Device and method for estimating biological information

Abstract

Devices and methods for estimating biological information are provided. The device for estimating biological information includes: a pulse wave sensor configured to measure a pulse wave signal from an object; a force sensor configured to measure a force applied between the object and the pulse wave sensor; and a processor configured to: obtain an oscillogram by using the pulse wave signal and the force, determine a first mean arterial pressure (MAP) based on the obtained oscillogram, extract additional information in an interval before a point of the first MAP of the oscillogram, obtain a second MAP based on the first MAP and the additional information, and estimate biological information based on the obtained second MAP.

Description

[0001] This application claims priority to Korean Patent Application No. 10-2021-0035852, filed with the Korean Intellectual Property Office on Mar. 19, 2021, the entire disclosure of which is incorporated herein by reference for all purposes. Technical Field

[0002] Example embodiments of the present disclosure relate to a device and method for estimating biological information and a technique for cuffless blood pressure estimation. Background Art

[0003] General techniques for extracting cardiovascular characteristics (such as blood pressure, etc.) without using a pressure cuff include a pulse wave analysis (PWA) method and a pulse wave velocity (PWV) method.

[0004] The pulse wave analysis (PWA) method is a method of extracting cardiovascular characteristics by analyzing the shape of a photoplethysmogram (PPG) signal or a body surface pressure signal obtained from a peripheral part of the body (e.g., fingertip, radial artery, etc.). The blood ejected from the left ventricle causes a reflection at large branch regions (such as the renal artery and the iliac artery), and this reflection affects the shape of the pulse wave or the body pressure wave measured at the peripheral part of the body. Therefore, 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 the pulse wave transit time. In this method, the delay (or pulse transit time (PTT)) between the R peak of the electrocardiogram (ECG) (corresponding to the left ventricular systolic interval) and the peak of the PPG signal of the finger or the radial artery is measured by measuring the ECG and the PPG signal of the peripheral part of the body, and the speed at which the blood from the heart reaches the peripheral part of the body is calculated by dividing the approximate length of the arm by the PTT. Summary of the Invention

[0006] According to an aspect of an example embodiment, there is provided a device for estimating biological information, the device including: a pulse wave sensor configured to measure a pulse wave signal from an object; a force sensor configured to measure a force applied between the object and the pulse wave sensor; and a processor configured to: obtain an oscillogram by using the pulse wave signal and the force, determine a first mean arterial pressure (MAP) based on the obtained oscillogram, extract additional information in an interval before a point of the first MAP of the oscillogram, obtain a second MAP based on the first MAP and the additional information, and estimate biological information based on the obtained second MAP.

[0007] A pulse wave sensor may include: at least one light sensor configured to emit light onto an object; and at least one detector configured to detect light scattered or reflected from the object.

[0008] The processor may also be configured to: determine a force value at a maximum amplitude point in the obtained oscillogram as a first MAP.

[0009] The processor may also be configured to: determine peak points in an interval before the first MAP, and extract at least one of the following as additional information: the amplitude and force at the determined peak points, the amplitude and force at a valley point between the peak points and the point of the first MAP, and the amplitude at the point of the first MAP.

[0010] Based on determining that there are no peak points in the interval before the first MAP, the processor may also be configured to: determine a maximum amplitude point in an interval before a valley point, where the valley point is the last valley point before the first MAP, as a peak point.

[0011] The processor may also be configured to: extract at least two additional information, and obtain a second MAP by applying a ratio between values of the at least two additional information to the first MAP.

[0012] The at least two additional information may include: the amplitude at the point of the first MAP and the amplitude at the peak point of the first MAP, and the processor is also configured to: obtain a second MAP by applying a ratio between the amplitude at the point of the first MAP and the amplitude at the peak point to the first MAP.

[0013] The at least two additional information may include: the amplitude at the point of the first MAP and the amplitude at the valley point of the first MAP, and the processor is also configured to: obtain a second MAP by applying a ratio between the amplitude at the point of the first MAP and the amplitude at the valley point to the first MAP.

[0014] The processor may also be configured to: estimate biometric information based on the second MAP by using a biometric information estimation model.

[0015] The processor may also be configured to: extract at least three additional information including the force at the peak point, and obtain a second MAP based on a ratio between values of at least two of the at least three additional information, and also based on a first value obtained by subtracting the value of the force at the peak point from the first MAP.

[0016] The processor may also be configured to: obtain a second MAP by applying a ratio between the amplitude at the point of the first MAP and the amplitude at the peak point to the first value.

[0017] The processor may also be configured to obtain a second MAP by applying a ratio between the amplitude at a point of the first MAP and the amplitude at a trough to a first value.

[0018] The processor may also be configured to estimate biometric information based on the first MAP and the second MAP by using a biometric information estimation model.

[0019] The device may further include a sensor position acquirer configured to acquire sensor position information of the pulse wave sensor, where the sensor position information indicates the position of the pulse wave sensor on an object in contact with the pulse wave sensor, and the processor may also be configured to perform control based on the sensor position information to guide the user to the contact position of the object.

[0020] The sensor position acquirer may include a fingerprint sensor configured to acquire a fingerprint image of an object in contact with the pulse wave sensor, and the sensor position acquirer is further configured to acquire sensor position information based on the fingerprint image acquired by the fingerprint sensor.

[0021] The sensor position acquirer may also be configured to acquire sensor position information based on an image of an object in contact with the pulse wave sensor, where the image is acquired by an external image capturing device.

[0022] The pulse wave sensor may have a plurality of channels for measuring pulse wave signals at multiple points of an object, and the processor may also be configured to select at least one channel from the plurality of channels based on a pulse wave signal corresponding to a predetermined position of an object in contact with the pulse wave sensor or based on a pulse wave signal having a noise level less than or equal to a predetermined level, and obtain an oscillogram based on the pulse wave signal obtained through the selected at least one channel.

[0023] The biometric information may include at least one of the following: blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, pressure index, fatigue level, skin age, and skin elasticity.

[0024] According to an aspect of an exemplary embodiment, a method for estimating biometric information is provided. The method includes: measuring a pulse wave signal from an object by using a pulse wave sensor; measuring a force applied between the object and the pulse wave sensor; obtaining an oscillogram by using the pulse wave signal and the force; determining a first mean arterial pressure (MAP) based on the obtained oscillogram; extracting additional information in an interval before a point of the first MAP of the oscillogram; obtaining a second MAP based on the first MAP and the additional information; and estimating biometric information based on the obtained second MAP.

[0025] The step of determining the first MAP may include: determining a force value at a maximum amplitude point in the obtained oscillogram as the first MAP.

[0026] The steps of extracting additional information may include: determining peak points in the interval before the first MAP, and extracting at least one of the following as additional information: the amplitude and force at the determined peak points, the amplitude and force at the valley points between the peak points and the points of the first MAP, and the amplitude at the points of the first MAP.

