Patent Description:
General techniques for extracting cardiovascular characteristics, such as blood pressure, and the like, without using a pressure cuff include a pulse transit time (PTT) method and a pulse wave analysis (PWA) method.

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, or the like. The blood ejected from the left ventricle causes reflection at areas of large branches, such as the renal arteries and the iliac arteries, and the reflection affects the shape of the pulse wave or body pressure wave measured at the peripheral part of the body. Thus, by analyzing this shape, arterial stiffness, arterial age, aortic artery pressure waveform, or the like, can be inferred.

The pulse wave velocity (PWV) method is a method of extracting cardiovascular characteristics, such as arterial stiffness, blood pressure, or the like, by measuring a pulse wave transmission time. In this method, a delay (a pulse transit time (PTT)) between an R-peak (left ventricular contraction interval) of an electrocardiogram (ECG) and a peak of a PPG signal of a finger or the radial artery is measured by measuring the ECG and PPG signals of the peripheral part of the body, and by calculating a velocity at which the blood from the heart reaches the peripheral part of the body by dividing an approximate length of the arm by the PTT
<CIT> discloses a method and an apparatus for estimating bio-information. Said apparatus for estimating bio-information includes a sensor part comprising a pulse wave sensor array, a load sensor and a processor. The pulse wave sensor array is hereby configured to detect a pulse wave signal when an object contacts a contact surface of the sensor part, and the load sensor is configured to detect a first contact load applied by the object to the contact surface. Further, the processor is configured to obtain a contact load distribution of the contact surface based on the pulse wave signal, obtain a second contact load at each position of the contact surface based on the contact load distribution and the first contact load and estimate bio-information based on the second contact load and the pulse wave signal. The estimating the bio-information includes setting a region of interest based on at least one of a blood vessel distribution of the object, an arrangement of a pulse wave sensor array, a specific position of the contact surface of the sensor and the second contact load at each position of the contact surface. Moreover, in one example of <CIT>, it is disclosed that once a pulse wave signal is detected at each position, the quality of each pulse wave signal is evaluated and a region of interest is set based on the evaluation. Hereby, the quality of each pulse wave signal is e.g. evaluated based on a maximum amplitude value of each pulse wave signal, a difference between a maximum amplitude value and a minimum amplitude value, an average amplitude value etc.
<CIT> relates to a bio-signal acquiring apparatus that includes a sensor part and a signal processor. The sensor part hereby comprises a bio-signal sensor, a load sensor, and an ultrasonic sensor array. The bio-signal sensor is configured to detect a bio-signal of an object that comes into contact with the sensor part, the load sensor is configured to detect a contact load of the object and the ultrasonic sensor array is configured to detect a contact load distribution of the object. The signal processor is configured to obtain a contact load of the object at a region of interest based on the contact load and the contact load distribution, and configured to output the contact load of the object at the region of interest and the bio-signal. In this context, <CIT> also mentions setting a region of interest by considering a distribution of blood vessels of an object. <CIT> provides a personal hand-held monitor (PHHM) which comprises a signal acquisition device for acquiring signals which can be used to derive a measurement of a subject's blood pressure (BP), the signal acquisition device being integrated with a personal hand-held computing device (PHHCD). The signal acquisition device comprises a blood flow occlusion means adapted to be pressed against one side only of a body part or to have one side only of a body part pressed against it, a means for measuring the pressure applied by or to the body part, and a means for detecting the flow of blood through the body part in contact with the blood flow occlusion means. The blood flow occlusion means comprises at least part of an external surface of the PHHM and wherein the pressure is sensed by means of a flexible and essentially incompressible gel in which is immersed a pressure sensor. The pressure sensor is adapted to provide electrical signals to the processor of the PHHCD.

According to an aspect of an example embodiment, an apparatus for estimating bio-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 bio-information at each sensor position based on each of the plurality of pulse wave signals; and estimate second bio-information based on a blood vessel position of the object, each sensor position, and the first bio-information at each sensor position.

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

The position sensor may include a fingerprint sensor configured to obtain a fingerprint image, and the position sensor is further configured to obtain the sensor position information based on the fingerprint image obtained by the fingerprint sensor based on the object being in contact with the pulse wave sensor.

Based on the object being in contact with the pulse wave sensor, the position sensor is further configured to obtain the sensor position information based on pre-defined measurement position information of the pulse wave sensor.

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

The apparatus may include a blood vessel position sensor which includes an ultrasonic sensor configured to transmit an ultrasonic wave to the object and receive a signal reflected from the object, and obtain the blood vessel position information of the object based on an ultrasonic image obtained by the ultrasonic sensor.

The processor is further configured to generate a calibration graph by plotting estimated bio-information values at each sensor position against a relative distance of each sensor position from the blood vessel position of the object; and based on performing curve fitting, obtain a final estimated bio-information value based on the calibration graph.

The processor is further configured to obtain a bio-information value at a point, corresponding to the blood vessel position of the object in the calibration graph, as the second bio-information.

The apparatus may 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.

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

The bio-information comprises one or more of blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, stress index, fatigue level, skin age, and skin elasticity.

