KR20220107909A - Apparatus and method for estimating blood pressure - Google Patents

Abstract

An apparatus for estimating blood pressure is disclosed. According to one embodiment, an apparatus may include a sensor part for measuring a PPG signal from a subject; and a processor that detects the position of a notch point based on the maximum point of the secondary unexplored node of the PPG signal, obtains a first value and a second value from the two sections divided by the notch point of the PPG signal, obtains a pulse-related feature value based on the first value and the second value, and estimates blood pressure based on the change rate of the pulse-related feature value obtained compared to a reference pulse-related feature value.

Description

Apparatus and method for estimating blood pressure {APPARATUS AND METHOD FOR ESTIMATING BLOOD PRESSURE}

It relates to a blood pressure estimation technique, and it relates to a technique for estimating blood pressure using incision points.

Recently, research on IT-medical convergence technology that combines IT technology with medical technology is being conducted due to the aging population structure, rapidly increasing medical expenses, and a shortage of professional medical service personnel. In particular, the monitoring of the health of the human body is not limited to being performed only in fixed places such as hospitals, but it is expanded to the field of mobile healthcare, which monitors the health of users anytime and anywhere in daily life such as home and office. is becoming The types of biosignals that indicate an individual's health status include ECG (electrocardiography), PPG (photoplethysmogram), and EMG (electromyography) signals. Signal sensors are being developed. In particular, in the case of the PPG sensor, it is possible to estimate the blood pressure of the human body by analyzing the shape of the pulse wave that reflects the state of the cardiovascular system.

According to the results of PPG biosignal-related research, the entire PPG signal is composed of superimposed propagation waves from the heart toward the end of the body and reflection waves returning from the end of the body. In addition, it is known that information for estimating blood pressure can be obtained by extracting various features related to traveling waves or reflected waves.

Detecting the position of the notch in the biosignal. Through this, an apparatus and method for estimating blood pressure are provided.

According to one aspect, the blood pressure estimating apparatus detects the position of the notch point based on the sensor unit for measuring the PPG signal from the subject, the maxima and minima of the second differential signal of the PPG signal, and the notch point of the PPG signal as a reference The processor may include a processor for obtaining a first value and a second value from both sections divided by , and estimating the blood pressure based on a rate of change of the acquired pulse pressure-related characteristic value compared to the reference pulse pressure characteristic value.

The processor determines the pair of maxima and minima of the second derivative signal, calculates the difference between the second derivative of the maxima and the second derivative of the minima in the pair of maxima and minima, and based on the difference The position of the notch point can be detected.

The processor may detect a time point of a pair of maximal points having the largest difference between the second derivative value of the maximum point and the second differential value of the minimum point as the position of the notch point.

The processor determines whether the number of pairs of the maximum and minimum points of the second differential signal of the PPG signal is less than or equal to a predetermined number, or the difference between the second differential value of the second differential value of the calculated pair of maximum and minimum points and the second differential value of the minimum is less than or equal to a threshold value. In this case, it is possible to request the user to re-measure the PPG signal.

The processor determines at least one of the period of the PPG signal and the time until the first minimum point of the second differential signal of the PPG signal as a reference time, and sets a time range for detecting the position of the notch based on the determined reference time. can

In the time range, a value obtained by multiplying a reference time by a first constant may be a starting point, and a value obtained by multiplying a reference time by a second constant may be used as an end point.

The pulse pressure-related feature value may include a ratio between the first value and the second value.

The first value and the second value are any one of the PPG signal area in the corresponding section, the measurement time of each section, the PPG signal amplitude data of each section, and the intensity of the signal obtained by differentiating the PPG signal of each section by the nth order may include.

The amplitude data of the PPG signal is either the maximum value of the PPG signal amplitude within each section, the average value of the PPG signal amplitude within each section, and the maximum value or the average value within each section of the n-squared value of the PPG signal amplitude. may include.

The intensity of a signal obtained by differentiating the PPG signal by the nth order may be the sum of signals obtained by taking the absolute value of a signal obtained by differentiating the PPG signal by the nth order within each section.

The processor estimates the user's pulse pressure based on the rate of change and the reference pulse pressure obtained at the time of calibration, extracts the mean blood pressure-related feature value from the PPG signal, and estimates the mean blood pressure based on the extracted mean blood pressure-related feature value; The user's systolic blood pressure or diastolic blood pressure may be estimated based on the estimated average blood pressure and pulse pressure.

The processor determines the user's systolic blood pressure based on the change rate of the mean blood pressure at the time of blood pressure estimation compared to the reference mean blood pressure value at the time of calibration, the rate of change of the estimated pulse pressure compared to the reference pulse pressure value at the time of calibration, and the reference systolic blood pressure or the reference diastolic blood pressure at the time of calibration. Blood pressure or diastolic blood pressure can be estimated.

In this case, the processor calculates a rate of change of the pulse pressure based on a rate of change of the obtained pulse pressure-related characteristic value compared to the obtained reference pulse pressure-related characteristic value, and based on the rate of change of the obtained average blood pressure-related characteristic value compared to the reference average blood pressure-related characteristic value. to calculate the rate of change in mean blood pressure.

The processor is configured to: a change rate of the acquired pulse pressure-related feature value compared to the reference pulse pressure-related feature value, a change rate of the acquired cardiac output-related feature value compared to the reference cardiac output-related feature value, and the acquired total vascular resistance compared to the reference total vascular resistance-related feature value The user's systolic blood pressure or diastolic blood pressure may be estimated based on the change rate of the related feature value.