[0027] The steps of extracting additional information may include: based on determining that there are no peak points in the interval before the first MAP, determining the maximum amplitude point in the interval before the valley point as the peak point, where the valley point is the last valley point before the first MAP.

[0028] The steps of extraction may include: extracting at least two additional information, and the steps of obtaining the second MAP may include: obtaining the second MAP by applying the ratio between the values of the at least two additional information to the first MAP.

[0029] The steps of estimating biological information may include: estimating biological information based on the second MAP by using a biological information estimation model.

[0030] The steps of extraction may include: extracting at least three additional information including the force at the peak point, and the steps of obtaining the second MAP may include: obtaining the second MAP based on the ratio between the values of at least two of the at least three additional information and also based on the value obtained by subtracting the value of the force at the peak point from the first MAP.

[0031] The steps of estimating biological information may include: estimating biological information based on the first MAP and the second MAP by using a biological information estimation model.

[0032] The method may further include: obtaining sensor position information of a pulse wave sensor, where the sensor position information indicates the position of the pulse wave sensor on an object in contact with the pulse wave sensor; and performing control based on the sensor position information to guide the user to the contact position of the object.

[0033] According to an aspect of the example embodiment, there is provided a computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to execute the method of estimating biological information.

[0034] According to an aspect of an exemplary embodiment, there is provided an electronic device including: a device for estimating biological information; and an output device configured to output a processing result of the device for estimating biological information, wherein the device for estimating biological information includes: a pulse wave sensor configured to measure a pulse wave signal from a subject; a force sensor configured to measure a force applied between the subject and the pulse wave sensor; and a processor configured to: obtain an oscillogram by using the pulse wave signal and the force, determine a first mean arterial pressure (MAP) based on the obtained oscillogram, extract additional information in an interval before a point of the first MAP of the oscillogram, obtain a second MAP based on the first MAP and the additional information, and estimate biological information based on the obtained second MAP.

[0035] The electronic device may include at least one of a wristwatch wearable device, an ear-worn device, and a mobile device.

[0036] The processor may also be configured to: determine a peak point in an interval before the first MAP, and extract at least one of the following as additional information: the amplitude and force at the determined peak point, the amplitude and force at a valley point between the peak point and the point of the first MAP, and the amplitude at the point of the first MAP.

[0037] The processor may also be configured to: extract at least two pieces of additional information, and obtain a second MAP based on a ratio between values of the at least two pieces of additional information and the first MAP. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The above and other aspects, features, and advantages of the present disclosure will become more apparent from the following detailed description of exemplary embodiments taken in conjunction with the accompanying drawings, in which:

[0039] Figure 1 is a block diagram showing a device for estimating biological information according to an exemplary embodiment;

[0040] Figure 2A and Figure 2B is a diagram explaining an example of estimating blood pressure based on oscillometry;

[0041] Figure 3A shows a case where a single blood vessel is located in a subject, Figure 3B shows a case where multiple blood vessels are located in a subject;

[0042] Figure 4A and Figure 4B is a diagram showing an oscillogram experimentally obtained and an actually observed oscillogram for a single blood vessel according to an exemplary embodiment;

[0043] Figure 4C and Figure 4Dis a diagram showing oscillograms experimentally obtained for multiple blood vessels and the actually observed oscillograms according to an exemplary embodiment;

[0044] Figure 5 is a diagram showing an example of an oscillogram of an object in which multiple blood vessels are located;

[0045] Figure 6 is a block diagram showing a device for estimating biological information according to an exemplary embodiment;

[0046] Figure 7A shows an example of a pulse wave sensor having a single channel, Figure 7B shows an example of a pulse wave sensor having multiple channels;

[0047] Figure 8 is a flowchart showing a method for estimating biological information according to an exemplary embodiment;

[0048] Figure 9 is a flowchart showing a method for estimating biological information according to an exemplary embodiment;

[0049] Figure 10 is a block diagram showing an electronic device including a device for estimating biological information according to an exemplary embodiment;

[0050] Figure 11 is a diagram showing a wristwatch wearable device including a device for estimating biological information according to an exemplary embodiment;

[0051] Figure 12 is a diagram showing a mobile device including a device for estimating biological information according to an exemplary embodiment; and

[0052] Figure 13 is a diagram showing an ear-worn device including a device for estimating biological information according to an exemplary embodiment. DETAILED DESCRIPTION

[0053] Details of the exemplary embodiments are included in the following detailed description and the drawings. The advantages and features of the disclosure and the method of implementing the disclosure will be more clearly understood through the following exemplary embodiments described in detail with reference to the drawings. Throughout the drawings and the detailed description, unless otherwise described, the same reference numerals will be understood to refer to the same elements, features, and structures.

[0054] It should be understood that although terms such as first and second may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. In addition, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. It will also be understood that unless explicitly described to the contrary, when an element is referred to as "including" another element, the element is not intended to exclude one or more other elements, but also includes one or more other elements. In the following description, terms (such as, "unit" and "module") indicate a unit for processing at least one function or operation, and they can be implemented by using hardware, software, or a combination thereof.

[0055] Hereinafter, embodiments of a device and a method for estimating biological information will be described in detail with reference to the accompanying drawings.

[0056] When an expression such as "at least one of..." is before a list of elements, the expression modifies the entire list of elements and not a single element in 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, all of a, b, and c, or any variation of the foregoing examples.

[0057] Figure 1 is a block diagram showing a device for estimating biological information according to an exemplary embodiment.

[0058] A device 100 for estimating biological information according to various exemplary embodiments to be described below can be installed in a terminal (such as, a smart phone, a tablet PC, a desktop computer, a laptop computer, etc.), a wearable device, etc. Examples of wearable devices can include a wristwatch-type wearable device, a bracelet-type wearable device, a wristband-type wearable device, a ring-type wearable device, a glasses-type wearable device, a headband-type wearable device, etc., but the wearable devices are not limited thereto.

[0059] Referring to Figure 1 , a device 100 for estimating biological information according to an embodiment includes a photoplethysmogram (PPG) sensor 110, a force sensor 120, and a processor 130.

[0060] The PPG sensor 110 measures a photoplethysmogram (PPG) signal (hereinafter, referred to as a "pulse wave signal") from an object. The object can be an area of the human body that can come into contact with the PPG sensor 110, and can be a body part where a pulse wave can be easily measured by PPG. For example, the object can be a finger where blood vessels are densely distributed, but the object is not limited thereto, and can be an area adjacent to the radial artery on the wrist, or a peripheral part of the body where veins or capillaries are located (such as, the upper part of the wrist, toes, etc.).

