of a pulse wave or a body pressure wave measured at the peripheral part of the body. Thus, by analyzing this shape, arterial stiffness, arterial age, aortic pressure waveform, etc. can be inferred.

[0005] The pulse wave velocity (PWV) method is a method of extracting cardiovascular characteristics such as arterial stiffness, blood pressure, etc. by measuring a pulse wave transmission time. In this method, a delay between an R-peak of an electrocardiogram (ECG) (left ventricular contraction interval) and a peak of a PPG signal of a finger or a radial artery (pulse transit time (PTT)) is measured by measuring an ECG and a PPG signal of a peripheral part of the body and calculating the velocity of blood from the heart to reach the peripheral part of the body by dividing the approximate length of the arm by the PTT. SUMMARY

[0006] According to an aspect of an example embodiment, an apparatus for estimating biological information of a user includes a pulse wave sensor configured to measure a plurality of pulse wave signals from an object of the user, a position sensor configured to obtain sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on the pulse wave sensor measuring each of the plurality of pulse wave signals, and a processor configured to estimate first biological information at each sensor position based on each of the plurality of pulse wave signals, and estimate second biological information based on a blood vessel position of the object, each sensor position, and the first biological information at each sensor position.

[0007] Based on the object being in contact with the pulse wave sensor, the position sensor is further configured to obtain sensor position information based on an image of the object captured by an external capturing device.

[0008] The position sensor may include a fingerprint sensor configured to obtain a fingerprint image, and the position sensor is further configured to obtain sensor position information based on the fingerprint image obtained by the fingerprint sensor according to contact of the object with the pulse wave sensor.

[0009] Based on the object being in contact with the pulse wave sensor, the position sensor is further configured to obtain sensor position information based on predefined measured position information of the pulse wave sensor.

[0010] The apparatus may include a blood vessel position sensor configured to obtain blood vessel position information of the object based on at least one of an optical image, an ultrasound image, a magnetic resonance imaging (MRI) image, and a photoacoustic image of the object obtained by an external device.

[0011] The apparatus may include a blood vessel position sensor including an ultrasonic sensor configured to transmit ultrasonic waves to a subject and receive signals reflected from the subject, and obtain blood vessel position information of the subject based on an ultrasonic image obtained by the ultrasonic sensor.

[0012] The processor is further configured to generate a calibration map by plotting the estimated bio-information value at each sensor position relative to the relative distance of each sensor position from the blood vessel position of the subject and based on performing curve fitting, and obtain a final estimated bio-information value based on the calibration map.

[0013] The processor is further configured to obtain a bio-information value of a point corresponding to a position of a blood vessel of the subject in the calibration map as second bio-information.

[0014] The apparatus may include a force sensor configured to measure a force applied by the subject to the pulse wave sensor; or a pressure sensor configured to measure a pressure applied by the subject to the pulse wave sensor.

[0015] The processor is further configured to generate an oscillogram based on each pulse wave signal of the plurality of pulse signals and the force measured by the force sensor or the pressure measured by the pressure sensor, and estimate first bio-information at each sensor position by using the oscillogram.

[0016] The biological information includes one or more of the following: blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, pressure index, fatigue level, skin age, and skin elasticity.

[0017] A method for estimating biometric information of a user may include: measuring multiple pulse wave signals from a subject; obtaining sensor position information identifying a sensor position on the subject for each of the multiple pulse wave signals based on a pulse wave sensor measuring each of the multiple pulse wave signals; estimating first biometric information at each sensor position based on each of the multiple pulse wave signals; and estimating second biometric information based on a blood vessel position of the subject, each sensor position, and the first biometric information at each sensor position.

[0018] The step of estimating the second bio-information includes generating a calibration graph by plotting the first estimated bio-information value at each sensor position relative to the relative distance of each sensor position from the blood vessel position of the object, and by performing curve fitting, and obtaining the second estimated bio-information value based on the calibration graph.

[0019] The step of estimating the second biological information includes obtaining a biological information value of a point corresponding to a blood vessel position of the subject in the calibration map as a second estimated biological information value.

[0020] The method may include measuring a force or pressure applied by the subject to the pulse wave sensor.

[0021] The estimating of the first bio-information at each sensor location may include generating an oscillogram based on each of the plurality of pulse wave signals and force or pressure, and estimating the first bio-information at each sensor location by using the oscillogram.

[0022] According to an aspect of an example embodiment, an apparatus for estimating bio-information of a user may include: a pulse wave sensor configured to measure a plurality of pulse wave signals from an object of the user; a position sensor configured to obtain sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on the pulse wave sensor measuring each of the plurality of pulse wave signals; and a processor configured to estimate first bio-information at each sensor position based on each of the plurality of pulse wave signals; determine one of a plurality of virtual blood vessel positions as a blood vessel position of the object based on the first bio-information at each sensor position, and estimate second bio-information based on the blood vessel position of the object, each sensor position, and the first bio-information at each sensor position.

[0023] Based on a difference between the first bio-information values ​​at each sensor position, the processor is configured to determine one virtual blood vessel position among the plurality of virtual blood vessel positions as the blood vessel position of the subject.

[0024] The virtual blood vessel position is set for each of a plurality of groups pre-classified based on a difference between first biological information values at each sensor position obtained from a plurality of users.

[0025] The processor is further configured to determine a group to which the difference belongs among the plurality of groups, and determine a virtual blood vessel position pre-defined for the determined group as the blood vessel position of the object.

[0026] The processor is further configured to generate a calibration graph by plotting the first biological information values at each sensor position with respect to a relative distance from the blood vessel position of the object, and obtain the second biological information value based on the calibration graph.

[0027] The processor is further configured to obtain a biological information value of a point corresponding to the blood vessel position of the object in the calibration graph as the second biological information value.

[0028] The device can include a force sensor configured to measure a force applied by the object to the pulse wave sensor, or a pressure sensor configured to measure a pressure applied by the object to the pulse wave sensor.

[0029] The processor can generate an oscillogram based on each of the plurality of pulse wave signals and the force or pressure measured by the force sensor or the pressure sensor, and estimate the first biological information at each sensor position by using the oscillogram.

[0030] A method of estimating biological information of a user can include measuring a plurality of pulse wave signals from an object of the user, obtaining sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on a pulse wave sensor measuring each of the plurality of pulse wave signals, estimating first biological information at each sensor position based on each of the plurality of pulse wave signals, determining one of a plurality of virtual blood vessel positions as a blood vessel position of the object based on the first biological information at each sensor position, and estimating second biological information based on the blood vessel position of the object, each sensor position, and the first biological information at each sensor position.