A pulse pressure estimation method according to an aspect includes the steps of measuring a PPG signal from a subject, obtaining a second differential signal of the PPG signal, and detecting the position of the notch based on the maximum and minimum points of the second differential signal of the PPG signal. step, obtaining a first value and a second value from both sections divided based on the notch point of the PPG signal, obtaining a pulse pressure-related feature value based on the first value and the second value, reference pulse pressure-related The method may include estimating blood pressure based on a rate of change of the acquired pulse pressure-related feature value compared to the feature value.

The step of detecting the position of the notch point is the step of determining a pair of the maximum and minimum points of the second differential signal of the PPG signal, and the second differential value of the maximum and the second differential value of the minimum in the pair of maximum and minimum points. calculating the difference between , and detecting the position of the notch based on the difference.

The step of detecting the position of the notch point based on the difference may include detecting a pair of maximal points having the largest difference between the second derivative value of the maximal point and the second derivative value of the minimal point as the position of the notch point.

In addition, in the pulse pressure estimation method, the number of pairs of maximum and minimum points of the second differential signal of the determined PPG signal is less than or equal to a predetermined number, or the difference between the second differential value of the second differential value of the calculated pair of maximum and minimum points and the second differential value of the minimum point is If it is less than the threshold, the method may further include the step of requesting the user to re-measure the PPG signal.

In addition, the pulse pressure estimation method determines at least one of the period of the PPG signal and the time to the first minimum point of the second differential signal of the PPG signal as the reference time, and the time range for detecting the position of the notch point based on the determined reference time It may further include the step of setting

The obtaining of the pulse pressure-related feature value based on the first value and the second value may include obtaining a ratio between the first value and the second value as the pulse pressure-related feature value.

The blood pressure change can be estimated by stably detecting the position of the notch of the biosignal in an environment where there is a non-ideal human contact state or noise, and deriving a feature value using the detected position of the notch.

1 is a block diagram of an apparatus for estimating blood pressure according to an exemplary embodiment.
2 is a block diagram of an apparatus for estimating blood pressure according to another exemplary embodiment.
3A is a block diagram of a processor configuration according to an embodiment.
3B illustrates a PPG signal obtained from a subject.
3C is a diagram of a user interface that guides a user to input a blood pressure value measured from an external device and indicates an input position of the blood pressure value.
4A is a diagram for explaining an example of detecting a position of a notch point;
4B to 4D are diagrams for explaining the acquisition of pulse pressure-related feature values based on the first value and the second value of both sections divided based on the notch point;
5 is a flowchart of a method for estimating blood pressure according to an embodiment;
6 illustrates an embodiment of the step 530 of detecting the notch point location of FIG. 5 .
7 illustrates a wearable device according to an exemplary embodiment.
8 illustrates a smart device according to an embodiment.

The details of other embodiments are included in the detailed description and drawings. Advantages and features of the described technology, and how to achieve them, will become apparent with reference to the embodiments described below in detail in conjunction with the drawings. Like reference numerals refer to like elements throughout.

Terms such as first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. The singular expression includes the plural expression unless the context clearly dictates otherwise. Also, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated. In addition, terms such as “…unit” and “module” described in the specification mean a unit that processes at least one function or operation, which may be implemented as hardware or software, or may be implemented as a combination of hardware and software.

Hereinafter, embodiments of an apparatus and method for estimating blood pressure will be described in detail with reference to the drawings.

1 is a block diagram of an apparatus for estimating blood pressure according to an exemplary embodiment.

Various embodiments of the blood pressure estimating apparatus 100 may be mounted on terminals such as a smart phone, a tablet PC, a desktop PC, a notebook PC, and a wearable device. In this case, the wearable device may be implemented as a wrist watch type, a bracelet type, a wristband type, a ring type, a glasses type, or a headband type. However, the present invention is not limited thereto and may be mounted on hardware manufactured in various forms to be used in specialized medical institutions.

Referring to FIG. 1 , the blood pressure estimating apparatus 100 includes a sensor unit 110 and a processor 120 .

The sensor unit 110 may measure at least one biosignal from the user's subject. An example of the biosignal may be a photoplethysmography (PPG) signal. The sensor unit 110 may measure other biosignals such as ECG.

In this case, the subject may be a region of the wrist surface adjacent to the radial artery, a region such as a wrist through which capillary or venous blood passes, or a peripheral region of the human body such as fingers, toes, and ears, which are regions with high blood vessel density in the human body.

The sensor unit 110 may include a light source that irradiates light to the subject, and a detector that detects light emitted after light irradiated to the subject by the light source is scattered or reflected by the body tissue of the subject. In this case, the light source may include at least one of a light emitting diode (LED), a laser diode, and a phosphor, but is not limited thereto. The light source may be one or plural. For example, the light source may include an LED array. The detector may include a photodiode, a photo transistor, a photodiode array, a phototransistor array, an image sensor (eg, a CMOS image sensor), and the like.

The sensor unit 110 may further include additional components necessary for measuring biosignals. For example, additional components such as an amplifier that amplifies the electrical signal output by the detector that detects light, an analog/digital converter that converts the electrical signal output by the detector or the electrical signal output by the amplifier into a digital signal, etc. It may be further included in the unit 110 . Also, when the sensor unit 110 measures the ECG signal, a plurality of electrodes may be included in the sensor unit 110 . Hereinafter, the PPG signal will be described as an example of the biosignal, but each embodiment is not limited thereto.

The processor 120 may be electrically, mechanically, or connected to the sensor unit 110 through wired/wireless communication. The processor 120 may control the sensor unit 110 and receive a PPG signal from the sensor unit 110 .