[0061] The pulse wave sensor 110 may include one or more light sources 111 configured to emit light onto an object, and one or more detectors 112 disposed at a predetermined distance from the light source 111 and configured to detect light scattered or reflected from the object. The light source 111 may include, but is not limited to, a light emitting diode (LED), a laser diode (LD), a phosphor, etc. In addition, the detector 112 may include a photodiode, a photodiode array, a complementary metal oxide semiconductor (CMOS) image sensor, a charge coupled device (CCD) image sensor, etc.

[0062] The pulse wave sensor 110 may include a light source 111 and a detector 112 formed in a single channel to measure a pulse wave signal at a specific point of an object. Optionally, the pulse wave sensor 110 may include multiple channels to measure multiple pulse wave signals at multiple points of an object. Each channel of the pulse wave sensor 110 may be formed in a predetermined shape (such as circular, elliptical, linear, etc.) to measure pulse wave signals at multiple points of an object. Each channel of the pulse wave sensor 110 may include one or more light sources and one or more detectors. In addition, each channel may include two or more light sources to emit light of multiple wavelengths. Optionally, the pulse wave sensor 110 may include, for example, one or more light sources and a CMOS image sensor to measure a pulse wave signal from a predetermined area of an object.

[0063] When a user places an object on the pulse wave sensor 110 and increases or decreases the pressing force to cause a change in the pulse wave amplitude, the force sensor 120 may measure the contact force applied between the pulse wave sensor 110 and the object. The force sensor 120 may include a strain gauge, etc. The force sensor 120 may be disposed at the upper end or the lower end of the pulse wave sensor 110.

[0064] The processor 130 may estimate biological information based on the pulse wave signal obtained through the pulse wave sensor 110 and the force obtained through the force sensor 120. The biological information may include, for example, blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, pressure index, fatigue level, skin age, skin elasticity, etc., but is not limited thereto. For ease of explanation, blood pressure will be used as an example for illustration in the following description, but the biological information is not limited to blood pressure.

[0065] Figure 2A and Figure 2B are diagrams explaining an example of estimating blood pressure based on the oscillometric method. Figure 3A and Figure 3B are diagrams showing a case where a single blood vessel is located in an object in contact with a light source and a detector and a case where multiple blood vessels are located in the object. Figure 4A and Figure 4BIt is a diagram showing the oscillogram experimentally obtained for a single blood vessel and the actually observed oscillogram according to an exemplary embodiment. Figure 4C and Figure 4D It is a diagram showing the oscillogram experimentally obtained for multiple blood vessels and the actually observed oscillogram according to an exemplary embodiment.

[0066] Figure 2A and Figure 2B It is a diagram explaining an example of estimating blood pressure based on oscillometry.

[0067] Referring to Figure 2A and Figure 2B ,The processor 130 can extract, for example, the peak-to-peak point or peak-to-peak amplitude of the pulse wave signal waveform by subtracting the negative (-) amplitude value in3 from the positive (+) amplitude value in2 of the waveform envelope in1 at each measurement time point of the pulse wave signal. In addition, the processor 130 can obtain an oscillogram (OW) by plotting the peak-to-peak amplitude at each measurement time point against the force value at the corresponding time point and by performing, for example, polynomial curve fitting.

[0068] The processor 130 can extract feature points for estimating blood pressure from the generated oscillogram OW, and can estimate blood pressure by using the extracted feature points. For example, the processor 130 can determine the force value at the maximum amplitude point in the oscillogram OW as the mean arterial pressure (MAP) as a feature point, and can extract the force values DP, SP, etc. at points corresponding to amplitude values having a preset ratio (e.g., 0.5 to 0.7) of the maximum amplitude value from the oscillogram OW as other feature points. For example, the processor 130 can determine the MAP itself as the mean blood pressure, and can determine the DP as the diastolic blood pressure and the SP as the systolic blood pressure. Alternatively, by applying the corresponding force values MAP, DP, and SP to a predefined blood pressure estimation model, the processor 130 can independently estimate the mean blood pressure, diastolic blood pressure, and systolic blood pressure. The blood pressure estimation model can be represented in the form of various linear combination functions or nonlinear combination functions (such as addition, subtraction, division, multiplication, logarithmic values, regression equations, etc.) without specific limitation.

[0069] Generally, the disadvantage of the method of estimating blood pressure based on oscillometry using a finger PPG signal is that due to the complex structure of the blood vessels in the finger, the blood pressure information of multiple blood vessels overlaps, generating a single optical signal, causing the blood pressure information of the target blood vessel to be distorted. For example, the oscillogram measured from the upper arm shows a single peak, but the oscillogram measured from the finger shows multiple peaks due to the blood vessels with low blood pressure, causing the oscillogram of the blood vessels with low blood pressure to overlap with the oscillogram of the target blood vessel, resulting in a possible reduction in the accuracy of estimating the desired blood pressure.

[0070] Reference Figure 4A , for an object including a single blood vessel 31, by performing mathematical modeling based on the change in the distance between the optical path and the target blood vessel to be measured, a point of MAP is obtained in the oscillogram 41, and the change in the distance is caused by skin deformation due to the force applied to the target blood vessel. Reference Figure 4B , by using the actually measured pulse wave signal as referred to above Figure 2A and Figure 2B , according to the change in the distance between the optical path and the target blood vessel due to the force applied to the target blood vessel, based on the observed sensitivity of the vascular oscillometry, a point of MAP is obtained in the oscillogram 42. When Figure 4A and Figure 4B are compared with each other, it can be known that the point of MPA in the oscillogram 41 is located at a position similar to the point of MPA in the oscillogram 42, and the corresponding oscillograms 41 and 42 show a similar shape with a single peak.

[0071] Reference Figure 3B , Figure 4C and Figure 4D , for an object including multiple blood vessels 32, the oscillogram 43 obtained by mathematical modeling of the target blood vessel and the oscillogram 44 obtained by using the actually measured pulse wave signal show multiple peaks. However, due to the distortion caused by blood vessels other than the target blood vessel, the point of MAP in the oscillogram 44 may appear at a position before the point of MAP in the oscillogram 43. Therefore, when estimating blood pressure for an object (such as a finger) where multiple blood vessels are located, it is necessary to calibrate MAP to improve the accuracy of the estimated blood pressure.

[0072] The processor 130 can obtain an oscillogram based on the pulse wave signal measured from the object and by measuring the force applied between the object and the pulse wave signal, and can determine a first MAP based on the obtained oscillogram. For example, the processor 130 can determine the force value at the maximum amplitude point in the obtained oscillogram as the first MAP, but the first MAP is not limited thereto.

[0073] The processor 130 can extract additional information in the interval before the point of the first MAP in the oscillogram. The additional information may refer to information for calibrating the first MAP to improve the accuracy of the estimated blood pressure.

[0074] Figure 5 is a diagram showing an example of an oscillogram of an object in which multiple blood vessels are located.