[0031] The determining of one of the plurality of virtual blood vessel positions as the blood vessel position of the object includes determining one of the plurality of virtual blood vessel positions as the blood vessel position of the object based on a difference between the first biological information values at each sensor position.

[0032] The determining of one of the plurality of virtual blood vessel positions as the blood vessel position of the object includes determining a group to which the difference belongs among a plurality of groups, and determining a virtual blood vessel position pre-defined for the determined group as the blood vessel position of the object.

[0033] The step of estimating the second bio-information includes generating a calibration map by plotting the first bio-information value at each sensor position with respect to the relative distance of each sensor position from the determined blood vessel position of the subject, and obtaining the second bio-information value based on the calibration map.

[0034] The method may include measuring a force or pressure applied by the subject to the pulse wave sensor.

[0035] The step of estimating the first bio-information at each sensor position includes: generating an oscillogram based on each pulse wave signal and the force or pressure; and estimating the first bio-information at each sensor position by using the oscillogram. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The above and other aspects, features and advantages of certain embodiments of the present disclosure will become more apparent from the following description taken in conjunction with the accompanying drawings, in which:

[0037] Figures 1 to 3 is a block diagram illustrating an apparatus for estimating bio-information according to an embodiment of the present disclosure;

[0038] Figure 4 yes Figures 1 to 3 An example of a configuration of a processor of an apparatus for estimating biological information shown in ;

[0039] Figure 5A and Figure 5B is a diagram explaining an example of estimating blood pressure using the oscillometric method;

[0040] Figure 6A and Figure 6B is a diagram explaining an example of calibrating blood pressure based on the position of blood vessels of a subject;

[0041] Figure 7 is a block diagram illustrating an apparatus for estimating bio-information according to another embodiment of the present disclosure;

[0042] Figure 8 It shows Figure 7 A diagram illustrating an example of a configuration of a processor;

[0043] Figures 9A to 9C is a diagram explaining an example of calibrating blood pressure based on a virtual blood vessel position;

[0044] Figure 10 is a block diagram illustrating an apparatus for estimating bio-information according to yet another embodiment of the present disclosure;

[0045] Figure 11 is a flowchart illustrating a method of estimating biological information according to an embodiment of the present disclosure;

[0046] Figure 12 is a flowchart illustrating a method of estimating biological information according to another embodiment of the present disclosure;

[0047] Figure 13 is a diagram illustrating an example of a wearable device;

[0048] Figure 14 is a diagram illustrating an example of a smart device. DETAILED DESCRIPTION

[0049] Details of example embodiments are included in the following detailed description and accompanying drawings. The advantages and features of the present disclosure and methods of implementing the present disclosure will be more clearly understood from the following detailed description of the embodiments with reference to the accompanying drawings. Throughout the drawings and detailed description, unless otherwise indicated, the same reference numerals will be understood to represent the same elements, features, and structures.

[0050] 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 to distinguish one element from another. In addition, unless otherwise clearly indicated, the singular form of a term is also intended to include the plural form of the term. It will also be understood that, unless explicitly described to the contrary, when an element is referred to as "comprising" another element, the element is not intended to exclude one or more other elements, but rather further include one or more other elements. In the following description, terms such as "unit" or "module" indicate a unit for processing at least one function or operation and the unit can be implemented using hardware, software, or a combination thereof.

[0051] Hereinafter, embodiments of an apparatus and method for estimating bio-information will be described in detail with reference to the accompanying drawings.

[0052] Various embodiments of the apparatus for estimating biometric information may be installed in a terminal (such as a smartphone, a tablet personal computer (PC), a desktop computer, a laptop computer, etc.) and a wearable device, etc. In this case, examples of the wearable device may include a smartwatch-type wearable device, a bracelet-type wearable device, a wristband-type wearable device, a ring-type wearable device, a glasses-type wearable device, or a headband-type wearable device, etc., but the wearable device is not limited thereto.

[0053] Figures 1 to 3 is a block diagram illustrating an apparatus for estimating bio-information according to an embodiment of the present disclosure.

[0054] Reference Figure 1 , an apparatus 100 for estimating biological information includes a pulse wave sensor 110 , a position sensor 120 , and a processor 130 .

[0055] The pulse wave sensor 110 measures a photoplethysmography (PPG) signal (hereinafter referred to as a "pulse wave signal") from a subject. In other words, the pulse wave sensor 110 can obtain the subject's pulse wave signal. In this case, the subject can be a body region that can be in contact with the pulse wave sensor 110, and can be a body part where the pulse wave can be easily measured based on the PPG signal. For example, the subject can be a finger where blood vessels are densely located, but the subject is not limited thereto and can be an area on the wrist adjacent to the radial artery, or a distal part of the body where veins or capillaries are located (such as the upper part of the wrist, toes, etc.).

[0056] The pulse wave sensor 110 may include one or more light sources for emitting light onto an object, and one or more light receivers disposed at a predetermined distance from the light sources and detecting light scattered or reflected from the object. The light source may emit light of different wavelengths. For example, the light source may emit light of infrared wavelengths, green wavelengths, blue wavelengths, red wavelengths, white wavelengths, and the like. The light source may include, but is not limited to, a light emitting diode (LED), a laser diode (LD), a phosphor, and the like. Furthermore, the light receiver may include a photodiode, a photodiode array, a complementary metal oxide semiconductor (CMOS) image sensor (CIS), a charge coupled device (CCD) image sensor, and the like.

[0057] The pulse wave sensor 110 may have a single channel including a light source and a light receiver to measure a pulse wave signal at a specific point on the subject. Alternatively, the pulse wave sensor 110 may have multiple channels to measure multiple pulse wave signals at multiple points on the subject. Each channel of the pulse wave sensor 110 may be formed in a predefined shape (such as a circle, an ellipse, a sector, etc.) so that the pulse wave signal can be measured at multiple points on the subject. Each channel of the pulse wave sensor 110 may include one or more light sources and one or more light receivers. In addition, each channel may include two or more light sources to emit light of multiple wavelengths. Alternatively, the pulse wave sensor 110 may be configured to measure multiple pulse wave signals in a predetermined area of ​​the subject. For example, the pulse wave sensor 110 may include one or more light sources and a light receiver formed as a CIS and disposed at a predetermined distance from the one or more light sources.

[0058] The position sensor 120 may obtain sensor position information (such as position information about the contact of the object with the pulse wave sensor 110 ) when the object is in contact with the pulse wave sensor 110 . At least some functions of the position sensor 120 may be integrated with the processor 130 .

[0059] For example, the position sensor 120 may obtain sensor position information based on an image of the object captured by an external image capturing device. The external image capturing device may be a camera module installed in a fixed location or a camera module installed in a mobile device (such as a smartphone). For example, once the external image capturing device captures an image of the object in contact with the pulse wave sensor 110, the position sensor 120 may receive the image of the object through a communication interface installed in the apparatus 100 for estimating biological information.