A method of estimating bio-information of a user may include measuring a plurality of pulse wave signals from an object; 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 bio-information at each sensor position based on each of the plurality of pulse wave signals; and estimating second bio-information based on a blood vessel position of the object, each sensor position, and the first bio-information at each sensor position.

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

The estimating of the second bio-information comprises obtaining a bio-information value at a point, corresponding to the blood vessel position of the object in the calibration graph, as the second estimated bio-information value.

The method may include measuring a force or a pressure applied by the object to the pulse wave sensor.

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

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.

Based on a difference between first bio-information values at each sensor position, the processor is further configured to determine the one of the plurality of virtual blood vessel positions as the blood vessel position of the object.

A virtual blood vessel position is set for each of a plurality of groups which are pre-classified based on the difference between the first bio-information values at each sensor position obtained from a plurality of users.

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.

The processor is further configured to generate a calibration graph by plotting the first bio-information values at each sensor position against a relative distance of each sensor position from the blood vessel position of the object; and obtain a second bio-information value based on the calibration graph.

The processor is further configured to obtain a bio-information value at a point, corresponding to the blood vessel position of the object in the calibration graph, as the second bio-information value.

The processor may generate an oscillogram based on each of the plurality of pulse wave signals and the force or the pressure measured by the force sensor or the pressure sensor; and estimate the first bio-information at each sensor position by using the oscillogram.

A method of estimating bio-information of a user may 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 bio-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 bio-information at each sensor position; and estimating second bio-information based on the blood vessel position of the object, each sensor position, and the first bio-information at each sensor position.

The determining of the one of a plurality of virtual blood vessel positions as the blood vessel position of the object comprises, based on a difference between first bio-information values at each sensor position, determining the one of the plurality of virtual blood vessel positions as the blood vessel position of the object.

The determining of the one of a plurality of virtual blood vessel positions as the blood vessel position of the object comprises 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.

The estimating of the second bio-information comprises generating a calibration graph by plotting the first bio-information values at each sensor position against a relative distance of each sensor position from the determined blood vessel position of the object; and obtaining a second bio-information value based on the calibration graph.

The estimating of the first bio-information at each sensor position comprises generating an oscillogram based on each of the pulse wave signals and the force or the pressure; and estimating the first bio-information at each sensor position by using the oscillogram.

Details of example embodiments are included in the following detailed description and drawings. Advantages and features of the present disclosure, and a method of achieving the same will be more clearly understood from the following embodiments described in detail with reference to the accompanying drawings.

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. Also, the singular forms of terms are intended to include the plural forms of the terms as well, unless the context clearly indicates otherwise. It will be further understood that when an element is referred to as "comprising" another element, the element is intended not to exclude one or more other elements, but to further include one or more other elements, unless explicitly described to the contrary. In the following description, terms such as "unit" and "module" indicate a unit for processing at least one function or operation and the unit may be implemented by using hardware, software, or a combination thereof.

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

Various embodiments of the apparatus for estimating bio-information may be mounted in terminals such as a smart phone, a tablet personal computer (PC), a desktop computer, a laptop computer, etc., wearable devices, and the like. In this case, examples of the wearables devices 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 devices are not limited thereto.

<FIG> are block diagrams illustrating an apparatus for estimating bio-information according to embodiments of the present disclosure.

Referring to <FIG>, the apparatus <NUM> for estimating bio-information includes a pulse wave sensor <NUM>, a position sensor <NUM>, and a processor <NUM>.

The pulse wave sensor <NUM> measures a photoplethysmography (PPG) signal (hereinafter referred to as a "pulse wave signal") from an object. In this case, the object may be a body area which may be in contact with the pulse wave sensor <NUM>, and may be a body part at which pulse waves may be easily measured based on PPG signals. For example, the object may be a finger where blood vessels are densely located, but the object is not limited thereto and may be an area on the wrist that is adjacent to the radial artery, or a distal portion of the body, such as an upper portion of the wrist, toes, etc., where veins or capillaries are located.

The pulse wave sensor <NUM> may include one or more light sources for emitting light onto the object, and one or more light receivers which are disposed at positions spaced apart from the light sources by a predetermined distance and detect light scattered or reflected from the object. The light sources may emit light of different wavelengths. For example, the light sources may emit light of an infrared wavelength, a green wavelength, a blue wavelength, a red wavelength, a white wavelength, and the like. The light sources may include a light emitting diode (LED), a laser diode (LD), a phosphor, and the like, but are not limited thereto. Further, the light receivers 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.

The pulse wave sensor <NUM> may have a single channel including a light source and a light receiver, so as to measure a pulse wave signal at a specific point of the object. Alternatively, the pulse wave sensor <NUM> may have multiple channels to measure a plurality of pulse wave signals at multiple points of the object. Each of the channels of the pulse wave sensor <NUM> may be formed in a pre-defined shape such as a circular shape, an oval shape, a fan shape, etc., so that pulse wave signals may be measured at multiple points of the object. Each channel of the pulse wave sensor <NUM> may include one or more light sources and one or more light receivers. Further, each channel may include two or more light sources to emit light of a plurality of wavelengths. Alternatively, the pulse wave sensor <NUM> may be configured to measure a plurality of pulse wave signals in a predetermined area of the object. For example, the pulse wave sensor <NUM> 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.