[0075] Reference Figure 5, the processor 130 may determine the peak points in the interval before the first MAP, and may extract the amplitude a1 and force f1 at the determined peak points, the amplitude a2 and force f2 at the valley points between the peak points and the points of the first MAP, and / or the amplitude a3 at the points of the first MAP as additional information. However, the additional information extracted by the processor 130 is not limited to this.

[0076] If there are no peak points in the interval before the first MAP, the processor 130 may determine the maximum amplitude point in the interval before the valley point immediately adjacent to the first MAP (or the last valley point that appears before the first MAP) as the peak point.

[0077] When obtaining the additional information, the processor 130 may obtain a second MAP based on the first MAP and the additional information, and may estimate the biological information based on the obtained second MAP, thereby reducing the error in blood pressure estimation caused by multiple blood vessels.

[0078] For example, the processor 130 may obtain the second MAP by applying the ratio between at least two additional information items to the first MAP.

[0079] For example, the processor 130 may obtain the second MAP by applying the ratio between the amplitude at the points of the first MAP and the amplitude at the peak points to the first MAP, and the second MAP may be represented by Equation 1 below.

[0080] [Equation 1]

[0081] Second MAP = First MAP × (1 + a1 / a3)

[0082] Here, a1 represents the amplitude at the peak points, and a3 represents the amplitude at the points of the first MAP. If the amplitude a1 at the peak points has an amplitude small enough to be ignored, then the amplitude a1 is much smaller than the amplitude a3, such that the first MAP is approximately equal to the second MAP; if not, the first MAP is likely to be underestimated, such that the second MAP can be obtained by amplifying the first MAP at a ratio of a1 / a3.

[0083] In addition, the processor 130 may obtain the second MAP by applying the ratio between the amplitude at the valley points and the amplitude at the points of the first MAP to the first MAP, and the second MAP may be represented by Equation 2 below.

[0084] [Equation 2]

[0085] Second MAP = First MAP × (1 + a2 / a3)

[0086] Here, a2 represents the amplitude at the valley point, and a3 represents the amplitude at the point of the first MAP. If the amplitude a2 at the valley point has an amplitude small enough to be ignored, then the amplitude a2 is much smaller than the amplitude a3, such that the first MAP is approximated to the second MAP; if not, the first MAP is likely to be underestimated, such that the second MAP can be obtained by amplifying the first MAP at a ratio of a2 / a3.

[0087] The processor 130 can estimate the biological information by using a biological information estimation model based on the obtained second MAP. For example, the processor 130 can estimate the blood pressure by applying the second MAP to a predefined blood pressure estimation model, and the blood pressure estimation model can be represented in the form of various linear or non-linear combination functions (such as addition, subtraction, division, multiplication, logarithmic values, regression equations, etc.) without specific limitations.

[0088] In another example, the processor 130 can obtain a second MAP based on the ratio between at least two additional information items and the value obtained by subtracting the force value at the peak point from the first MAP, and the second MAP indicates the degree of underestimation.

[0089] For example, the processor 130 can obtain a second MAP by applying the ratio between the amplitude at the point of the first MAP and the amplitude at the peak point to the value obtained by subtracting the force value at the peak point from the first MAP, and the second MAP can be represented by Equation 3 below.

[0090] [Equation 3]

[0091] Second MAP = a1 / a3 × (First MAP - f1)

[0092] Here, a1 represents the amplitude at the peak point, a3 represents the amplitude at the point of the first MAP, and f1 represents the force value at the peak point. In Equation 3, f1 corresponding to the MAP of blood vessels other than the target blood vessel is excluded, such that the second MAP obtained by using Equation 3 can indicate the degree of distortion of the first MAP.

[0093] In addition, the processor 130 can obtain a second MAP by applying the ratio between the amplitude at the valley point and the amplitude at the point of the first MAP to the value obtained by subtracting the force value at the peak point from the first MAP, and the second MAP can be represented by Equation 4 below.

[0094] [Equation 4]

[0095] Second MAP = a2 / a3 × (First MAP - f1)

[0096] Here, a2 represents the amplitude at the trough point, a3 represents the amplitude at the point of the first MAP, and f1 represents the force value at the peak point. In Equation 4, f1 corresponding to the MAP of vessels other than the target vessel is excluded, so that the second MAP obtained using Equation 4 can indicate the degree of distortion of the first MAP.

[0097] Although the above method for calibrating the first MAP has been described with reference to Equations 1 to 4, these are merely examples, and the embodiments are not limited thereto.

[0098] The processor 130 may estimate biometric information based on the first MAP and the second MAP by using a biometric information estimation model. For example, the processor 130 may estimate blood pressure by applying the first MAP and the second MAP to a predefined blood pressure estimation model, and the blood pressure estimation model may be represented in the form of various linear combination functions or nonlinear combination functions (such as addition, subtraction, division, multiplication, logarithmic values, regression equations, etc.) without specific limitations.

[0099] Figure 6 is a block diagram showing a device for estimating biometric information according to another exemplary embodiment.

[0100] Referring to Figure 6 , a device 600 for estimating biometric information according to an embodiment includes a pulse wave sensor 610, a force sensor 620, a processor 630, and a sensor position acquirer 640. The pulse wave sensor 610 includes a light source 611 and a detector 612. The pulse wave sensor 610, the force sensor 620, the processor 630, the light source 611, and the detector 612 may be the same as or similar to those described in detail above with reference to Figure 1 Those described in detail.

[0101] When the object comes into contact with the pulse wave sensor 610, the sensor position acquirer 640 may acquire the sensor position information of the pulse wave sensor 610 located on the object. At least some of the functions of the sensor position acquirer 640 may be integrated into the processor 630.

[0102] The sensor position acquirer 640 may include a fingerprint sensor configured to acquire a fingerprint image of an object in contact with the pulse wave sensor 610. The fingerprint sensor may be disposed at an upper end or a lower end of the pulse wave sensor 610. The sensor position acquirer 640 may acquire sensor position information (e.g., information about the position of the pulse wave sensor on the object in contact with the pulse wave sensor) based on the fingerprint image acquired by the fingerprint sensor when the object is in contact with the pulse wave sensor 610. In addition, the sensor position acquirer 640 may estimate the sensor position by analyzing a change in the fingerprint pattern based on the fingerprint image of the object. For example, when a finger applies pressure to the pulse wave sensor 610, the contact position between the finger and the pulse wave sensor 610 is pressed more than other positions of the finger, such that the distance between the ridges or valleys of the fingerprint at the contact position between the finger and the pulse wave sensor 610 is relatively greater than other positions. If the distance between the ridges or valleys of the fingerprint at a predetermined position of the finger is greater than or equal to a predetermined threshold as compared with other positions, then the sensor position acquirer 640 may acquire the position as the sensor position.