[0060] By analyzing the relative position of the pulse wave sensor 110 and the object based on the image of the object, the position sensor 120 can obtain the position of the object in contact with the pulse wave sensor 110 as the sensor position. In addition, if an external image capturing device having a function of obtaining a sensor position obtains sensor position information by capturing an image of the object, the position sensor 120 can receive the sensor position information through the communication interface.

[0061] In another example, the position sensor 120 may include a fingerprint sensor for obtaining a fingerprint image of the object in contact with the pulse wave sensor 110. The fingerprint sensor may be provided at the upper or lower end of the pulse wave sensor 110. The position sensor 120 may estimate the sensor position by analyzing changes in the fingerprint pattern based on the fingerprint image of the object. For example, when a finger applies pressure to the pulse wave sensor 110, the contact position of the finger in contact with the pulse wave sensor 110 is pressed against the pulse wave sensor 110 to a greater extent than other positions of the finger, resulting in a greater distance between the ridges or valleys of the fingerprint at the contact position between the finger and the pulse wave sensor 110 than at other positions. If the distance between the ridges or valleys of the fingerprint at the finger position is greater than or equal to a predetermined threshold value when compared to other positions, the position sensor 120 may obtain that position as the sensor position.

[0062] In yet another example, when the pulse wave sensor 110 has multiple channels to simultaneously measure multiple pulse wave signals, the position sensor 120 may obtain a preset measurement position for each pulse wave signal as the sensor position. In one example, based on contact between the object and the pulse wave sensor, the position sensor 120 may obtain each sensor position information based on predefined measurement position information of the pulse wave sensor.

[0063] The processor 130 may be electrically connected to the pulse wave sensor 110 and may control the pulse wave sensor 110 in response to a request for estimating biological information. The processor 130 may control the pulse wave sensor 110 to obtain pulse wave signals at multiple measurement locations of the subject. In this case, if the pulse wave sensor 110 has a single channel including one light source and one receiver, the processor 130 may control the pulse wave sensor 110 multiple times to obtain pulse wave signals at multiple locations of the subject.

[0064] Processor 130 may estimate biometric information based on multiple pulse wave signals obtained at multiple sensor locations on the subject. Furthermore, processor 130 may obtain final biometric information based on the biometric information obtained at each sensor location, each sensor location information, and the subject's vascular location information. Biometric information may include one or more of the following: blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, pressure index, fatigue level, skin age, and skin elasticity.

[0065] Reference Figure 2 , an apparatus 200 for estimating bio-information according to another embodiment includes a pulse wave sensor 110, a position sensor 120, a processor 130, and a force / pressure sensor 210. Redundant descriptions of the position sensor 120 and the processor 130 will be omitted.

[0066] When a user places an object on the pulse wave sensor 110 and increases or decreases the pressing force / pressure to cause a change in the pulse wave amplitude, the force / pressure sensor 210 can measure the force / pressure applied between the pulse wave sensor 110 and the object. The force / pressure sensor 210 may include a force sensor (including a strain gauge, etc.), a force sensor array, a balloon-type pressure sensor, a pressure sensor combined with a force sensor and an area sensor, etc.

[0067] Processor 130 can estimate biometric information at each sensor location based on the pulse wave signals obtained by pulse wave sensor 110 at multiple sensor locations and the force / pressure obtained by force / pressure sensor 210. In this case, once force / pressure sensor 210 obtains the contact force between the object and pulse wave sensor 110, processor 130 can convert the contact force into contact pressure using a conversion model that defines the correlation between contact force and contact pressure. Alternatively, processor 130 can obtain contact pressure using contact force and area information from pulse wave sensor 110. Furthermore, if force / pressure sensor 210 is implemented as a force sensor for measuring contact force and an area sensor for measuring contact area, processor 130 can obtain contact pressure based on the contact force measured by the force sensor and the contact area measured by the area sensor.

[0068] Reference Figure 3According to another embodiment, the apparatus 300 for estimating bio-information includes a pulse wave sensor 110, a position sensor 120, a processor 130, and a blood vessel position sensor 310. The pulse wave sensor 110, the position sensor 120, and the processor 130 are described above in detail, and thus redundant descriptions thereof will be omitted. Figure 2 The force / pressure sensor 210 may be included in the apparatus 300 for estimating bio-information according to an embodiment of the present disclosure.

[0069] The blood vessel position sensor 310 can obtain the subject's blood vessel position information when the user registers. Alternatively, in response to a user's request to estimate biometric information, the blood vessel position sensor 310 can check whether the user's subject's blood vessel position information exists or whether it is time to calibrate the information. If the subject's blood vessel position information does not exist or it is time to calibrate the information, the blood vessel position sensor 310 can obtain the subject's blood vessel position information from the user. At least some functions of the blood vessel position sensor 310 can be integrated with the processor 130. Examples of obtaining blood vessel positions by the blood vessel position sensor 310 will be described below, but the present disclosure is not limited to these examples.

[0070] For example, the blood vessel position sensor 310 may directly receive an input of blood vessel position information from a user. In this case, the blood vessel position sensor 310 may display an image of the object on a display and may provide an interface for the user to directly specify the blood vessel position on the object image using an input device (e.g., a finger, a touch pen, etc.).

[0071] In another example, the blood vessel position sensor 310 may receive an image captured by an external image capturing device for capturing optical images, ultrasound images, magnetic resonance imaging (MRI) images, photoacoustic images, etc., through a communication interface, and may obtain blood vessel position information of the subject by analyzing the received image. Alternatively, if the external image capturing device analyzes the blood vessel position while capturing the image, the blood vessel position sensor 310 may receive the blood vessel position information of the subject through the communication interface.

[0072] In another example, the blood vessel position sensor 310 may include, for example, an ultrasonic sensor that transmits ultrasonic waves to an object and receives reflected waves from the object. The blood vessel position sensor 310 may obtain blood vessel position information based on an ultrasonic image obtained by the ultrasonic sensor.

[0073] Figure 4 yes Figures 1 to 3 An example of the configuration of a processor of an apparatus for estimating biological information shown in . Figure 5A and Figure 5B is a diagram explaining an example of estimating blood pressure using the oscillometric method. Figure 6A and Figure 6Bis a diagram explaining an example of calibrating blood pressure based on the position of a blood vessel of a subject.

[0074] Reference Figure 4 , the processor 400 according to an embodiment of the present disclosure includes an oscillogram generator 410 , a bio-information estimator 420 , and a bio-information calibrator 430 .

[0075] The oscillogram generator 410 may generate an oscillogram for each sensor position based on the pulse wave signal and the contact pressure measured by the pulse wave sensor 110 at each sensor position.