A position sensor <NUM> may obtain sensor position information when the object is in contact with the pulse wave sensor <NUM>, such as position information on the object being in contact with the pulse wave sensor <NUM>. At least some functions of the position sensor <NUM> may be integrated with the processor <NUM>.

For example, the position sensor <NUM> may obtain the sensor position information based on object images captured by an external image capturing device. The external image capturing device may be a camera module installed at a fixed location or a camera module mounted in a mobile device such as a smartphone, and the like. For example, once the external image capturing device captures an image of the object being in contact with the pulse wave sensor <NUM>, the position sensor <NUM> may receive the image of the object through a communication interface mounted in the apparatus <NUM> for estimating bio-information.

By analyzing relative positions of the pulse wave sensor <NUM> and the object based on the image of the object, the position sensor <NUM> may obtain the position of the object, being in contact with the pulse wave sensor <NUM>, as a sensor position. Further, once the 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 <NUM> may receive the sensor position information through the communication interface.

In another example, the position sensor <NUM> may include a fingerprint sensor for acquiring a fingerprint image of the object in contact with the pulse wave sensor <NUM>. The fingerprint sensor may be disposed at an upper end or a lower end of the pulse wave sensor <NUM>. The position sensor <NUM> may estimate a sensor position by analyzing a change in a fingerprint pattern based on the fingerprint image of the object. For example, when a finger applies pressure to the pulse wave sensor <NUM>, a contact position of the finger, which is in contact with the pulse wave sensor <NUM>, is pressed against the pulse wave sensor <NUM> more than as compared to other positions of the finger, such that a distance between ridges or valleys of a fingerprint of the contact position between the finger and the pulse wave sensor <NUM> is larger than other positions. If a distance between ridges or valleys of the fingerprint at a position of the finger is greater than or equal to a predetermined threshold value when compared to other positions, the position sensor <NUM> may obtain the position as a sensor position.

In yet another example, when the pulse wave sensor <NUM> has multiple channels to measure a plurality of pulse wave signals at the same time, the position sensor <NUM> may obtain a preset measurement position to measure each pulse wave signal as a sensor position.

The processor <NUM> may be electrically connected to the pulse wave sensor <NUM>, and may control the pulse wave sensor <NUM> in response to a request for estimating bio-information. The processor <NUM> may control the pulse wave sensor <NUM> to obtain pulse wave signals at a plurality of measurement positions of the object. In this case, if the pulse wave sensor <NUM> has a single channel including one light source and one receiver, the processor <NUM> may control the pulse wave sensor <NUM> a plurality of number of times to obtain pulse wave signals at a plurality of positions of the object.

The processor <NUM> may estimate bio-information based on the plurality of pulse wave signals obtained at the plurality of sensor positions of the object. Further, the processor <NUM> may obtain final bio-information based on bio-information obtained at each sensor position, each sensor position information, and blood vessel position information of the object.

Referring to <FIG>, an apparatus <NUM> for estimating bio-information according to another embodiment includes the pulse wave sensor <NUM>, the position sensor <NUM>, the processor <NUM>, and a force/pressure sensor <NUM>. Redundant descriptions of the position sensor <NUM> and the processor <NUM> will be omitted.

When a user places an object on the pulse wave sensor <NUM> and increases or decreases a pressing force/pressure to induce a change in pulse wave amplitude, the force/pressure sensor <NUM> may measure the force/pressure exerted between the pulse wave sensor <NUM> and the object. The force/pressure sensor <NUM> may include a force sensor including a strain gauge, and the like, a force sensor array, an air bladder type pressure sensor, a pressure sensor in combination with a force sensor and an area sensor, and the like.

The processor <NUM> may estimate bio-information at each sensor position based on the pulse wave signals, obtained at a plurality of sensor positions by the pulse wave sensor <NUM>, and the force/pressure obtained by the force/pressure sensor <NUM>. In this case, once the force/pressure sensor <NUM> obtains a contact force between the object and the pulse wave sensor <NUM>, the processor <NUM> may convert the contact force into contact pressure by using a conversion model which defines a correlation between the contact force and the contact pressure. Alternatively, the processor <NUM> may obtain contact pressure by using the contact force and area information of the pulse wave sensor <NUM>. Furthermore, if the force/pressure sensor <NUM> is implemented as a force sensor for measuring a contact force and an area sensor for measuring a contact area, the processor <NUM> may obtain contact pressure based on the contact force, measured by the force sensor, and the contact area measured by the area sensor.

Referring to <FIG>, an apparatus <NUM> for estimating bio-information according to yet another embodiment includes the pulse wave sensor <NUM>, the position sensor <NUM>, the processor <NUM>, and a blood vessel position sensor <NUM>. The pulse wave sensor <NUM>, the position sensor <NUM>, and the processor <NUM> are described above in detail, such that redundant descriptions thereof will be omitted. The force/pressure sensor <NUM> of <FIG> may be included in the apparatus <NUM> for estimating bio-information according to an embodiment of the present disclosure.