[0103] In addition, the sensor position acquirer 640 may acquire sensor position information based on an object image captured by an external image capturing device. The external image capturing device may be a camera module installed at a fixed position or a camera module installed in a mobile device (such as a smart phone, etc.). For example, once the external image capturing device captures an image of a finger in contact with the pulse wave sensor 610, the sensor position acquirer 640 may receive the image of the finger through a communication module installed in the device 600 for estimating biological information.

[0104] By analyzing the relative position between the pulse wave sensor 610 and the finger based on the image of the finger, the sensor position acquirer 640 may acquire the position of the finger in contact with the pulse wave sensor 610 as the sensor position. In addition, if an external image capturing device having a function of acquiring the sensor position acquires sensor position information by capturing an image of the finger, the sensor position acquirer 640 may receive the sensor position information from the external image capturing device through the communication module.

[0105] The processor 630 may guide the user to the contact position of the object based on the acquired sensor position information, or may acquire an oscillogram by selecting some of the plurality of pulse wave signals acquired by the plurality of channels.

[0106] For example, if the pulse wave sensor 610 has a single channel including one light source and one detector, the processor 630 may guide the user to the contact position of the object based on the blood vessel position of the object and the sensor position information.

[0107] Figure 7AIt is a diagram explaining an example of a pulse wave sensor 610 having a single channel 72. The processor 630 can display a finger image on a display, and can display the blood vessel position 71 of the finger superimposed on the position of the channel 72 of the pulse wave sensor 610 to guide the user to place the blood vessel of the finger on the channel 72.

[0108] In another example, if the pulse wave sensor 610 has multiple channels for measuring multiple pulse wave signals at multiple points of an object, the processor 630 can determine an appropriate channel based on the blood vessel position of the object and the sensor position.

[0109] Figure 7B It is a diagram explaining an example of a pulse wave sensor 610 having multiple channels 73 for measuring multiple pulse wave signals at multiple points of a finger. Each of the channels ch1, ch2, and ch3 can include a light source and a detector. For example, when a request for estimating blood pressure is received, the processor 630 can select one of the multiple channels 73 by using the blood vessel position 71 of the finger and the sensor position information, and can drive the selected channel. For example, the processor 630 can drive channel ch3, which is the closest to the blood vessel position 71, among the channels ch1, ch2, and ch3 of the pulse wave sensor 610. Optionally, the processor 630 can obtain pulse wave signals from each of the channels ch1, ch2, and ch3 by driving the multiple channels 73 of the pulse wave sensor 610 simultaneously or sequentially, and can select channel ch3, which is located closest to the blood vessel position 71, as the channel for estimating blood pressure.

[0110] In addition, if the pulse wave sensor 610 has multiple channels, the processor 630 can select one channel from the multiple channels based on a pulse wave signal corresponding to a predetermined position of the object or a pulse wave signal having a noise level less than or equal to a predetermined level, and can obtain an oscillogram based on the pulse wave signal obtained through the selected channel. For example, among the multiple pulse wave signals measured through the multiple channels, the processor 630 can determine a pulse wave signal corresponding to a specific position of the finger, or can determine a pulse wave signal having a noise level less than or equal to a predetermined level by determining the noise of the pulse wave signal, and can obtain an oscillogram by selecting at least one of the multiple channels based on the pulse wave signal.

[0111] Figure 8 It is a flowchart showing a method for estimating biological information according to an exemplary embodiment. Figure 8 The method is an example of a method for estimating biological information executed by the above-described devices 100 and 600 for estimating biological information, which has been described in detail above, and thus will be briefly described below.

[0112] At 810, a device for estimating biological information may measure a pulse wave signal from an object through a pulse wave sensor. For example, the pulse wave sensor may have a single channel to measure the pulse wave signal at a specific point of the object, or may have multiple channels to measure multiple pulse wave signals at multiple points of the object.

[0113] At 820, a device for estimating biological information may measure the force applied between the object and the pulse wave sensor through a force sensor.

[0114] At 830, a device for estimating biological information may obtain an oscillogram by using the pulse wave signal and the force. For example, if a pulse wave sensor with multiple channels acquires multiple pulse wave signals in 810, the device for estimating biological information may select one channel from the multiple channels based on the pulse wave signal corresponding to a predetermined position of the object or the pulse wave signal having a noise level less than or equal to a predetermined level, and may obtain an oscillogram based on the pulse wave signal obtained through the selected channel.

[0115] At 840, a device for estimating biological information may determine a first mean arterial pressure (MAP) based on the obtained oscillogram. For example, the device for estimating biological information may determine the force value at the maximum amplitude point in the obtained oscillogram as the first MAP.

[0116] At 850, a device for estimating biological information may extract additional information in the interval before the point of the first MAP of the oscillogram. For example, the device for estimating biological information may determine a peak point in the interval before the first MAP, and may extract at least one of the amplitude and force at the determined peak point, the amplitude and force at the valley point between the peak point and the point of the first MAP, and the amplitude at the point of the first MAP as additional information. If there is no peak point in the interval before the first MAP, the device for estimating biological information may determine the maximum amplitude point in the interval before the valley point immediately preceding the first MAP.

[0117] At 860, a device for estimating biological information may obtain a second MAP based on a first MAP and additional information. For example, the device for estimating biological information may obtain the second MAP by applying a ratio between at least two additional information items to the first MAP. For example, the device for estimating biological information may obtain the second MAP by applying a ratio between the magnitude at a point on the first MAP and the magnitude at a peak point to the first MAP, or by applying a ratio between the magnitude at a point on the first MAP and the magnitude at a valley point to the first MAP. In another example, the device for estimating biological information may obtain the second MAP based on a ratio between at least two additional information items and a value obtained by subtracting the force value at the peak point from the first MAP. For example, the device for estimating biological information may obtain the second MAP by applying a ratio between the magnitude at a point on the first MAP and the magnitude at the peak point to the value obtained by subtracting the force value at the peak point from the first MAP, or may obtain the second MAP by applying a ratio between the magnitude at a point on the first MAP and the magnitude at the valley point to the value obtained by subtracting the force value at the peak point from the first MAP. However, the above examples are only described for illustrative purposes and the embodiments are not limited thereto.

[0118] At 870, the device for estimating biological information may estimate biological information based on the obtained second MAP. For example, the device for estimating biological information may estimate biological information by using a biological information estimation model based on the first MAP and / or the second MAP.

[0119] Figure 9 is a flowchart showing a method for estimating biological information according to another exemplary embodiment. Figure 9 The method of is an example of a method for estimating biological information that can be executed by the above-described device 100 and device 600 for estimating biological information, and the method for estimating biological information has been described in detail above and will thus be briefly described below.