When the PPG signal is received, the processor 120 may perform pre-processing such as filtering to remove noise or amplifying the PPG signal. For example, when the PPG signal is received, the processor 120 performs band pass filtering of 0.4 to 10 Hz using a band pass filter, thereby reducing noise from the PPG signal received from the sensor unit 110 . can be removed The bandpass filter may be a digital filter implemented in software code, executable by a processor. As another example, the bandpass filter may be an analog filter, and in this case, the PPG signal measured by the sensor unit 110 may be transmitted to the processor 120 after passing through the bandpass filter (not shown).

In addition, it is also possible for the processor 120 to perform correction of the PPG signal through reconstruction of the PPG signal based on the Fast Fourier Transform. However, the present invention is not limited thereto, and may vary according to various measurement environments such as computing performance or measurement accuracy of the device, purpose of estimating blood pressure or pulse pressure, the user's measurement site, the temperature, humidity of the subject, and the temperature of the sensor unit. Pre-processing can be performed.

Meanwhile, the processor 120 may generate a representative waveform of the PPG signal measured by the sensor unit 110 . The PPG signal includes repetitive pulses related to changes in the amount of blood flowing through the blood vessels, and the shapes of each waveform may be slightly different from each other.

For example, the processor 120 may obtain an ensemble average of a plurality of waveforms as a representative waveform. As another example, a waveform having the highest signal to noise ratio (SNR) among the plurality of waveforms may be determined as the representative waveform. However, the present invention is not limited thereto, and various embodiments for determining the representative waveform are possible. In this case, the representative waveform determination by the processor 120 may be performed after noise removal of the PPG signal described above. The processor 120 may acquire a cardiovascular-related characteristic by using the representative waveform. In the following description, the PPG signal used by the processor 120 to obtain the blood pressure-related feature value may mean a representative waveform of the PPG signal.

The processor 120 may estimate the pulse pressure based on the PPG signal, and may estimate the blood pressure based on the estimated pulse pressure. For example, the PPG signal is secondarily differentiated to derive a second differential signal, and a pulse pressure-related feature value (hereinafter referred to as a pulse pressure feature value) can be obtained based on the maximum and minimum points of the derived second differential signal. have.

For example, the processor 120 detects the position of a dicrotic notch in the PPG signal based on the maximum and minimum points of the second differential signal of the PPG signal, and pulse pressure characteristics based on the detected position of the notch point. value can be obtained.

For example, the processor 120 may determine a pair of a maximum and a minimum in a predetermined time range of the second differential signal of the PPG signal. The pair of maxima and minima may be determined as a maxima and minima adjacent to each other among a plurality of maxima and minima. In addition, the difference in amplitude between the maximum and minimum points for each determined pair of maximum and minimum points may be calculated, and the position of the notch point may be detected based on the difference in amplitude. For example, the processor 120 may detect a time point of a pair of maximum points having the largest difference between the amplitude of the maximum point and the amplitude of the minimum point as the position of the notch point. However, the present invention is not limited thereto.

In this case, the processor 120 may set a predetermined time range for detecting the notch point, and detect the notch point within the set time range. The processor 120 may set a time range for detecting the position of the notch by multiplying the reference time by a predefined constant. In this case, the reference time may include, but is not limited to, the period of the PPG signal, the time to the first minimum point of the second differential signal of the PPG signal, and the like.

The processor 120 may obtain a first value and a second value from both sections divided based on the notch point of the detected PPG signal, and obtain a pulse pressure characteristic value based on the first value and the second value.

The processor 120 differentiates the PPG signal area of each of both sections based on the position of the notch in the PPG signal, the measurement time of each section, the PPG signal amplitude data of each section, and the PPG signal of each section by nth order differentiation. Any one or a combination of two or more intensities may be obtained as the first value and the second value.

For example, the processor 120 divides the PPG signal into two sections, left and right, based on the position of the notch point, and adds magnitudes of amplitudes sampled in each section to the time domain of the corresponding section to obtain the area of each section. However, the present invention is not limited thereto, and a partial area in a predetermined time range for each section is used as the area of the PPG signal, or a value obtained by adding n-squared values for each amplitude sampled when acquiring a PPG signal in the time domain of each section is added to the PPG signal The first value and the second value may be obtained using the area of .

As another example, the processor 120 calculates the maximum value of the PPG signal amplitude for each section divided based on the position of the notch point in the PPG signal, the average value of the PPG signal amplitude within each section, and the PPG signal amplitude within each section to the n square. The first value and the second value may be obtained by determining any one of the maximum value of one value and the average value of the n-squared value of the PPG signal amplitude within each section as the amplitude data, but is not limited thereto.

As another example, the processor 120 determines the sum of the absolute values of the amplitudes of the n-th differentiated signal of the PPG signal within each section as the intensity of the n-th differentiated signal of the PPG signal to obtain the first value and the second value. can be determined, but is not limited thereto.

The processor 120 may obtain a ratio between the first value and the second value as a pulse pressure characteristic value. However, the present invention is not limited thereto, and the difference between the first value and the second value, the sum, the product, and a combination thereof may be obtained as the pulse pressure characteristic value.

The processor 120 may estimate the pulse pressure by using the pulse pressure characteristic value. For example, the pulse pressure may be estimated by inputting a pulse pressure characteristic value into a predefined pulse pressure estimation model.

The processor 120 may extract a mean blood pressure-related feature value (hereinafter, referred to as a mean blood pressure feature value) from the measured PPG signal to estimate the user's mean arterial pressure. At this time, the average blood pressure characteristic value is a characteristic value associated with cardiac output (hereinafter referred to as a characteristic value of cardiac output) and a characteristic value associated with total peripheral resistance (hereinafter referred to as a characteristic value of total vascular resistance). It can be obtained by combining linearly or non-linearly.