The blood vessel position sensor <NUM> may obtain blood vessel position information of an object at a time when a user is registered. Alternatively, in response to a user's request for estimating bio-information, the blood vessel position sensor <NUM> may check whether there is blood vessel position information of the user's object or whether it is time to calibrate the information; and if there is no blood vessel position information of the object or it is time to calibrate the information, the blood vessel position obtainer <NUM> may obtain blood vessel position information of the object from the user. At least some functions of the blood vessel position sensor <NUM> may be integrated with the processor <NUM>. Examples of obtaining blood vessel positions by the blood vessel position sensor <NUM> will be described below, but the present disclosure is not limited to these examples.

For example, the blood vessel position sensor <NUM> may directly receive input of blood vessel position information from a user. In this case, the blood vessel position sensor <NUM> may display an image of the object on a display, and may provide an interface for the user to directly designate a blood vessel position on the object image by using an input means (e.g., finger, touch pen, etc.).

In another example, the blood vessel position sensor <NUM> may receive images, which are captured by an external image capturing device for capturing optical images, ultrasonic images, magnetic resonance imaging (MRI) images, photoacoustic images, etc., through the communication interface, and may obtain blood vessel position information of the object by analyzing the received images. Alternatively, if the external image capturing device analyzes a blood vessel position while capturing the images, the blood vessel position sensor <NUM> may receive the blood vessel position information of the obj ect through the communication interface.

In yet another example, the blood vessel position sensor <NUM> may include, for example, an ultrasonic sensor which transmits an ultrasonic wave to the object, and receives a reflection wave from the object. The blood vessel position sensor <NUM> may obtain blood vessel position information based on ultrasonic images obtained by the ultrasonic sensor.

<FIG> is an example of a configuration of a processor of the apparatus for estimating bio-information illustrated in <FIG>. <FIG> and <FIG> are diagrams explaining an example of estimating blood pressure using oscillometry. <FIG> and <FIG> are diagrams explaining an example of calibrating blood pressure based on blood vessel positions of an object.

Referring to <FIG>, a processor <NUM> according to an embodiment of the present disclosure includes an oscillogram generator <NUM>, a bio-information estimator <NUM>, and a bio-information calibrator <NUM>.

The oscillogram generator <NUM> may generate an oscillogram for each sensor position based on pulse wave signals, measured at each sensor position by the pulse wave sensor <NUM>, and contact pressure.

For example, referring to <FIG> and <FIG>, the oscillogram generator <NUM> may extract a peak-to-peak point of the pulse wave signal waveform by subtracting a negative (-) amplitude value in3 from a positive (+) amplitude value in2 of a waveform envelope in1 at each measurement time of the pulse wave signal, and may obtain the oscillogram (OW) by plotting the peak-to-peak amplitude at each measurement time against the contact pressure value at a corresponding time and by performing polynomial curve fitting.

The bio-information estimator <NUM> may extract characteristic points from the oscillogram for each sensor position, and may estimate bio-information for each sensor position by using the extracted characteristic points. For example, the bio-information estimator <NUM> 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., <NUM> to <NUM>) to a maximum amplitude value MA, and the like.

The bio-information estimator <NUM> may determine, for example, the contact pressure value MP at a point, corresponding to the maximum amplitude value, as mean arterial pressure (MAP); and may determine contact pressure values DP and SP at the left and right points, corresponding to amplitude values having a preset ratio to the maximum amplitude value, as diastolic blood pressure (DBP) and systolic blood pressure (SBP), respectively. Alternatively, the bio-information estimator <NUM> may independently estimate the MAP, DBP, and SBP by applying each of the extracted contact pressure values MP, DP, and SP to a pre-defined blood pressure estimation model. In this case, the blood pressure estimation model may be expressed in the form of various linear or non-linear combination functions, such as addition, subtraction, division, multiplication, logarithmic value, regression equation, and the like, with no particular limitation.

The bio-information calibrator <NUM> may obtain final bio-information based on the bio-information generated for each sensor position by the bio-information estimator <NUM>. For example, the bio-information calibrator <NUM> may generate a calibration graph by plotting estimated bio-information values for each sensor position against a relative distance of each sensor position from the blood vessel position of the object, and by fitting the curve. Further, the bio-information calibrator <NUM> may obtain a final estimated bio-information value based on the generated calibration graph.

<FIG> illustrates, in (<NUM>), an example in which a first sensor position L1 is a tip of a fingernail, a second sensor position L2 is located at a distance of <NUM> from the first sensor position L1, and a blood vessel 61a of a finger <NUM> is located between the first sensor position L1 and the second sensor position L2. In this case, a relative distance of both the first sensor position L1 and the second sensor position L2 from the blood vessel position 61a is <NUM>.