[0120] At 910, when an object contacts a pulse wave sensor, the device for estimating biological information may obtain sensor position information of the pulse wave sensor located on the object. For example, the device for estimating biological information may obtain the sensor position information based on a fingerprint image obtained by a fingerprint sensor when the object contacts the pulse wave sensor, or may obtain the sensor position information based on an image of the object obtained by an external image capturing device (or an image capturing device (such as, for example, a camera)).

[0121] At 920, a device for estimating biological information may guide a user to a contact position of an object based on sensor position information. For example, if a pulse wave sensor has a single channel, the device for estimating biological information may guide the user to the contact position of the object based on the vascular position of the object and the sensor position information.

[0122] The device for estimating biological information may measure a pulse wave signal of the object from the contact position at 930, may measure a force applied between the object and the pulse wave sensor at 940, and may obtain an oscillogram by using the measured pulse wave signal and force at 950.

[0123] At 960, the device for estimating biological information may determine a first mean arterial pressure (MAP) based on the obtained oscillogram.

[0124] At 970, the device for estimating biological information may extract additional information in an interval before a point of the first MAP of the oscillogram.

[0125] At 980, the device for estimating biological information may obtain a second MAP based on the first MAP and the additional information. For example, the device for estimating biological information may obtain the second MAP by applying a ratio between at least two additional information items to the first MAP. Optionally, the device for estimating biological information may obtain the second MAP indicating a degree of underestimation based on a ratio between at least two additional information items and a value obtained by subtracting a force value at a peak point from the first MAP.

[0126] At 990, the device for estimating biological information may estimate biological information based on the obtained second MAP. For example, the device for estimating biological information may estimate biological information by using a biological information estimation model based on the first MAP and / or the second MAP.

[0127] Figure 10 is a block diagram illustrating an example of an electronic device including a device for estimating biological information according to an example embodiment.

[0128] In one example embodiment, the electronic device 1000 may include, for example, various types of wearable devices (e.g., smart watches, smart wristbands, smart glasses, smart headphones, smart rings, smart patches, and smart necklaces), as well as mobile devices (such as smart phones, tablet PCs, etc.), or home appliances or various Internet of Things (IoT) devices based on IoT technology (e.g., home IoT devices).

[0129] Refer to Figure 10, the electronic device 1000 may include a sensor device 1010, a processor 1020, an input device 1030, a communication interface 1040, a camera assembly 1050, an output device 1060, a storage device 1070, and a power supply 1080. All components of the electronic device 1000 may be integrally installed in a specific device, or may be distributed in two or more devices.

[0130] The sensor device 1010 may include the pulse wave sensors 110 and / or 610 of the aforementioned devices 100 and 600 for estimating biological information, and the force sensors 120 and / or 620. The pulse wave sensor 110 and / or 610 may include one or more light sources 111 and 611 and one or more detectors 112 and / or 612, and when an object comes into contact with the pulse wave sensor 110 and / or 610, the pulse wave sensor 110 and / or 610 may obtain a pulse wave signal from the object. The force sensors 120 and / or 620 may be disposed at the upper or lower end of the pulse wave sensor 110 and / or 610, and may measure the contact force applied between the object and the pulse wave sensor 110 and / or 610.

[0131] The sensor device 1010 may include sensors for performing various other functions (e.g., a gyro sensor, a Global Positioning System (GPS), etc.).

[0132] The processor 1020 may execute a program stored in the storage device 1070 to control components connected to the processor 1020, and may perform various data processing or calculations. The processor 1020 may include a main processor (e.g., a Central Processing Unit (CPU) or an Application Processor (AP), etc.) and an auxiliary processor that can operate independently of the main processor or in combination with the main processor (e.g., a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a Sensor Hub Processor, or a Communication Processor (CP), etc.).

[0133] The processor 1020 may include the processors of the aforementioned devices 100 and 600 for estimating biological information. For example, in response to a user's request to estimate biological information, the processor 1020 may send a control signal to the sensor device 1010, and may estimate biological information by using the pulse wave signal and the force signal received from the sensor device 1010. The processor 1020 may estimate biological information by using an oscillogram of the object, and may send the estimated biological information to an external device through the communication interface 1040.

[0134] For example, the processor 1020 may obtain an oscillogram by using a pulse wave signal and a force signal, may determine a first mean arterial pressure (MAP) based on the obtained oscillogram, may extract additional information in an interval before a point of the first MAP of the oscillogram, may obtain a second MAP based on the first MAP and the additional information, and may estimate biometric information based on the obtained second MAP.

[0135] In addition, the processor 1020 may determine a peak point in an interval before the first MAP, and may extract at least one of an amplitude and a force at the determined peak point, an amplitude and a force at a valley point between the peak point and the point of the first MAP, and an amplitude at the point of the first MAP as additional information, and may obtain a second MAP based on a ratio between at least two additional information items and the first MAP.

[0136] The input device 1030 may receive commands and / or data to be used by each component of the electronic device 1000 from a user or the like. The input device 1030 may include, for example, a microphone, a mouse, a keyboard, or a digital pen (e.g., a stylus).

[0137] The communication interface 1040 may support establishing a direct (e.g., wired) communication channel and / or a wireless communication channel between the electronic device 1000 and other electronic devices, a server, or the sensor device 1010 within a network environment, and support communication via the established communication channel. The communication interface 1040 may include one or more communication processors that can operate independently of the processor 1020 and support direct communication and / or wireless communication.

[0138] The communication interface 1040 may include a wireless communication module (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module, etc.) and / or a wired communication module (e.g., a local area network (LAN) communication module, a power line communication (PLC) module, etc.). These various types of communication modules may be integrated into a single chip, or may be separately implemented as multiple chips. The wireless communication module may identify and authenticate the electronic device 1000 in a communication network by using user information (e.g., an international mobile subscriber identity (IMSI)) stored in a user identification module.

[0139] The camera assembly 1050 may capture a still image or a moving image. The camera assembly 1050 may include a lens assembly having one or more lenses, an image sensor, an image signal processor, and / or a flash. The lens assembly included in the camera assembly 1050 may collect light emitted from an object to be imaged.

[0140] The output device 1060 may output data generated or processed by the electronic device 1000 visually and / or non-visually. The output device 1060 may include a sound output device, a display device, an audio module, and / or a haptic module.

[0141] The sound output device may output a sound signal to the outside of the electronic device 1000. The sound output device may include a speaker and / or a receiver. The speaker may be used for general purposes (such as playing multimedia or playing a recording), and the receiver may be used for incoming calls. The receiver may be implemented separately from the speaker or as part of the speaker.

[0142] The display device may visually provide information to the outside of the electronic device 1000. The display device may include, for example, a display, a holographic device, or a projector, and a control circuit for controlling the device. The display device may include a touch circuit adapted to detect a touch and / or a sensor circuit (e.g., a pressure sensor) adapted to measure the intensity of a force caused by the touch.