[0076] For example, refer to Figure 5A and Figure 5B The oscillogram generator 410 may extract, for example, the peak-to-peak point of the pulse wave signal waveform by subtracting the negative (-) amplitude value in3 from the positive (+) amplitude value in2 of the waveform envelope in1 of the pulse wave signal at each measurement time, and may obtain an oscillogram (OW) by plotting the peak-to-peak amplitude at each measurement time relative to the contact pressure value at the corresponding time (i.e., with the contact pressure value at the corresponding time as the abscissa and the peak-to-peak amplitude at each measurement time as the ordinate) and by performing polynomial curve fitting.

[0077] The biometric information estimator 420 may extract characteristic points from the oscillogram for each sensor position and estimate the biometric information for each sensor position using the extracted characteristic points. For example, the biometric information estimator 420 may extract, as characteristic points, a contact pressure value MP at a point corresponding to a maximum amplitude value, contact pressure values ​​DP and SP at points corresponding to amplitude values ​​having a preset ratio (e.g., 0.5 to 0.7) to the maximum amplitude value MA, and the like.

[0078] The bio-information estimator 420 may determine, for example, the contact pressure value MP at the point corresponding to the maximum amplitude value as the mean arterial pressure (MAP), and may determine the contact pressure value DP at the left point and the contact pressure value SP at the right point corresponding to the amplitude value having a preset ratio with respect to the maximum amplitude value as the diastolic blood pressure (DBP) and the systolic blood pressure (SBP), respectively. Alternatively, the bio-information estimator 420 may independently estimate the MAP, DBP, and SBP by applying each of the extracted contact pressure values ​​MP, DP, and SP to a predefined blood pressure estimation model. In this case, the blood pressure estimation model may be expressed in the form of various linear or nonlinear combination functions (such as addition, subtraction, division, multiplication, logarithmic values, regression equations, etc.), without particular limitation.

[0079] The biometric information calibrator 430 can obtain final biometric information based on the biometric information generated by the biometric information estimator 420 for each sensor position. For example, the biometric information calibrator 430 can generate a calibration graph by plotting the estimated biometric information value for each sensor position relative to the relative distance of each sensor position from the subject's blood vessel position (i.e., with the relative distance of each sensor position from the subject's blood vessel position as the horizontal axis and the estimated biometric information value for each sensor position as the vertical axis) and fitting the curve. Furthermore, the biometric information calibrator 430 can obtain final estimated biometric information values ​​based on the generated calibration graph.

[0080] Figure 6A In (1), an example is shown in which the first sensor position L1 is the fingernail tip, the second sensor position L2 is located 4 mm from the first sensor position L1, and the blood vessel 61 a of the finger 60 is located between the first sensor position L1 and the second sensor position L2. In this case, the relative distance between the first sensor position L1 and the second sensor position L2 and the blood vessel position 61 a is 2 mm.

[0081] Reference Figure 6B (1), the bio-information calibrator 430 may locate the blood vessel position 61a at "0" on the X-axis, and then may plot the estimated blood pressure value of the first sensor position L1 at a distance of "-2" and "+2" from "0" on the X-axis, and may plot the estimated blood pressure value of the second sensor position L2 at a distance of "-2" and "+2" from "0" on the X-axis. Then, when plotting the estimated blood pressure values ​​of the first sensor position L1 and the second sensor position L2, the bio-information calibrator 430 may perform curve fitting to generate a calibration graph 62a of, for example, a quadratic function. In this case, various known curve fitting techniques may be used to perform curve fitting. When generating the calibration graph 62a, the bio-information estimator 420 may obtain the blood pressure value at the blood vessel position (i.e., the point 63a corresponding to "0" on the X-axis in the calibration graph 62a) as the final blood pressure value.

[0082] Figure 6A In (2), an example is shown in which the blood vessel 61b of the finger 60 is located 6 mm from the first sensor position L1 and 2 mm from the second sensor position L2. In this case, the relative distance between the first sensor position L1 and the blood vessel position 61b is 6 mm, and the relative distance between the second sensor position L2 and the blood vessel position 61b is 2 mm. Figure 6BAs shown in (2), the bio-information calibrator 430 may locate the blood vessel position 61b at "0" on the X-axis, and then may plot the estimated blood pressure value at the first sensor position L1 at a distance of "-6" and "+6" from "0" on the X-axis, and may plot the estimated blood pressure value at the second sensor position L2 at a distance of "+2" and "-2" from "0" on the X-axis. The bio-information calibrator 430 may then perform curve fitting to generate a calibration graph 62b showing a relatively smooth curve. In this case, the bio-information estimator 420 may obtain the blood pressure value at the blood vessel position (i.e., point 63b corresponding to "0" on the X-axis in the calibration graph 62b) as the final blood pressure value.

[0083] Figure 6A In (3), an example is shown in which the blood vessel 61c of the finger 60 is superimposed on the first sensor position L1, the relative distance between the first sensor position L1 and the blood vessel position 61c is 0 mm, and the relative distance between the second sensor position L2 and the blood vessel position 61c is 4 mm. Figure 6B As shown in (3), the bio-information calibrator 430 may generate a calibration graph 62c by plotting the estimated blood pressure value at the first sensor position L1 at "0" on the X-axis and the estimated blood pressure values ​​at the second sensor position L2 at distances "+4" and "-4" from "0" on the X-axis, and performing curve fitting. In this case, the bio-information estimator 420 may obtain the blood pressure value at the blood vessel position (i.e., point 63c corresponding to "0" on the X-axis in the calibration graph 62c) as the final blood pressure value.

[0084] Figure 7 is a block diagram illustrating an apparatus for estimating bio-information according to another embodiment of the present disclosure. Figure 8 It shows Figure 7 A diagram of an example of a configuration of a processor. Figures 9A to 9C is a diagram explaining an example of calibrating blood pressure based on virtual blood vessel positions.

[0085] Reference Figure 7 , an apparatus 700 for estimating bio-information according to another embodiment includes a pulse wave sensor 710, a position sensor 720, a processor 730, and virtual blood vessel position information 740. The embodiments of the pulse wave sensor 710 and the position sensor 720 are described above in detail.

[0086] Once pulse wave signals are obtained at a plurality of locations of the subject, the processor 730 may obtain final bio-information based on predefined virtual blood vessel location information 740 .

[0087] The virtual blood vessel position information 740 may be obtained from multiple users via an external device or the apparatus 700 for estimating bio-information. The virtual blood vessel position information 740 may be pre-stored in a storage device of the apparatus 700 for estimating bio-information. The virtual blood vessel position information 740 may include multiple virtual blood vessel positions for each subject. In this case, one virtual blood vessel position may be set for each of multiple groups classified according to predetermined criteria.