Referring to (<NUM>) of <FIG>, the bio-information calibrator <NUM> may locate the blood vessel position 61a at "<NUM>" on the X axis, and then may plot an estimated blood pressure value of the first sensor position L1 at distances of "-<NUM>" and "+<NUM>" from the distance of "<NUM>" on the X axis, and may plot an estimated blood pressure value of the second sensor position L2 at distances of "+<NUM>" and"-<NUM>" on the X axis. Then, upon plotting the estimated blood pressure values of the first and second sensor positions L1 and L2, the bio-information calibrator <NUM> 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 the curve fitting. Upon generating the calibration graph 62a, the bio-information estimator <NUM> may obtain a blood pressure value at a blood vessel position, i.e., a point 63a corresponding to "<NUM>" on the X axis in the calibration graph 62a, as a final blood pressure value.

<FIG> illustrates, in (<NUM>), an example in which a blood vessel 61b of the finger <NUM> is located at a distance of <NUM> from the first sensor position L1 and at a distance of <NUM> from the second sensor position L2, in which case a relative distance of the first sensor position L1 from the blood vessel position 61a is <NUM>, and a relative distance of the second sensor position L2 therefrom is <NUM>. As illustrated in (<NUM>) of <FIG>, the bio-information calibrator <NUM> may locate the blood vessel position 61b at "<NUM>" on the X axis, and then may plot an estimated blood pressure value of the first sensor position L1 at distances of "-<NUM>" and "+<NUM>" on the X axis, and may plot an estimated blood pressure value of the second sensor position L2 at distances of "+<NUM>" and"-<NUM>" on the X axis. Then, the bio-information calibrator <NUM> may perform curve fitting to generate a calibration graph 62b showing a relatively smooth curve. In this case, the bio-information estimator <NUM> may obtain a blood pressure value at a blood vessel position, i.e., a point 63b corresponding to "<NUM>" on the X axis in the calibration graph 62b, as a final blood pressure value.

<FIG> illustrates, in (<NUM>), an example in which a blood vessel 61c of the finger <NUM> is superimposed on the first sensor position L1, and a relative distance of the first sensor position L1 from the blood vessel position 61a is <NUM> and a relative distance of the second sensor position L2 therefrom is <NUM>. As illustrated in (<NUM>) of <FIG>, the bio-information calibrator <NUM> may generate a calibration graph 62c by plotting an estimated blood pressure value of the first sensor position L1 at "<NUM>" on the X axis and an estimated blood pressure value of the second sensor position L2 at distances of "+<NUM>" and"-<NUM>" on the X axis, and by performing curve fitting. In this case, the bio-information estimator <NUM> may obtain a blood pressure value at a blood vessel position, i.e., a point 63c corresponding to "<NUM>" on the X axis in the calibration graph 62c, as a final blood pressure value.

<FIG> is a block diagram illustrating an apparatus for estimating bio-information according to another embodiment of the present disclosure. <FIG> is a diagram illustrating an example of a configuration of a processor of <FIG>. <FIG> are diagrams explaining an example of calibrating blood pressure based on a virtual blood vessel position.

Referring to <FIG>, the apparatus <NUM> for estimating bio-information according to another embodiment includes a pulse wave sensor <NUM>, a position sensor <NUM>, a processor <NUM>, and a virtual blood vessel position information <NUM>. Embodiments of the pulse wave sensor <NUM> and the position sensor <NUM> are described in detail above.

Once pulse wave signals are obtained at a plurality of positions of an object, the processor <NUM> may obtain final bio-information based on the pre-defined virtual blood vessel position information <NUM>.

The virtual blood vessel position information <NUM> may be obtained from a plurality of users by an external device or the apparatus <NUM> for estimating bio-information. The virtual blood vessel position information <NUM> may be pre-stored in a storage of the apparatus <NUM> for estimating bio-information. The virtual blood vessel position information <NUM> may include a plurality of virtual blood vessel positions for each object, in which case one virtual blood vessel position may be set for each of a plurality of groups which are classified according to predetermined criteria.

For example, referring to <FIG>, by measuring pulse wave signals at each of the first sensor position L1 and the second sensor position L2 of a user's finger <NUM>, and by moving virtual blood vessel positions from position <NUM> to position <NUM>, a calibration graph may be generated for each of the virtual blood vessel positions and a final blood pressure value may be estimated, as described above. By using data remaining after excluding abnormal data based on the generated calibration graph or the estimated final blood pressure value, a plurality of groups may be classified as illustrated in <FIG>. For example, as illustrated in <FIG>, a plurality of groups may be classified based on differences between the estimated blood pressure at the first sensor position L1 and the estimated blood pressure at the second sensor position L2. However, the example of classifying the groups is not limited thereto, and the groups may be classified by various linear/non-linear combinations, including a ratio between the estimated blood pressure at the first sensor position L1 and the estimated blood pressure at the second sensor position L2.

Referring to <FIG>, a virtual blood vessel position may be defined for each group. For example, in Group <NUM>, the estimated pressure value of the second sensor position L2 is much greater than the estimated pressure value of the first sensor position L1, such that a position (a) superimposed on the second sensor position L2 may be defined as the virtual blood vessel position for Group <NUM>. In this manner, a position (b) of the object may be defined as the virtual blood vessel position for Group <NUM>, a position (c) may be defined as the virtual blood vessel position for Group <NUM>, and a position (d) may be defined as the virtual blood vessel position for Groups <NUM> and <NUM>.