The processor 120 may estimate the user's systolic blood pressure or diastolic blood pressure based on the measured PPG signal. In this case, the processor 120 may estimate the user's systolic blood pressure or diastolic blood pressure based on the acquired pulse pressure-related feature value. For example, the processor 120 may estimate the user's systolic or diastolic blood pressure based on the estimated user's pulse pressure and the estimated user's average blood pressure. At this time, the processor 120 may estimate the user's systolic blood pressure and diastolic blood pressure based on the reference mean blood pressure at the time of calibration and the reference pulse pressure at the time of calibration, and the reference systolic and diastolic blood pressure at the calibration time, but is limited thereto. it is not

As another example, the processor 120 may estimate the user's systolic blood pressure or diastolic blood pressure based on the rate of change of the estimated mean blood pressure compared to the reference mean blood pressure value at the time of calibration, and the rate of change of the estimated pulse pressure compared to the reference pulse pressure value at the time of the calibration. can

As another example, the processor 120 may estimate the user's blood pressure based on a rate of change of the feature value acquired when estimating the blood pressure compared to the reference feature value acquired at the time of calibration.

For example, the processor 120 may estimate the user's systolic blood pressure or diastolic blood pressure based on a change rate of the pulse pressure feature value acquired at the time of blood pressure estimation compared to the reference pulse pressure feature value acquired at the time of calibration. For example, the processor 120 may determine the rate of change of the pulse pressure characteristic value obtained at the time of the user's reference pulse pressure characteristic value, the rate of change of the cardiac output characteristic value obtained at the time of blood pressure estimation compared to the reference cardiac output characteristic value obtained at the time of calibration, and the time of calibration. The user's systolic or diastolic blood pressure can be estimated based on the rate of change of the total vascular resistance characteristic value obtained at the time of blood pressure estimation compared to the reference total vascular resistance characteristic value obtained at can

2 is a block diagram of an apparatus for estimating blood pressure according to another exemplary embodiment.

Referring to FIG. 2 , the blood pressure estimation apparatus 200 may include a sensor unit 110 , a processor 120 , a communication unit 230 , an output unit 220 , and a storage unit 210 .

As described above, the sensor unit 110 may measure the PPG signal from the subject. In this embodiment, the sensor unit 110 can be omitted as described later.

The storage unit 210 may store information such as pulse pressure and/or various reference information necessary for blood pressure estimation, an acquired PPG signal, and an estimated pulse pressure and/or blood pressure value. In this case, the reference information may include, but is not limited to, user information such as the user's age, gender, occupation, and current health status, and information about a relationship between the PPG signal and the pulse pressure. At this time, the storage unit 210 is a flash memory type (flash memory type), hard disk type (hard disk type), multimedia card micro type (multimedia card micro type), card type memory (eg, SD or XD memory) etc.), Random Access Memory (RAM), Static Random Access Memory (SRAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Programmable Read-Only Memory (PROM), magnetic It may include at least one type of storage medium among a memory, a magnetic disk, and an optical disk.

The output unit 220 may output the PPG signal measured by the sensor unit 110 and the processing result of the processor 120 and provide it to the user. The output unit 220 may provide information to the user in various visual/non-visual methods using a display module, a speaker, a haptic device, etc. mounted in the device.

For example, the output unit 220 may output the waveform of the PPG signal and/or the waveform of the second differential signal in the form of a graph. In addition, the pair of maxima and minima on the graph of the second differential signal of the PPG signal, the position of the notch point, the acquired pulse pressure and/or blood pressure related feature value, the pulse pressure and/or blood pressure related feature value at the time of calibration, the reference pulse pressure, and a marker visually indicating the reference blood pressure and the like. In addition, the user's blood pressure estimated value may be visually displayed, and the user may be provided with various colors, line thicknesses, fonts, etc. based on whether the estimated blood pressure value is within a normal range. In addition, by using vibration or tactile feedback together according to whether the blood pressure estimate value is abnormal, the user can easily recognize whether the blood pressure is abnormal. Alternatively, when there is an abnormality in the blood pressure estimation value compared to the previous estimation history, information about the action to be taken by the user, such as a warning message, an alarm signal, etc., food to be careful about, or related hospital information may be displayed.

The communication unit 230 may connect to the external device 240 through a communication technology under the control of the processor 120 and receive a PPG signal from the external device 240 . In this case, the external device 240 may include various devices that directly measure the PPG signal from the user or manage the measured PPG signal without particular limitation, such as a smart phone, a tablet PC, a wearable device, a cuff-type blood pressure monitor, and the like. Also, the communication unit 230 may transmit the processing result of the processor 120 to the external device 240 .

At this time, the communication technology is Bluetooth communication, BLE (Bluetooth Low Energy) communication, near field communication unit, WLAN (Wi-Fi) communication, Zigbee communication, infrared (IrDA, infrared Data Association) communication. , WFD (Wi-Fi Direct) communication, UWB (ultra wideband) communication, Ant+ communication WIFI communication and may include a mobile communication method, but is not limited thereto.

When both the sensor unit 110 and the communication unit 230 are mounted in the blood pressure estimating apparatus 200 , the processor 120 may obtain a PPG signal by selectively controlling the sensor unit 110 and the communication unit 230 . . Meanwhile, the sensor unit 110 may be omitted depending on the characteristics of the device 200 .