[0088] For example, reference Figure 9A As described above, by measuring the pulse wave signal at each of the first sensor position L1 and the second sensor position L2 of the user's finger 90, and by moving the virtual blood vessel position from position 1 to position 8, a calibration map can be generated for each virtual blood vessel position, and a final blood pressure value can be estimated. By using the data remaining after excluding abnormal data based on the generated calibration map or the estimated final blood pressure value, it is possible to Figure 9B For example, Figure 9B As shown in , a plurality of groups may be classified based on the difference between the estimated blood pressure at the first sensor location L1 and the estimated blood pressure at the second sensor location L2. However, the example of classifying the groups is not limited thereto, and the groups may be classified by various linear / nonlinear combinations (including the ratio between the estimated blood pressure at the first sensor location L1 and the estimated blood pressure at the second sensor location L2).

[0089] refer to Figure 9C , a virtual blood vessel position can be defined for each group. For example, in group 1, the estimated pressure value at the second sensor position L2 is much greater than the estimated pressure value at the first sensor position L1, so position (a) superimposed on second sensor position L2 can be defined as the virtual blood vessel position for group 1. In this way, position (b) of the object can be defined as the virtual blood vessel position for group 2, position (c) can be defined as the virtual blood vessel position for group 3, and position (d) can be defined as the virtual blood vessel position for groups 4 and 5.

[0090] Reference Figure 8 , the processor 800 according to an embodiment includes an oscillogram generator 810 , a bio-information estimator 820 , a blood vessel position determiner 830 , and a bio-information calibrator 840 .

[0091] The oscillogram generator 810 may generate an oscillogram for each sensor position based on the pulse wave signal and the contact pressure measured by the pulse wave sensor 710 at each sensor position.

[0092] The bio-information estimator 820 may extract characteristic points from the oscillogram OW for each sensor position, and may estimate bio-information for each sensor position by using the extracted characteristic points.

[0093] The blood vessel position determiner 830 may determine the optimal blood vessel position among multiple virtual blood vessel positions based on the virtual blood vessel position information 740 and the biometric information for each sensor position. For example, the blood vessel position determiner 830 may calculate the difference between the estimated blood pressure at the first sensor position L1 and the estimated blood pressure at the second sensor position L2 as a predefined group classification criterion and determine the group to which the calculated difference belongs. Furthermore, based on the virtual blood vessel position information 740, the blood vessel position determiner 830 may determine the virtual blood vessel position corresponding to the determined group as the optimal (or improved) blood vessel position for the user subject.

[0094] Once the blood vessel position determiner 830 determines the optimal blood vessel position of the object, the bio-information calibrator 840 can generate a calibration map based on the relative distance between the optimal blood vessel position and each of the first sensor position L1 and the second sensor position L2 as described above, and can obtain an estimated value corresponding to the blood vessel position in the calibration map as final bio-information.

[0095] According to this embodiment, even when accurate blood vessel information cannot be obtained from the user's subject, biological information can be accurately estimated, and since a separate sensor is not required, the device can be manufactured in a compact size.

[0096] Figure 10 is a block diagram illustrating an apparatus for estimating biological information according to still another embodiment of the present disclosure.

[0097] Reference Figure 10 , an apparatus 1000 for estimating bio-information according to another embodiment includes a pulse wave sensor 1010, a position sensor 1020, a force / pressure sensor 1040, a processor 1030, a storage device 1050, an output interface 1060, and a communication interface 1070. Various embodiments of the pulse wave sensor 1010, the position sensor 1020, the force / pressure sensor 1040, and the processor 1030 are described above in detail, so that redundant descriptions thereof will be omitted.

[0098] The storage device 1050 can store various information necessary for estimating biometric information. For example, the storage device 1050 can store pulse wave signals measured by the pulse wave sensor 1010, object images, fingerprint images, and sensor position information obtained by the position sensor 1020, and force / pressure values ​​obtained by the force / pressure sensor 1040. Furthermore, the storage device 1050 can store processing results from the processor 1030 (such as estimated biometric information values ​​for each sensor position, calibration charts, and final estimated biometric information values). Furthermore, the storage device 1050 can store blood vessel position information of a user's object, as well as user characteristic information (such as the user's age, gender, and health status). Furthermore, the storage device 1050 can store virtual blood vessel position information, etc. However, the information is not limited to this.

[0099] The storage device 1050 may include at least one storage medium selected from the group consisting of a flash memory, a hard disk memory, a multimedia card micro memory, a card-type memory (e.g., a secure digital (SD) memory, an extreme digital (XD) memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk, but is not limited thereto.

[0100] The output interface 1060 may output the pulse wave signal measured by the pulse wave sensor 1010, the object image, fingerprint image and sensor position information obtained by the position sensor 1020, the force / pressure value obtained by the force / pressure sensor 1040, and / or the processing result of the processor 1030. In this case, the output interface 1060 may provide information by a non-visual method using a speaker, a tactile device, or the like, along with the visual display of the information on the display.

[0101] For example, the output interface 1060 can output the measured pulse wave signal in the form of a graph. Furthermore, the output interface 1060 can visually display the estimated user's blood pressure value using various visual methods (such as by changing the color, line thickness, font, etc. based on whether the estimated blood pressure value falls within or outside the normal range). Optionally, when comparing the estimated blood pressure value with a previous estimation history, if the estimated blood pressure value is determined to be abnormal, the output interface 1060 can provide a warning message, etc., as well as guidance information regarding the user's actions (such as information about foods the user should be cautious of, relevant hospital information, etc.). The output interface 1060 can guide the user on the contact position of the subject based on the position information obtained by the position sensor 1020. Furthermore, based on the force / pressure obtained by the force / pressure sensor 1040, the output interface 1060 can guide the force / pressure to be applied by the subject to the pulse wave sensor 1010.

[0102] The communication interface 1070 can communicate with an external device using wired or wireless communication technology under the control of the processor 1030, and can send and receive various data to and from the external device. For example, the communication interface 1070 can send the bio-information estimation result to the external device and can receive various reference information required for estimating the bio-information from the external device. In this case, the external device may include an information processing device (such as a cuff-type blood pressure measurement device, a smartphone, a tablet PC, a desktop computer, a laptop computer, etc.).

[0103] In this case, examples of communication technology may include Bluetooth communication, Bluetooth Low Energy (BLE) communication, near field communication (NFC), wireless local area network (WLAN) communication, Zigbee communication, infrared data association (IrDA) communication, wireless fidelity (Wi-Fi) direct (WFD) communication, ultra-wideband (UWB) communication, Ant+ communication, Wi-Fi communication, radio frequency identification (RFID) communication, 3G communication, 4G communication, 5G communication, etc. However, this is merely exemplary and is not intended to be limiting.