[0143] The audio module may convert a sound into an electrical signal and vice versa. The audio module may obtain a sound via an input device, or may output a sound via a sound output device and / or a speaker and / or headphones of another electronic device directly or wirelessly connected to the electronic device 1000.

[0144] The haptic module may convert an electrical signal into a mechanical stimulus (e.g., vibration, movement) or an electrical stimulus that can be recognized by a user through touch or kinesthesia. The haptic module may include, for example, a motor, a piezoelectric element, and / or an electrical stimulator.

[0145] The storage device 1070 may store driving conditions for driving the sensor device 1010 and various data for other components of the electronic device 1000. The various data may include, for example, software and input data and / or output data for commands related thereto. The storage device 1070 may include a volatile memory and / or a non-volatile memory.

[0146] The power supply 1080 may manage the power supplied to the electronic device 1000. The power supply 1080 may be implemented as part of a power management integrated circuit (PMIC). The power supply 1080 may include a battery, which includes a non-rechargeable primary battery, a rechargeable secondary battery, and / or a fuel cell.

[0147] Figure 11 and Figure 12 is a diagram showing an example of the structure of a device for estimating biometric information according to an exemplary embodiment.

[0148] Referring to Figure 11, the wristwatch wearable device 1100 may include a device for estimating biological information according to an exemplary embodiment (e.g., the electronic device 1000 shown in Figure 10 ), and may include a main body and a wristband. A display is provided on the front surface of the main body, and various application screens including time information, received message information, etc. may be displayed. A sensor device 1110 may be provided on the rear surface of the main body to measure a pulse wave signal and a force signal for estimating biological information. However, the position of the sensor device 1110 is not limited thereto.

[0149] Referring to Figure 12 , the mobile device 1200 (such as a smart phone) may include a device for estimating biological information according to an exemplary embodiment (e.g., the electronic device 1000 shown in Figure 10 ).

[0150] The mobile device 1200 may include a housing and a display panel. The housing may form the exterior of the mobile device 1200. The housing has a first surface, and the display panel and the cover glass may be sequentially provided on the first surface, and the display panel may be exposed to the outside through the cover glass. A sensor device 1210, a camera module (or camera assembly), and / or an infrared sensor, etc. may be provided on the second surface of the housing. However, the position of the sensor device 1210 is not limited thereto. When the user sends a request for estimating biological information by executing an application installed in the mobile device 1200, etc., the mobile device 1200 may estimate biological information by using the sensor device 1210, and may provide the estimated biological information value to the user as an image and / or sound.

[0151] Referring to Figure 13 , the ear-worn device 1300 may include a device for estimating biological information according to an exemplary embodiment (e.g., the electronic device 1000 shown in Figure 10 ).

[0152] The ear-worn device 1300 may include a main body and an earband. The user may wear the ear-worn device 1300 by hanging the earband on the user's auricle. Depending on the type of the ear-worn device 1300, the earband may be omitted. The main body may be inserted into the external auditory canal. A sensor device 1310 may be installed in the main body. However, the position of the sensor device 1310 is not limited thereto. The ear-worn device 1300 may provide the component estimation result to the user as sound, or may send the estimation result to an external device (such as a mobile device, a tablet PC, a personal computer, etc.) through a communication module provided in the main body.

[0153] The disclosure may be provided as computer-readable code written on a computer-readable recording medium. The computer-readable recording medium may be any type of recording device that stores data in a computer-readable manner.

[0154] Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage, and carrier waves (e.g., data transmission through the Internet). The computer-readable recording media may be distributed over multiple computer systems connected to a network so that the computer-readable code is written therein and executed therefrom in a decentralized manner. Those of ordinary skill in the art to which the disclosure pertains can easily derive the functional programs, codes, and code segments for implementing the disclosed functions.

[0155] According to an example embodiment, at least one of the components, elements, modules, and units represented by blocks in the drawings may be implemented as various numbers of hardware, software, and / or firmware structures that perform the corresponding functions described above. According to an example embodiment, at least one of these components may use a direct circuit structure (such as a memory, a processor, a logic circuit, a look-up table, etc.) that can perform the corresponding function under the control of one or more microprocessors or other control devices. In addition, at least one of these components may be embodied as a part of a module, program, or code that includes one or more executable instructions for performing the specified logical function and is executed by one or more microprocessors or other control devices. In addition, at least one of these components may include a processor (such as a central processing unit (CPU), a microprocessor, etc.) that performs the corresponding function or may be implemented by the processor. Two or more of these components may be combined into a single component that performs all the operations or functions of the combined two or more components. In addition, at least a part of the function of at least one of these components may be performed by another of these components. The functional aspects of the above example embodiments may be implemented in algorithms executed on one or more processors. In addition, the components represented by blocks or processing steps may employ any number of existing technologies for electronic configuration, signal processing, and / or control, data processing, etc.

[0156] Although the disclosure has been described with reference to the disclosed example embodiments, it will be apparent to those of ordinary skill in the art that various changes and modifications can be made thereto without departing from the spirit and scope of the disclosure as set forth in the appended claims.

Claims

1. A device for estimating biological information, the device comprising: A pulse wave sensor configured to measure a pulse wave signal from an object; A force sensor configured to measure a force applied between the object and the pulse wave sensor; And A processor configured to: Obtain an oscillogram by using the pulse wave signal and the force, Determine a first mean arterial pressure MAP based on the obtained oscillogram, Wherein, the processor is further configured to: Determine a peak point in an interval before the first mean arterial pressure MAP in the oscillogram, and Extract at least one of the following items in the oscillogram as additional information: the amplitude at the determined peak point, the force at the determined peak point, the amplitude at a valley point between the peak point and the point of the first mean arterial pressure MAP, the force at the valley point between the peak point and the point of the first mean arterial pressure MAP, and the amplitude at the point of the first mean arterial pressure MAP, Wherein, the processor is further configured to: Extract at least two pieces of additional information, Obtain a second mean arterial pressure MAP by applying a ratio between the values of the at least two pieces of additional information to the first mean arterial pressure MAP, and Estimate biological information based on the obtained second mean arterial pressure MAP.

2. The device according to claim 1, wherein The pulse wave sensor includes: At least one optical sensor configured to emit light onto the object; and At least one detector configured to detect light scattered or reflected from the object.

3. The device according to claim 1, wherein, The processor is further configured to: determine the force value at the maximum amplitude point in the obtained oscillogram as the first mean arterial pressure MAP.

4. The device according to claim 1, wherein, The processor is further configured to: based on determining that there is no peak point in the interval before the first mean arterial pressure MAP, determine the maximum amplitude point in the interval before the valley point as the peak point, where the valley point is the last valley point before the first mean arterial pressure MAP.