3A is a block diagram of a processor configuration according to an embodiment. 3B illustrates a PPG signal obtained from a subject. 3C is a diagram of a user interface that guides a user to input a blood pressure value measured from an external device and indicates an input position of the blood pressure value. 4A is a diagram for explaining an example of detecting a position of a notch point. 4B, 4C and 4D are diagrams for explaining how to obtain a pulse pressure characteristic value based on the first and second values of both sections when the PPG is divided into two sections based on the notch point.

Referring to FIG. 3A , the processor 120 includes a notch position detection unit 310 , a feature value acquisition unit 320 , a calibration unit 330 , a characteristic value normalization unit 340 , a pulse pressure estimation unit 350 , and a blood pressure. It may include an estimator 360 .

When the notch position detection unit 310 receives the PPG signal from the sensor unit 110 , it may derive a second differential signal of the PPG signal. In addition, the notch position detection unit 310 may set a predetermined time range for detecting the notch position, and detect the position of the notch point within a predetermined time range of the second differential signal. For example, determine the pairs of maxima and minima in the time range of the second derivative signal of the PPG signal, calculate the difference between the amplitude of the maxima and the amplitude of the minima for each determined pair of maxima and minima, and based on the difference can detect the position of the notch point.

Referring to FIG. 4A, a second differential signal of one PPG signal waveform is shown, T means the time from the second differential signal to the first minimum point, and r1 and r2 are the time range for detecting the position of the notch point ( T _I ) corresponds to a constant for setting. Also, T _dic means the position of the notch point.

For example, as illustrated, the notch position detection unit 310 may determine the time T from the second differential signal to the first minimum point as the reference time. In addition, the value (r1×T) obtained by multiplying the determined reference time (T) by the first constant (r1) is the starting point of the time range (T _I ), and the reference time (T) is multiplied by the second constant (r2) Let (r2×T) be the endpoint of the time range (T _I ). As an example, the time range (T _I ) for detecting the position of the notch point may be determined to be 2T to 5T, but is not limited thereto.

When the time range (T _I ) is set, the notch position detection unit 310 sets the maximum point and the minimum point immediately following the maximum point in the time range (T _I ) as a pair of maximum points and minimum points {(M ₁ , L _{1 )} ), (M _{2 ,} L ₂ ), (M ₃ , L ₃ )}. _{The notch} detection unit ₃₁₀ determines _{the amplitude} difference ₍ D ₁ , D ₂ , D ₃ ) may be calculated, and the time point Tdic of the maximum point M ₂ of the pair D ₂ having the largest amplitude difference may be detected as the position of the notch point.

In an ideal second differential signal that does not contain noise, the position of the third maximal point can generally be detected as the position of the notch point. As a result, various non-ideal waveforms appear. Therefore, in this embodiment, in order to remove such noise, the accuracy of pulse pressure estimation can be improved by detecting the time point of the pair of maximum points having the largest amplitude difference between the maximum and minimum points as the position of the notch point.

In addition, the notch position detection unit 310, in the second differential signal of the PPG signal, the number of pairs of maxima and minima is less than a predetermined number (eg, three), or maxima and minima of pairs of maxima and minima If the maximum value among the amplitude differences of ?

Referring back to FIG. 3A , the feature value acquisition unit 320 may acquire at least one of a pulse pressure feature, an average blood pressure, a cardiac output feature, and a total vascular resistance feature. In this case, the feature value acquisition unit 320 may acquire the reference feature value at the time of calibration and/or the feature value at the time of estimating the blood pressure. However, an embodiment in which the reference feature value at the time of calibration is obtained by the calibration unit 330 to be described below is also possible.

For example, the feature value acquisition unit 320 acquires a first value and a second value from both sections of the PPG signal divided based on the notch position, and determines the pulse pressure feature value based on the first value and the second value. can be obtained

As an example, referring to FIG. 4B , the feature value obtaining unit 320 is the area of both sections in which the PPG signal is divided based on the position T _dic of the notch DN detected by the notch position detecting unit 310 . (A ₁ , A ₂ ) may be obtained as a first value and a second value. For example, in one cycle (T _p ) PPG signal, the area (A ₁ ) from the starting point (0) to the notch point position (T _dic ) is determined as a first value, and one cycle PPG from the notch point position (T _dic ) The area A ₂ up to the end time point T _p of the signal may be determined as the second value.

Also, the feature value acquisition unit 320 may acquire the pulse pressure feature value feat_PP based on the obtained first value A ₁ and the second value A ₂ . For example, the feature value acquisition unit 320 may acquire a ratio between the first value (A ₁ ) and the second value (A ₂ ) as a pulse pressure feature value (feat_PP), which is exemplified in Equation 1 below. has been

As another example, referring to FIG. 4C , the feature value acquisition unit 320 is configured to perform the feature value acquisition unit 320 in both sections of the PPG signal divided based on the position T _dic of the notch point DN detected by the notch point position detection unit 310 , each The measurement time (T _dic , T _p -T _dic ) of the section may be obtained as a first value and a second value. For example, in one period (T _p ) PPG signal, the time (T _dic ) from the start time (0) to the notch position (T _dic ) is determined as the first value, and from the notch position (T _dic ) to the end time ( The time (T _p -T _dic ) until T _p ) may be determined as the second value.

Also, the feature value acquisition unit 320 may acquire the pulse pressure feature value feat_PP based on the obtained first value T _dic and the second value T _p -T _dic . For example, the feature value obtaining unit 320 may obtain a ratio between the first value (T _dic ) and the second value (T _p -T _dic ) as the pulse pressure feature value (feat_PP), which is obtained by the following equation 2 is exemplified.