[0104] Figure 11 is a flowchart illustrating a method of estimating biological information according to an embodiment of the present disclosure. Figure 11 The method is an example of a method of estimating bio-information performed by the aforementioned apparatuses 100 , 200 , 300 , and 1000 for estimating bio-information described in detail above, and thus, will be briefly described below.

[0105] In operation 1110, the apparatuses 100, 200, 300, and 1000 for estimating biometric information may measure multiple pulse wave signals at multiple locations of a user's object using a pulse wave sensor. When the user places the object on the pulse wave sensor, the user may change the contact pressure to cause a change in the pulse wave amplitude. In this case, the change in contact force / contact pressure may be obtained by the force / pressure sensor.

[0106] Then, when pulse wave signals are obtained at multiple locations of the subject, the apparatuses 100, 200, 300, and 1000 for estimating biometric information may obtain the location of the pulse wave sensor on the subject in operation 1120. For example, when the subject is in contact with the pulse wave sensor, sensor location information may be obtained based on an image of the subject captured by an external image capturing device or a fingerprint image captured by a fingerprint sensor installed in the apparatus.

[0107] Subsequently, the apparatus 100, 200, 300, and 1000 for estimating bio-information may estimate bio-information at each sensor location based on the pulse wave signal obtained at each sensor location in operation 1130. For example, the apparatus 100, 200, 300, and 1000 for estimating bio-information may generate an oscillogram based on the contact force / contact pressure obtained when measuring the pulse wave signal and the pulse wave signal of each sensor, and may estimate bio-information by using the generated oscillogram.

[0108] Next, in operation 1140, the bio-information estimating apparatus 100, 200, 300, and 1000 may estimate final bio-information based on the subject's blood vessel location information, sensor location information, and bio-information at each sensor location. For example, the bio-information estimating apparatus 100, 200, 300, and 1000 may generate a calibration chart by calculating the relative distance from each sensor location to the blood vessel location, plotting the bio-information at each sensor location relative to the relative distance, and performing curve fitting. Furthermore, when generating the calibration chart, the bio-information estimating apparatus 100, 200, 300, and 1000 may obtain bio-information at points corresponding to blood vessel locations in the calibration chart as final bio-information.

[0109] Then, the apparatus 100, 200, 300, and 1000 for estimating bio-information may output a bio-information estimation result in operation 1150. The apparatus 100, 200, 300, and 1000 for estimating bio-information may provide information (such as estimated bio-information values, warnings, measurements, bio-information estimation history, etc.) to the user by using a display, a speaker, a tactile device, etc.

[0110] Figure 12 is a flowchart illustrating a method of estimating biological information according to another embodiment of the present disclosure. Figure 12 The method is an example of a method of estimating bio-information performed by the aforementioned apparatuses 700 and 1000 for estimating bio-information described in detail above, and thus, will be briefly described below.

[0111] In operation 1210 , the apparatuses 700 and 1000 for estimating bio-information may measure a plurality of pulse wave signals at a plurality of locations of a subject of a user by using a pulse wave sensor, and in operation 1220 , the apparatuses 700 and 1000 for estimating bio-information may obtain the locations of the pulse wave sensors on the subject.

[0112] Then, in operation 1230 , the apparatuses 700 and 1000 for estimating bio-information may estimate bio-information at each sensor location based on the pulse wave signal obtained at each sensor location.

[0113] Subsequently, the apparatuses 700 and 1000 for estimating bio-information may determine one of the plurality of virtual blood vessel positions as the optimal (improved) blood vessel position of the subject in operation 1240. For example, the apparatus 700 for estimating bio-information may determine a group to which a difference between an estimated blood pressure value at a first sensor position and an estimated blood pressure value at a second sensor position belongs, and may determine the virtual blood vessel position of the determined group as the optimal blood vessel position of the subject of the user.

[0114] Next, in operation 1250, the apparatuses 700 and 1000 for estimating bio-information may estimate final bio-information based on the determined optimal blood vessel position information of the object, the sensor position information, and the bio-information at each sensor position, and in operation 1260, the apparatuses 700 and 1000 for estimating bio-information may output the bio-information estimation result.

[0115] Figure 13 is a diagram illustrating an example of a wearable device. Various embodiments of the aforementioned apparatus for estimating bio-information may be installed in a wearable device.

[0116] Reference Figure 13 , the wearable device 1300 includes a main body 1310 and a band 1330 .

[0117] The straps 1330 connected to both ends of the body 1310 can be flexible so as to bend around the user's wrist. The straps 1330 can be composed of a first strap and a second strap that are separate from each other. The first and second straps each have their ends connected to the body 1310, 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 formed in the form of a magnetic connection, a Velcro connection, a pin connection, etc., but is not limited to these. Furthermore, the straps 1330 are not limited to these and can be formed integrally as a non-detachable strap.

[0118] In this case, air may be injected into the band 1330 or the band 1330 may be provided with an air bag so that the band 1330 may have elasticity according to changes in pressure applied to the wrist and may transmit the changes in pressure of the wrist to the body 1310 .

[0119] A battery may be embedded in the body 1310 or the band 1330 to supply power to the wearable device 1300 .

[0120] In addition, the main body 1310 may include a sensor unit 1320 mounted on one side of the main body 1310. The sensor unit 1320 may include a pulse wave sensor for measuring a pulse wave signal. The pulse wave sensor may include a light source for emitting light onto the skin of a wrist or finger, and a light receiver (such as a CIS optical sensor, a photodiode, etc.) for detecting light scattered or reflected from the wrist or finger. The pulse wave sensor may have multiple channels for measuring pulse wave signals at multiple points on the wrist or finger, and each channel may include a light source and a light receiver, and each channel may include multiple light sources for emitting light of different wavelengths. In addition, the sensor unit 1320 may also include a force / pressure sensor for measuring the force / pressure between the wrist or finger and the sensor unit 1320. In addition, the sensor unit 1320 may also include a fingerprint sensor, an ultrasonic sensor, etc., which may be stacked on each other.

[0121] The processor may be installed in the main body 1310. The processor may be electrically connected to a module installed in the wearable device 1300. Based on the pulse wave signal and contact force / pressure measured by the sensor unit 1320 at multiple measurement locations of the subject, the processor may estimate the blood pressure at each measurement location using an oscillometric method based on the pulse wave signal and contact force / pressure measured at the multiple measurement locations of the subject, and may estimate the final blood pressure by calibrating the estimated blood pressure at each measurement location based on the subject's blood vessel location. In this case, the subject's blood vessel location may be the subject's actual blood vessel location obtained based on user input, ultrasound images, MRI images, optical images, etc. Alternatively, if the subject's actual blood vessel location is difficult to obtain, the blood vessel location may be the optimal blood vessel location selected from predefined virtual blood vessel locations for multiple users according to predetermined criteria.