Referring to <FIG>, a processor <NUM> according to an embodiment includes an oscillogram generator <NUM>, a bio-information estimator <NUM>, a blood vessel position determiner <NUM>, and a bio-information calibrator <NUM>.

The oscillogram generator <NUM> may generate an oscillogram for each sensor position based on pulse wave signals, measured by the pulse wave sensor <NUM> at each sensor position, and contact pressure.

The bio-information estimator <NUM> 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.

The blood vessel position determiner <NUM> may determine an optimal blood vessel position among a plurality of virtual blood vessel positions, based on the virtual blood vessel position information <NUM> and the bio-information for each sensor position. For example, the blood vessel position determiner <NUM> may calculate, as pre-defined group classification criteria, a difference value between the estimated blood pressure of the first sensor position L1 and the estimated blood pressure of the second sensor position L2, and may determine a group to which the calculated difference value belongs. Further, based on the virtual blood vessel position information <NUM>, the blood vessel position determiner <NUM> may determine a virtual blood vessel position, corresponding to the determined group, as an optimal (or improved) blood vessel position of a user's object.

Once the blood vessel position determiner <NUM> determines the optimal blood vessel position of the object, the bio-information calibrator <NUM> may generate a calibration graph based on a relative distance between the optimal blood vessel position and each of the first and second sensor positions L1 and L2 as described above, and may obtain an estimated value, corresponding to the blood vessel position in the calibration graph, as final bio-information.

According to this embodiment, bio-information may be estimated accurately even when accurate blood vessel information may not be obtained from a user's object, and the apparatus may be manufactured in a compact size as there is no need for a separate sensor.

<FIG> is a block diagram illustrating an apparatus for estimating bio-information according to yet another embodiment of the present disclosure.

Referring to <FIG>, an apparatus <NUM> for estimating bio-information according to another embodiment includes a pulse wave sensor <NUM>, a position sensor <NUM>, a force/pressure sensor <NUM>, a processor <NUM>, a storage <NUM>, an output interface <NUM>, and a communication interface <NUM>. Various embodiments of the pulse wave sensor <NUM>, the position sensor <NUM>, the force/pressure sensor <NUM>, and the processor <NUM> are described in detail above, such that redundant description thereof will be omitted.

The storage <NUM> may store a variety of information required for estimating bio-information. For example, the storage <NUM> may store pulse wave signals measured by the pulse wave sensor <NUM>, object images, fingerprint images, and sensor position information which are obtained by the position sensor <NUM>, force/pressure values obtained by the force/pressure sensor <NUM>, and the like. Further, the storage <NUM> may store processing results of the processor <NUM>, such as an estimated bio-information value for each sensor position, a calibration graph, a final estimated bio-information value, and the like. In addition, the storage <NUM> may store blood vessel position information of a user's object, and user characteristic information such as a user's age, gender, health condition, and the like. Moreover, the storage <NUM> may store virtual blood vessel position information and the like. However, the information is not limited thereto.

The storage <NUM> may include at least one storage medium of a flash memory type memory, a hard disk type memory, a multimedia card micro type 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, and the like, but is not limited thereto.

The output interface <NUM> may output the pulse wave signals measured by the pulse wave sensor <NUM>, the object images, the fingerprint images, and the sensor position information which are obtained by the position sensor <NUM>, the force/pressure values obtained by the force/pressure sensor <NUM>, and/or the processing results of the processor <NUM>. In this case, along with the visual display of the information on a display, the output interface <NUM> may provide the information by a non-visual method using a speaker, a haptic device, and the like.

For example, the output interface <NUM> may output the measured pulse wave signal in the form of graphs. Further, the output interface <NUM> may visually display an estimated blood pressure value of a user by using various visual methods, such as by changing color, line thickness, font, and the like, based on whether the estimated blood pressure value falls within or outside a normal range. Alternatively, upon comparing the estimated blood pressure value with a previous estimation history, if it is determined that the estimated blood pressure value is abnormal, the output interface <NUM> may provide a warning message and the like, as well as guide information on a user's action such as food information that the user should be careful about, related hospital information, and the like. The output interface <NUM> may guide a user on a contact position of an object based on the position information obtained by the position sensor <NUM>. In addition, based on the force/pressure obtained by the force/pressure sensor <NUM>, the output interface <NUM> may guide force/pressure to be applied by the object to the pulse wave sensor <NUM>.

The communication interface <NUM> may communicate with an external device by using wired or wireless communication techniques under the control of the processor <NUM>, and may transmit and receive various data to and from the external device. For example, the communication interface <NUM> may transmit a bio-information estimation result to the external device, and may receive a variety of reference information required for estimating 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 measuring device, a smartphone, a tablet PC, a desktop computer, a laptop computer, and the like.