5. The device according to claim 1, wherein The at least two pieces of additional information include the amplitude at the point of the first mean arterial pressure MAP and the amplitude at the peak point, Wherein, the processor is further configured to: obtain a second mean arterial pressure MAP by applying a ratio between the amplitude at the point of the first mean arterial pressure MAP and the amplitude at the peak point to the first mean arterial pressure MAP.

6. The device according to claim 1, wherein, The at least two pieces of additional information include the amplitude at the point of the first mean arterial pressure MAP and the amplitude at the valley point, Wherein, the processor is further configured to: obtain a second mean arterial pressure MAP by applying a ratio between the amplitude at the point of the first mean arterial pressure MAP and the amplitude at the valley point to the first mean arterial pressure MAP.

7. The device according to claim 1, wherein The processor is further configured to: estimate biological information based on the second mean arterial pressure MAP by using a biological information estimation model.

8. The device according to claim 1, wherein, The processor is further configured to: Extract at least three pieces of additional information including the force at the peak point, and Obtain a second mean arterial pressure MAP based on a ratio between the values of at least two of the at least three pieces of additional information and also based on a first value obtained by subtracting the value of the force at the peak point from the first mean arterial pressure MAP.

9. The device according to claim 8, wherein The processor is further configured to: obtain a second mean arterial pressure MAP by applying a ratio between the amplitude at the point of the first mean arterial pressure MAP and the amplitude at the peak point to the first value.

10. The device according to claim 8, wherein, The processor is further configured to: obtain a second mean arterial pressure (MAP) by applying a ratio between the amplitude at a point of the first MAP and the amplitude at a trough to a first value.

11. The apparatus according to claim 8, wherein, The processor is further configured to: estimate biometric information based on the first MAP and the second MAP by using a biometric information estimation model.

12. The device according to any one of claims 1 to 11 further comprises: A sensor position acquirer, configured to acquire sensor position information of a pulse wave sensor, where the sensor position information indicates the position of the pulse wave sensor on an object in contact with the pulse wave sensor wherein the processor is further configured to: perform control based on the sensor position information to guide a user to the contact position of the object.

13. The device according to claim 12, wherein, The sensor position acquirer includes: a fingerprint sensor, configured to acquire a fingerprint image of an object in contact with the pulse wave sensor wherein the sensor position acquirer is further configured to: acquire the sensor position information based on the fingerprint image acquired by the fingerprint sensor.

14. The device according to claim 12, wherein, The sensor position acquirer is further configured to: acquire the sensor position information based on an image of an object in contact with the pulse wave sensor, the image being acquired by an external image capturing device.

15. The device according to any one of claims 1 to 11, wherein, The pulse wave sensor has a plurality of channels for measuring pulse wave signals at a plurality of points of an object. wherein the processor is further configured to: select at least one channel from the plurality of channels based on a pulse wave signal corresponding to a predetermined position of an object in contact with the pulse wave sensor or based on a pulse wave signal having a noise level less than or equal to a predetermined level, and obtain an oscillogram based on the pulse wave signal obtained through the selected at least one channel.

16. The device according to any one of claims 1 to 11, wherein The biometric information includes at least one of the following: blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, pressure index, fatigue level, skin age, and skin elasticity.

17. A method for estimating biometric information, the method comprising: measuring a pulse wave signal from an object by using a pulse wave sensor; measuring a force applied between the object and the pulse wave sensor; obtaining an oscillogram by using the pulse wave signal and the force; determining a first mean arterial pressure (MAP) based on the obtained oscillogram wherein the method further includes: determining a peak point in an interval before the first MAP in the oscillogram, and extracting at least one of the following items in the oscillogram as additional information: the amplitude at the determined peak point, the force at the determined peak point, the amplitude at a trough between the peak point and the point of the first MAP, the force at a trough between the peak point and the point of the first MAP, and the amplitude at the point of the first MAP. wherein the method further includes: extracting at least two pieces of additional information; obtaining a second mean arterial pressure (MAP) by applying a ratio between the values of the at least two pieces of additional information to the first MAP; and estimating biometric information based on the obtained second MAP.

18. The method according to claim 17, wherein, The step of determining the first MAP includes: determining the force value at the point of the maximum amplitude in the obtained oscillogram as the first MAP.

19. The method according to claim 17, wherein, The steps of extracting additional information include: determining a peak point as the maximum amplitude point in the interval before a valley point based on determining that there is no peak point in the interval before the first mean arterial pressure (MAP), where the valley point is the last valley point before the first mean arterial pressure (MAP).

20. The method according to claim 17, wherein, The steps of estimating biological information include: estimating the biological information based on a second mean arterial pressure (MAP) by using a biological information estimation model.

21. The method according to claim 17, wherein, The extraction steps include: extracting at least three additional information including the force at the peak point. Among them, the steps of obtaining the second mean arterial pressure (MAP) include: obtaining the second mean arterial pressure (MAP) based on the ratio between the values of at least two of the at least three additional information and also based on the value obtained by subtracting the value of the force at the peak point from the first mean arterial pressure (MAP).

22. The method according to claim 21, wherein, The steps of estimating biological information include: estimating biological information based on the first mean arterial pressure (MAP) and the second mean arterial pressure (MAP) by using a biological information estimation model.

23. The method according to any one of claims 17 to 22 further includes: obtaining sensor position information of a pulse wave sensor, the sensor position information indicating the position of the pulse wave sensor on an object in contact with the pulse wave sensor; and performing control based on the sensor position information to guide the user to the contact position of the object.

24. An electronic device includes: a device for estimating biological information; and an output device configured to output a processing result of the device for estimating biological information, wherein the device for estimating biological information includes: a pulse wave sensor configured to measure a pulse wave signal from an object; a force sensor configured to measure the force applied between the object and the pulse wave sensor; and a processor configured to: obtain an oscillogram by using the pulse wave signal and the force, determine a first mean arterial pressure (MAP) based on the obtained oscillogram, wherein the processor is further configured to: determine a peak point in the interval before the first mean arterial pressure (MAP) in the oscillogram, and extract at least one of the following in the oscillogram as additional information: the amplitude at the determined peak point, the force at the determined peak point, the amplitude at the valley point between the peak point and the point of the first mean arterial pressure (MAP), the force at the valley point between the peak point and the point of the first mean arterial pressure (MAP), and the amplitude at the point of the first mean arterial pressure (MAP), wherein the processor is further configured to: extract at least two additional information, obtain a second mean arterial pressure (MAP) based on the ratio between the values of the at least two additional information and the first mean arterial pressure (MAP), and estimate biological information based on the obtained second mean arterial pressure (MAP).

25. The electronic device according to claim 24, wherein, The electronic device includes at least one of a wristwatch wearable device, an ear-worn device, and a mobile device.

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