[0122] In addition, the main body 1310 may include a memory that stores reference information for estimating blood pressure and performing various functions of the wearable device 1300 and information processed by various modules of the main body 1310.

[0123] In addition, the main body 1310 may include a manipulator 1340, which is provided on one side surface of the main body 1310 and receives a user's control command and sends the received control command to the processor. The manipulator 1340 may have a power button for inputting a command to turn on / off the wearable device 1300.

[0124] In addition, a display for outputting information to the user may be mounted on the front surface of the main body 1310. The display may have a touch screen for receiving touch input. The display may receive the user's touch input and send the touch input to the processor, and may display the processing result of the processor.

[0125] Further, the main body 1310 can include a communication interface for communication with an external device. The communication interface can transmit a blood pressure estimation result to an external device such as a user's smartphone.

[0126] Figure 14 FIG. 1 is a diagram illustrating an example of a smart device. In this case, the smart device can include a smartphone, a tablet PC, etc. The smart device can include various embodiments of the aforementioned device for estimating biological information.

[0127] Referring to Figure 14 , the smart device 1400 includes a main body 1410 and a pulse wave sensor 1430 mounted on one surface of the main body 1410. For example, the pulse wave sensor 1430 can include one or more light sources 1432 disposed at a predetermined position of the pulse wave sensor 1430. The one or more light sources 1432 can emit light of different wavelengths. Further, a plurality of light receivers 1431 can be disposed at a predetermined distance from the light sources 1432. However, this is merely an example, and the pulse wave sensor 1430 can have various shapes as described above. Further, a force / pressure sensor for measuring a contact force / pressure of a finger can be mounted in the main body 1410 at a lower end of the pulse wave sensor 1430.

[0128] Further, a display can be mounted on a front surface of the main body 1410. The display can visually output a blood pressure estimation result, a health condition assessment result, etc. The display can include a touch screen, and can receive information input through the touch screen and transmit the information to the processor.

[0129] As shown in Figure 14 , the main body 1410 can include an image sensor 1420. The image sensor 1420 can photograph various images, and can obtain, for example, a fingerprint image of a finger in contact with the pulse wave sensor 1430. Further, when an image sensor based on a CIS technology is mounted in the light receiver 1431 of the pulse wave sensor 1430, the image sensor 1420 can be omitted.

[0130] As described above, the processor can estimate blood pressure based on a blood vessel position of an object and sensor position information obtained when the object is in contact with the sensor.

[0131] Embodiments of the disclosure can be implemented by computer-readable code written on a non-transitory computer readable medium, which is executed by a processor. The non-transitory computer readable medium can be any kind of recording apparatus that stores data in a computer readable manner.

[0132] Examples of the non-transitory computer readable medium include ROM, RAM, CD-ROM, magnetic tapes, floppy disks, optical data storage, and carrier waves (e.g., data transmission through the Internet). The non-transitory computer readable medium can be distributed over multiple computer systems connected to the network so that the computer readable code is written and executed in a distributed manner. Ordinary programmers skilled in the art of the present disclosure can derive the functional programs, codes, and code segments to implement the embodiments of the present disclosure from this disclosure.

[0133] The present disclosure has been described with respect to example embodiments. However, it will be understood by those skilled in the art that various changes and modifications can be made without changing the technical conception and features of the present disclosure. Therefore, it is intended that such changes and modifications be included within the scope of the present disclosure.

Claims

1. A device for estimating biometric information of a user, the device comprising: a pulse wave sensor configured to: obtain a plurality of pulse wave signals of a subject; a position sensor configured to: obtain sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on measurement of each of the plurality of pulse wave signals by the pulse wave sensor; as well as The processor is configured to: estimating first biological information at each sensor position based on each of the plurality of pulse wave signals; and estimating second biological information based on the blood vessel position of the subject, each sensor position, and the first biological information at each sensor position, The processor is configured as follows: generating a calibration graph by plotting a first bio-information value at each sensor position with respect to a relative distance of each sensor position from a blood vessel position of the subject and based on performing curve fitting; and obtaining a second bio-information value based on the calibration map, The processor is configured to obtain a biological information value of a point corresponding to a blood vessel position of the object in the calibration map as the second biological information value.

2. The device according to claim 1, wherein Based on the object being in contact with the pulse wave sensor, the position sensor is further configured to obtain sensor position information based on an image of the object captured by an external capturing device.

3. The device according to claim 1, wherein The position sensor includes a fingerprint sensor configured to obtain a fingerprint image, and The position sensor is further configured to obtain sensor position information based on a fingerprint image obtained by the fingerprint sensor in response to contact between the object and the pulse wave sensor.

4. The device according to claim 1, wherein Based on the object being in contact with the pulse wave sensor, the position sensor is further configured to obtain sensor position information based on predefined measured position information of the pulse wave sensor.

5. The apparatus according to claim 1, further comprising: A blood vessel position sensor is configured to obtain blood vessel position information of the object based on at least one of an optical image, an ultrasound image, a magnetic resonance imaging image, and a photoacoustic image of the object obtained by an external device.

6. The apparatus according to claim 1, further comprising: The blood vessel position sensor includes an ultrasonic sensor configured to transmit ultrasonic waves to a subject and receive signals reflected from the subject, and obtains blood vessel position information of the subject based on an ultrasonic image obtained by the ultrasonic sensor.

7. The apparatus according to claim 1, further comprising: A force sensor is configured to measure a force applied by the subject to the pulse wave sensor.

8. The apparatus according to claim 7, wherein The processor is also configured to: generating an oscillogram based on each of the plurality of pulse wave signals and the force measured by the force sensor, and The first bio-information at each sensor position is estimated by using an oscillogram.

9. The apparatus according to claim 1, further comprising: A pressure sensor is configured to measure pressure applied to the pulse wave sensor by an object, wherein the pressure sensor is implemented as a force sensor for measuring contact force and an area sensor for measuring contact area, and the pressure is obtained based on the contact force measured by the force sensor and the contact area measured by the area sensor.

10. The apparatus according to claim 9, wherein The processor is also configured to: generating an oscillogram based on each of the plurality of pulse wave signals and the pressure measured by the pressure sensor, and The first bio-information at each sensor position is estimated by using an oscillogram.

11. The apparatus according to claim 1, wherein The biological information includes one or more of the following: blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, pressure index, fatigue level, skin age, and skin elasticity.