In this case, examples of the communication techniques 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, <NUM> communication, <NUM> communication, <NUM> communication, and the like. However, this is merely exemplary and is not intended to be limiting.

<FIG> is a flowchart illustrating a method of estimating bio-information according to an embodiment of the present disclosure. The method of <FIG> is an example of a method of estimating bio-information which is performed by the aforementioned apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information, which are described above in detail, and thus will be briefly described below.

The apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may measure a plurality of pulse wave signals at a plurality of positions of a user's object by using a pulse wave sensor in operation <NUM>. While the user places the object on the pulse wave sensor, the user may change contact pressure to induce a change in pulse wave amplitude. In this case, a change in contact force/contact pressure may be obtained by a force/pressure sensor.

Then, while the pulse wave signals are obtained at the plurality of positions of the object, the apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may obtain a position of the pulse wave sensor on the object in operation <NUM>. For example, when the object is in contact with the pulse wave sensor, sensor position information may be obtained based on an image of the object, captured by an external image capturing device, or a fingerprint image obtained by fingerprint sensor mounted in the apparatuses.

Subsequently, the apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may estimate bio-information at each sensor position based on the pulse wave signals obtained at each sensor position in operation <NUM>. For example, the apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may generate an oscillogram based on the contact force/contact pressure, obtained while the pulse wave signals are measured, and the pulse wave signals of each sensor, and may estimate bio-information by using the generated oscillogram.

Next, the apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may estimate final bio-information based on blood vessel position information of the object, the sensor position information, and bio-information at each sensor position in operation <NUM>. For example, the apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may generate a calibration graph by calculating a relative distance of each sensor position from the blood vessel position, plotting the bio-information of each sensor position against the relative distance, and performing curve fitting. Further, upon generating the calibration graph, the apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may obtain bio-information at a point, corresponding to the blood vessel position in the calibration graph, as the final bio-information.

Then, the apparatuses <NUM>, <NUM>, <NUM>, and <NUM> for estimating bio-information may output a bio-information estimation result in operation <NUM>. The apparatuses <NUM>, <NUM>, and <NUM> for estimating bio-information may provide a user with information, such as the estimated bio-information values, a warning, measurements, a bio-information estimation history, etc., by using a display, a speaker, a haptic device, and the like.

<FIG> is a flowchart illustrating a method of estimating bio-information according to another embodiment of the present disclosure. The method of <FIG> is an example of a method of estimating bio-information which is performed by the aforementioned apparatuses <NUM> and <NUM> for estimating bio-information, which is described above in detail, and thus will be briefly described below.

The apparatuses <NUM> and <NUM> for estimating bio-information may measure a plurality of pulse wave signals at a plurality of positions of a user's object by using a pulse wave sensor in operation <NUM>, and may obtain a position of the pulse wave sensor on the object in operation <NUM>.

Then, the apparatuses <NUM> and <NUM> for estimating bio-information may estimate bio-information at each sensor position based on the pulse wave signals obtained at each sensor position in operation <NUM>.

Subsequently, the apparatuses <NUM> and <NUM> for estimating bio-information may determine one of a plurality of virtual blood vessel positions as an optimal (or improved) blood vessel position of the object in operation <NUM>. For example, the apparatus <NUM> for estimating bio-information may determine a group to which a difference value between an estimated blood pressure value at the first sensor position and an estimated blood pressure value at the second sensor position belongs, and may determine a virtual blood vessel position of the determined group as the optimal blood vessel position of the user's object.

Next, the apparatuses <NUM> and <NUM> for estimating bio-information may estimate final bio-information based on the determined optimal vessel position information of the object, the sensor position information, the bio-information at each sensor position in operation <NUM>, and may output a bio-information estimation result in operation <NUM>.

<FIG> is a diagram illustrating an example of a wearable device. Various embodiments of the aforementioned apparatuses for estimating bio-information may be mounted in the wearable device.

Referring to <FIG>, the wearable device <NUM> includes a main body <NUM> and a strap <NUM>.

The strap <NUM>, which is connected to both ends of the main body <NUM>, may be flexible so as to be bent around a user's wrist. The strap <NUM> may be composed of a first strap and a second strap which are separated from each other. Respective ends of the first strap and the second strap are connected to the main body <NUM>, and the other ends thereof may be connected to each other via a connecting means. In this case, the connecting means may be formed as magnetic connection, Velcro connection, pin connection, and the like, but is not limited thereto. Further, the strap <NUM> is not limited thereto, and may be integrally formed as a non-detachable band.

In this case, air may be injected into the strap <NUM>, or the strap <NUM> may be provided with an air bladder, so that the strap <NUM> may have elasticity according to a change in pressure applied to the wrist, and may transmit the change in pressure of the wrist to the main body <NUM>.

A battery may be embedded in the main body <NUM> or the strap <NUM> to supply power to the wearable device <NUM>.