As another example, referring to FIG. 4D , the feature value acquisition unit 320 divides the PPG signal into two sections based on the position (T _dic ) of the notch point DN detected by the notch point position detection unit 310 , and , the maximum amplitudes (P _a , P _b ) of the PPG signal in each section may be obtained as the first value and the second value. For example, in one period (T _p ) PPG signal, the maximum amplitude (P _a ) between the start time point (0) and the notch point position (T _dic ) is determined as the first value, and from the cut point position (T _dic ) to the end time point The maximum amplitude (P _b ) between (T _p ) may be determined as the second value.

Also, the feature value acquisition unit 320 may acquire the pulse pressure feature value feat_PP based on the obtained first value P _a and the second value P _b . For example, the feature value acquisition unit 320 may acquire a ratio between the first value (P _a ) and the second value (P _b ) as a pulse pressure feature value (feat_PP), which is exemplified in Equation 3 below has been However, the present invention is not limited thereto, and a method of obtaining the pulse pressure feature value feat_PP based on the obtained first value P _a and the second value P _b may be freely modified.

The feature value acquisition unit 320 may acquire an average blood pressure feature value based on the measured PPG signal. For example, the feature value acquisition unit 320 acquires the cardiac output feature value and the total vascular resistance feature value from the PPG signal, and combines the acquired cardiac output-related feature value and the total vascular resistance-related feature value in a linear or non-linear manner. The mean blood pressure feature value (feat_MAP_current) can be obtained.

The feature value acquisition unit 320 may extract a feature point from the PPG signal, and acquire a cardiac output feature value and/or a total vascular resistance feature value based on the extracted feature point.

At this time, the characteristic points are heart rate information, the shape of the waveform of the PPG signal, the time and amplitude of the maximum point of the PPG signal, the time and amplitude of the minimum point of the PPG signal, the area of the PPG signal, the lapse of time of the PPG signal, and the PPG signal. It includes, but is not limited to, one or more of amplitude and time information of the component pulse waveform, and an internal division point between two or more characteristic points. Here, the PPG signal may be the aforementioned PPG signal representative waveform.

3B illustrates a PPG signal obtained from a subject. An example in which the feature value acquisition unit 320 extracts a feature point from a PPG signal will be described with reference to FIG. 3B .

The PPG signal may be composed of a superposition of a propagation wave that starts from the heart and goes toward the distal end of the body and a reflection wave that returns back from the distal end. FIG. 3B illustrates that the waveform of the PPG signal obtained from the subject is formed by superimposing five component pulses, for example, a traveling wave fw and reflected waves rw1, rw2, rw3, and rw4. The feature value acquisition unit 320 may extract the feature points by analyzing the component pulse waveforms fw, rw1, fw2, rw3, and rw4 from the PPG signal.

As an example, the feature value acquisition unit 320 may determine the time (T ₁ , T ₂ , T ₃ ) or amplitude (P ₁ , P ₂ ) of the maximum point of the first to third component pulse waveforms (fw, rw1, rw2). , P ₃ ) can be extracted as feature points. At this time, the feature value acquisition unit 320 secondly differentiates the PPG signal PS and uses the second differential signal to obtain the time of the maximum point of the constituent pulse waveforms fw, rw1, rw2 (T ₁ , T ₂ , T ₃ ) can be extracted. For example, the time (T ₁ , T ₂ , T ₃ ) corresponding to the first to third local minimum points is extracted by searching the local minimum point in the second differential signal, and the The amplitudes P ₁ , P ₂ , P ₃ corresponding to the times T ₁ , T ₂ , and T ₃ may be extracted. Here, the local minimum point means a point having a shape where the signal decreases and then increases again around a specific point when a partial section of the second differential signal is observed, that is, has a downward convex shape.

As another example, the feature value acquisition unit 320 is a point at which the amplitude is maximum in one period (0 to PPG _dur ) of the PPG signal PS, or in a predetermined section within one period (0 to PPG _dur ) of the PPG signal PS. Time (T _max ) or amplitude (P _max ) of can be extracted as a feature point. In this case, the predetermined section may mean from the beginning of the PPG signal indicating the systolic section of blood pressure to the time point T _dic at which the notch DN occurs.

As another example, the feature value acquisition unit 320 may extract the lapse of time (PPG _dur ) indicating one cycle of the PPG signal or the area (PPG _area ) of the PPG signal as the feature point. In this case, the area of the PPG signal may mean the total area of the PPG signal or an area corresponding to a predetermined ratio (eg, 70%) of the entire time elapsed (PPG _dur ).

As another example, the feature value acquisition unit 320 may extract an internal division point between two or more extracted feature points as an additional feature point. An unstable waveform is generated in the PPG signal due to a non-ideal environment such as motion noise and sleep, so that feature points may be extracted at the wrong location. The blood pressure measurement can be supplemented by using the internal distribution point between the erroneously extracted feature points.

For example, when the feature value acquisition unit 320 extracts the feature points (T ₁ , P ₁ ) and (T _max , P _max ), the internal division point between the two feature points (T ₁ , P ₁ ) and (T _max , P _max ) (T _sys , P _sys ) can be calculated. At this time, the feature value acquisition unit 320 assigns a weight to the time values T ₁ and T _max of the two feature points (T ₁ , P ₁ ) and (T _max , P _max ), and uses each weighted time value. Thus, the time (T _sys ) of the internal division point is calculated, and the amplitude (P _sys ) corresponding to the calculated time (T _sys ) of the internal division point can be extracted. However, the present invention is not limited thereto and through the analysis of the obtained PPG signal, the first and second component pulse waveforms (fw, rw ₁ ) and related feature points (T ₁ , P ₁ ) and (T ₂ , P ₂ ) are internal division points between , the third and fourth component pulse waveforms (rw _2, rw ₃ ) and associated feature points (T ₃ , P ₃ ), an internal division point between (T ₄ , P ₄ ), and the like may be further calculated.