12. A computer-readable storage medium storing a program, wherein: When the program is executed by a processor, the processor is caused to execute a method for estimating biometric information of a user, the method comprising: obtaining a plurality of pulse wave signals of the subject; obtaining sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on measuring each of the plurality of pulse wave signals with a pulse wave sensor; estimating first biological information at each sensor position based on each of the plurality of pulse wave signals; and estimating second biological information based on the blood vessel position of the subject, each sensor position, and the first biological information at each sensor position, wherein the step of estimating the second biological information includes: generating a calibration graph by plotting the first biological information value at each sensor position relative to the relative distance of each sensor position from the blood vessel position of the subject and by performing curve fitting; and obtaining the second biological information value based on the calibration graph, The step of obtaining the second biological information includes obtaining a biological information value of a point corresponding to a blood vessel position of the object in the calibration map as the second biological information value.

13. The computer-readable storage medium of claim 12, wherein: The method also includes measuring a force applied by the subject to the pulse wave sensor.

14. The computer-readable storage medium of claim 13, wherein: The step of estimating first biometric information at each sensor location includes: An oscillogram is generated based on each of the plurality of pulse wave signals and the force, and first bio-information at each sensor position is estimated by using the oscillogram.

15. The computer-readable storage medium of claim 12, wherein: The method further includes measuring pressure applied by the object to the pulse wave sensor by a pressure sensor, wherein the pressure sensor is implemented as a force sensor for measuring contact force and an area sensor for measuring contact area, and the pressure is obtained based on the contact force measured by the force sensor and the contact area measured by the area sensor.

16. The computer-readable storage medium of claim 15, wherein: The step of estimating first biometric information at each sensor location includes: An oscillogram is generated based on each of the plurality of pulse wave signals and pressure, and first bio-information at each sensor position is estimated by using the oscillogram.

17. A device for estimating biometric information of a user, the device comprising: a pulse wave sensor configured to: obtain a plurality of pulse wave signals of a subject; a position sensor configured to: obtain sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on the pulse wave sensor measuring each of the plurality of pulse wave signals; as well as The processor is configured to: estimating first bio-information at each sensor location based on each of the plurality of pulse wave signals; determining one of the plurality of virtual blood vessel positions as the blood vessel position of the subject based on the first bio-information at each sensor position; and estimating second biological information based on the blood vessel position of the subject, each sensor position, and the first biological information at each sensor position, wherein the processor is configured to: generate a calibration map by plotting a first bio-information value at each sensor location relative to a relative distance of each sensor location from a location of a blood vessel of the subject; and obtaining a second bio-information value based on the calibration map, The processor is configured to obtain a biological information value of a point corresponding to a blood vessel position of the object in the calibration map as the second biological information value.

18. The apparatus according to claim 17, wherein Based on the difference between the first bio-information values ​​at each sensor position, the processor is further configured to determine one virtual blood vessel position among the plurality of virtual blood vessel positions as the blood vessel position of the subject.

19. The apparatus according to claim 18, wherein A virtual blood vessel position is set for each of a plurality of groups preclassified based on a difference between first bio-information values ​​of each sensor position obtained from a plurality of users.

20. The apparatus according to claim 19, wherein The processor is also configured to: determining a group to which the difference between the first biological information values ​​at each sensor position belongs among the plurality of groups; and A virtual blood vessel position predefined for the determined group is determined as the blood vessel position of the subject.

21. The apparatus of claim 17, further comprising: A force sensor is configured to measure a force applied by the subject to the pulse wave sensor.

22. The apparatus according to claim 21, wherein The processor is also configured to: generating an oscillogram based on each of the plurality of pulse wave signals and the force measured by the force sensor, and The first bio-information at each sensor position is estimated by using an oscillogram.

23. The apparatus of claim 17, further comprising: A pressure sensor is configured to measure pressure applied to the pulse wave sensor by an object, wherein the pressure sensor is implemented as a force sensor for measuring contact force and an area sensor for measuring contact area, and the pressure is obtained based on the contact force measured by the force sensor and the contact area measured by the area sensor.

24. The apparatus according to claim 23, wherein The processor is also configured to: generating an oscillogram based on each of the plurality of pulse wave signals and the pressure measured by the pressure sensor, and The first bio-information at each sensor position is estimated by using an oscillogram.

25. A computer-readable storage medium storing a program, wherein: When the program is executed by a processor, the processor is caused to execute a method for estimating biometric information of a user, the method comprising: obtaining a plurality of pulse wave signals of the subject; obtaining sensor position information identifying a sensor position on the object for each of the plurality of pulse wave signals based on measuring each of the plurality of pulse wave signals with a pulse wave sensor; estimating first bio-information at each sensor location based on each of the plurality of pulse wave signals; determining one of the plurality of virtual blood vessel positions as the blood vessel position of the subject based on the first biological information at each sensor position; and estimating second biological information based on the blood vessel position of the subject, each sensor position, and the first biological information at each sensor position, wherein the step of estimating the second biological information includes: generating a calibration map by plotting the first biological information value at each sensor position relative to the relative distance of each sensor position from the determined blood vessel position of the subject; and obtaining the second biological information value based on the calibration map, The step of obtaining the second biological information includes obtaining a biological information value of a point corresponding to a blood vessel position of the object in the calibration map as the second biological information value.

26. The computer-readable storage medium of claim 25, wherein: The step of determining one of the plurality of virtual blood vessel positions as the blood vessel position of the subject includes determining one of the plurality of virtual blood vessel positions as the blood vessel position of the subject based on a difference between first bio-information values ​​at each sensor position.

27. The computer-readable storage medium of claim 26, wherein: The step of determining one of the plurality of virtual blood vessel positions as the blood vessel position of the object includes determining a group to which the difference belongs among a plurality of groups, and determining a virtual blood vessel position predefined for the determined group as the blood vessel position of the object.

28. The computer-readable storage medium of claim 25, wherein: The method also includes measuring a force applied by the subject to the pulse wave sensor.

29. The computer-readable storage medium of claim 28, wherein: The step of estimating first biometric information at each sensor location includes: generating an oscillogram based on each pulse wave signal and the force; and The first bio-information at each sensor position is estimated by using an oscillogram.

30. The computer-readable storage medium of claim 25, wherein: The method further includes measuring pressure applied by the object to the pulse wave sensor by a pressure sensor, wherein the pressure sensor is implemented as a force sensor for measuring contact force and an area sensor for measuring contact area, and the pressure is obtained based on the contact force measured by the force sensor and the contact area measured by the area sensor.

31. The computer-readable storage medium of claim 30, wherein: The step of estimating first biometric information at each sensor location includes: generating an oscillogram based on each pulse wave signal and the pressure; and The first bio-information at each sensor position is estimated by using an oscillogram.

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