Furthermore, the main body <NUM> may include a sensor part <NUM> mounted on one side thereof. The sensor part <NUM> may include a pulse wave sensor for measuring pulse wave signals. The pulse wave sensor may include a light source for emitting light onto skin of a wrist or a finger, a light receiver such as a CIS optical sensor for detecting light scattered or reflected from the wrist or the finger, a photodiode, and the like. The pulse wave sensor may have multiple channels for measuring pulse wave signals at multiple points of the wrist or the finger, and each of the channels may include a light source and a light receiver, and may include a plurality of light sources for emitting light of different wavelengths. In addition, the sensor part <NUM> may further include a force/pressure sensor for measuring force/pressure between the wrist or finger and the sensor part <NUM>. Moreover, the sensor part <NUM> may further include a fingerprint sensor, an ultrasonic sensor, and the like, which may be stacked on top of each other.

A processor may be mounted in the main body <NUM>. The processor may be electrically connected to modules mounted in the wearable device <NUM>. Based on the pulse wave signals and the contact force/pressure, which are measured by the sensor part <NUM> at a plurality of measurement positions of the object, the processor may estimate blood pressure at each measurement position using oscillometry based on the pulse wave signals, measured at a plurality of measurement positions of the object, and the contact force/pressure, and may estimate final blood pressure by calibrating the estimated blood pressure at each measurement position based on the blood vessel position of the object. In this case, the blood vessel position of the object may be an actual blood vessel position of the object which is obtained based on user input, an ultrasonic image, an MRI image, an optical image, and the like. Alternatively, if it is difficult to obtain an actual blood vessel position of the object, the blood vessel position may be an optimal blood vessel position which is selected according to predetermined criteria from among pre-defined virtual blood vessel positions for a plurality of users.

Further, the main body <NUM> may include a storage which stores reference information for estimating blood pressure and performing various functions of the wearable device <NUM>, and information processed by various modules thereof.

In addition, the main body <NUM> may include a manipulator <NUM> which is provided on one side surface of the main body <NUM>, and receives a user's control command and transmits the received control command to the processor. The manipulator <NUM> may have a power button to input a command to turn on/off the wearable device <NUM>.

Further, a display for outputting information to a user may be mounted on a front surface of the main body <NUM>. The display may have a touch screen for receiving touch input. The display may receive a user's touch input and transmit the touch input to the processor, and may display processing results of the processor.

Moreover, the main body <NUM> may include a communication interface for communication with an external device. The communication interface may transmit a blood pressure estimation result to the external device, such as a user's smartphone.

<FIG> is a diagram illustrating an example of a smart device. In this case, the smart device may include a smartphone, a tablet PC, and the like. The smart device may include various embodiments of the aforementioned apparatuses for estimating bio-information.

Referring to <FIG>, the smart device <NUM> includes a main body <NUM> and a pulse wave sensor <NUM> mounted on one surface of the main body <NUM>. For example, the pulse wave sensor <NUM> may include one or more light sources <NUM> disposed at predetermined positions thereof. The one or more light sources <NUM> may emit light of different wavelengths. In addition, a plurality of light receivers <NUM> may be disposed at predetermined distances from the light sources <NUM>. However, this is merely an example, and the pulse wave sensor <NUM> may have various shapes as described above. Further, a force/pressure sensor for measuring a contact force/pressure of a finger may be mounted in the main body <NUM> at a lower end of the pulse wave sensor <NUM>.

Moreover, a display may be mounted on a front surface of the main body <NUM>. The display may visually output a blood pressure estimation result, a health condition evaluation result, and the like. The display may include a touch screen, and may receive information input through the touch screen and transmit the information to a processor.

The main body <NUM> may include an image sensor <NUM> as illustrated in <FIG>. The image sensor <NUM> may capture various images, and may obtain, for example, a fingerprint image of a finger being in contact with the pulse wave sensor <NUM>. In addition, when an image sensor based on the CIS technology is mounted in the light receiver <NUM> of the pulse wave sensor <NUM>, the image sensor <NUM> may be omitted.

The processor may estimate blood pressure based on the blood vessel position of the object and sensor position information obtained when the object is in contact with the sensor, as described above.

The embodiments of the present disclosure can be implemented by computer-readable code written on a non-transitory computer-readable medium that is executed by a processor. The non-transitory computer-readable medium may be any type of recording device in which data is stored in a computer-readable manner.

Claim 1:
An apparatus (<NUM>) for estimating bio-information of a user, the apparatus (<NUM>) comprising:
a pulse wave sensor (<NUM>) configured to measure (<NUM>) a plurality of pulse wave signals from an object of the user;
a position sensor (<NUM>) configured to obtain (<NUM>) 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 (<NUM>) measuring each of the plurality of pulse wave signals; and
a processor (<NUM>) configured to:
estimate (<NUM>) first bio-information at each sensor position based on each of the plurality of pulse wave signals;
generate a calibration graph (<NUM>) by plotting the estimated first bio-information values at each sensor position against a relative distance of each sensor position from a blood vessel position (<NUM>) of the object;
based on performing curve fitting, obtain (<NUM>) a second estimated bio-information value based on the calibration graph (<NUM>); and
obtain (<NUM>) a bio-information value at a point, corresponding to the blood vessel position (<NUM>) of the object in the calibration graph (<NUM>), as the second bio-information.