The feature value acquisition unit 320 may acquire a cardiac output feature value and/or a total vascular resistance feature value based on the extracted feature point. In this case, the feature value acquisition unit 320 may acquire a cardiac output feature value and/or a total vascular resistance feature value based on at least one of the plurality of extracted feature points and/or a heart rate.

As an example, the feature value acquisition unit 320 is the time and amplitude of the point at which the component pulse, which is the extracted feature point, is maximized, the total measurement time of the PPG signal, or the time until the position (T _dic ) of the notch point, the PPG signal Acquire the total area or partial area of the PPG signal, the time at the point where the amplitude is maximum in a predetermined section of the PPG signal, any one of the amplitude, or its reciprocal number, the heart rate, etc. as the cardiac output characteristic value and/or the total vascular resistance characteristic value can do.

As another example, the feature value acquisition unit 320 may acquire the cardiac output feature value and/or the total vascular resistance feature value based on a statistical value obtained by combining at least two of the extracted feature points and the heart rate. For example, the feature value acquisition unit 320 divides the maximum amplitude of the constituent pulse by the maximum amplitude in the entire section of the PPG signal, the maximum amplitude in the entire section of the PPG signal divided by the total area of the PPG signal, The value obtained by subtracting the time at the maximum amplitude of the constituent pulse by the time of the internal division point, or its reciprocal, the value obtained by subtracting the maximum amplitude of the constituent pulse from the maximum amplitude in the entire section of the PPG signal, or its reciprocal, in the entire section of the PPG signal. Statistical values of maximum amplitude and heart rate may be obtained as cardiac output characteristic values and/or total vascular resistance characteristic values.

Although Table 1 below exemplifies candidates for the cardiac output characteristic value and/or the total vascular resistance characteristic value in relation to that shown in FIG. 3B above, the present invention is not limited thereto.

number Cardiac output feature value, and/or total vascular resistance feature value candidate One HR (heart rate) 2 PPG _area 3 P ₃ /P _max 4 P ₃ /P _sys 5 P _max /PPG _area 6 1/PPG _dur 7 1/(T ₃ -T ₁ ) 8 1/(T ₃ -T _sys ) 9 1/(T ₃ -T _max ) 10 1/(T ₂ -T ₁ ) 11 P ₂ /P ₁ 12 P ₃ /P _max 13 P ₃ /P ₁

The pulse pressure characteristic value, the average blood pressure characteristic value, the cardiac output characteristic value, and the total vascular resistance characteristic value acquired by the characteristic value acquisition unit 320 may be transmitted to the characteristic value normalization unit 340 . When a user measures blood pressure using the blood pressure estimation apparatus 100 or 200 , calibration must be performed first. The calibrator 330 may perform calibration according to a preset period, pulse pressure, and/or blood pressure estimation result analysis or a user's request.

As an example, the calibrator 330 may perform calibration at the user's initial use time and every preset period from the first use time. For example, when a user requests an initial blood pressure estimation using the device 100, the calibrator 330 refers to the storage unit to check whether reference information necessary for blood pressure estimation exists, and if not, the calibration may be performed. have.

As another example, the calibrator 330 may analyze the pulse pressure and/or the blood pressure estimation result, and determine whether to perform the calibration based on the analyzed result. For example, when the blood pressure estimation is completed, the calibrator 330 may determine whether to perform the calibration by determining the accuracy of the estimated blood pressure. For example, a normal range of the estimated blood pressure value may be predefined, and when the estimated blood pressure value is out of the normal range, when the number of times out of the normal range exceeds a threshold, the number of times the normal range is not continuously satisfied, or for a predetermined period When the number of times the normal range is not satisfied is equal to or greater than a predetermined threshold, it may be determined that calibration is required.

When the calibration unit 330 determines to perform calibration, the calibration unit 330 may control the sensor unit 110 to obtain a PPG signal for calibration. The calibration unit 330 may guide the user to bring the subject into contact with the sensor unit 110 , guide the connection of an external device through the communication unit 210 , or guide the reference blood pressure measurement through an external device.

In this case, for example, the calibration unit 330 controls the communication unit 230 of FIG. 2 to receive reference information at the time of calibration from an external device, for example, reference blood pressure such as cuff systolic blood pressure and cuff diastolic blood pressure from the cuff blood pressure device. can do.

Alternatively, the calibrator 330 displays a user interface 370 as shown in FIG. 3C on the display, and guides the user to input the systolic blood pressure and the diastolic blood pressure measured through an external device through the user interface 370 . You may. Referring to FIG. 3C , the user interface 370 of the blood pressure estimating apparatus may include a graphic object 371 that can be touched by a user and indicates a location where a blood pressure value measured using an external device is input.

When the PPG signal for calibration is obtained by the sensor unit 110, the calibration unit 330 obtains reference information necessary for blood pressure estimation using the obtained PPG signal for calibration, and stores the obtained reference information in the storage unit. It can be used for the next blood pressure estimation.

For example, the calibrator 330 may obtain a reference pulse pressure characteristic value (feat_PP_cal), a reference mean blood pressure characteristic value (feat_MAP_cal), a reference cardiac output characteristic value, and a reference total vascular resistance characteristic value at the time of calibration. The reference mean blood pressure characteristic value (feat_MAP_cal) may be obtained by linearly or non-linearly combining the reference cardiac output characteristic value and the reference total vascular resistance characteristic value obtained at the time of calibration, as described above in the characteristic value acquisition unit 320. . The reference cardiac output characteristic value and the reference total vascular resistance characteristic value may be obtained based on the characteristic points extracted from the PPG signal measured at the time of calibration. In this case, the cardiac output characteristic value and/or the total vascular resistance characteristic value may be acquired based on at least one or more of the plurality of extracted characteristic points and/or the heart rate. A detailed description will be omitted.

In addition, the calibration unit 330 uses the reference systolic blood pressure (SBP_cal) and the reference diastolic blood pressure (DBP_cal) received through the communication unit 230 or input through the user interface 370 during calibration to obtain a reference pulse pressure (PP_cal) at the time of calibration. can be obtained. The reference pulse pressure may be obtained by subtracting the reference diastolic blood pressure from the reference systolic blood pressure (PP_cal = SBP_cal - DBP_cal).

The calibrator 330 may acquire the reference mean blood pressure MAP_cal at the calibration time by using the reference diastolic blood pressure DBP_cal and the reference pulse pressure PP_cal at the calibration time. The reference mean blood pressure (MAP_cal) may be obtained through Equation 4 below, but is not limited thereto.

는 고정된 상수일 수도 있고, 심박에 따라 변화하는 변수를 의미할 수도 있다.

가 심박에 따라 변화하는 변수일 경우, 심박이 커짐에 따라

또한 커질 수 있다.In this case, PP_cal is the reference pulse pressure at the time of calibration, DBP_cal is the reference diastolic pressure at the time of calibration,

may be a fixed constant or may mean a variable that changes according to the heartbeat.

If is a variable that changes with the heart rate, as the heart rate increases,

It can also be large.

The characteristic value normalization unit 340 may calculate a change rate of each characteristic value by normalizing the acquired pulse pressure characteristic value, average blood pressure characteristic value, cardiac output characteristic value, and/or total vascular resistance characteristic value.

As an example, the feature value normalization unit 340 uses the pulse pressure feature value (feat_PP_cal) at the time of calibration, and the current pulse pressure feature value (feat_PP_current) increases at a certain rate compared to the pulse pressure feature value (feat_PP_cal) at the first calibration time / A normalization process indicating whether it has decreased may be performed. The normalization result of the pulse pressure characteristic value, that is, the rate of change of the pulse pressure characteristic value, may mean Δfeat_PP in Equations 7, 13, and 14 below. In addition, the rate of change (Δfeat_PP) of the pulse pressure characteristic value may be used when calculating the rate of change (ΔPP_est) of the pulse pressure at the time of estimating the blood pressure compared to the reference pulse pressure at the time of calibration in Equations (11) and (12).

As another example, the feature value normalization unit 340 uses the average blood pressure feature value (feat_MAP_cal) at the time of calibration, how much of the current mean blood pressure feature value (feat_MAP_current) is compared to the average blood pressure feature value (feat_MAP_cal) at the time of the first calibration? A normalization process indicating whether the ratio increases/decreases may be performed. The normalization result of the mean blood pressure characteristic value, that is, the change rate of the mean blood pressure characteristic value, may mean Δfeat_MAP in Equation 8 below. In addition, the rate of change (Δfeat_MAP) of the mean blood pressure characteristic value may be used in Equations 11 and 12 to calculate the average blood pressure change rate (ΔMAP_est) at the time of estimating blood pressure compared to the reference mean blood pressure at the time of calibration.

As another example, the feature value normalization unit 340 may calculate the rate of change of the cardiac output feature value (feat_CO) and/or the total vascular resistance feature value (feat_TPR) in this way.

In this case, Δfeat_CO is the rate of change of the cardiac output characteristic value, feat_CO_current is the cardiac output characteristic value obtained at the time of blood pressure measurement, and feat_CO_cal is the reference cardiac output characteristic value obtained at the time of calibration. Δfeat_TPR is the rate of change of the total vascular resistance characteristic value, feat_TPR_current is the total vascular resistance characteristic value obtained at the time of blood pressure measurement, and feat_TPR_cal is the reference total vascular resistance characteristic value obtained at the time of calibration.

The characteristic value normalization unit 340 transmits the rate of change of the pulse pressure characteristic value to the pulse pressure estimator 350, or converts the rate of change of the average blood pressure characteristic value, the rate of change of the cardiac output characteristic value, and the rate of change of the total vascular resistance characteristic value to the blood pressure estimator ( 370) can be transferred.

The pulse pressure estimator 350 may estimate the user's pulse pressure through Equation 7 below. That is, the pulse pressure may be estimated based on the reference pulse pressure PP_cal obtained by the calibration unit 330 and the rate of change of the pulse pressure characteristic value received from the characteristic value normalization unit 340 .

PP_est is the pulse pressure to be estimated, Δfeat_PP is the rate of change of the pulse pressure characteristic value transmitted from the characteristic value normalization unit 330, PP_cal is the reference pulse pressure obtained from the reference systolic blood pressure and the reference diastolic blood pressure measured at the time of calibration (= reference systolic blood pressure - reference) diastolic blood pressure), feat_PP_cal denotes a reference pulse pressure characteristic value extracted from the PPG signal measured at the time of calibration, and feat_PP_current denotes a pulse pressure characteristic value extracted from the current PPG signal. SF_PP corresponds to a scale factor for estimating the rate of change of pulse pressure compared to calibration, and the value of SF_PP may be a constant within the range of 20-50, but this is an exemplary value and is not limited thereto.

The blood pressure estimator 360 may estimate at least one of the user's average blood pressure, systolic blood pressure, and diastolic blood pressure.

The blood pressure estimator 360 may estimate the user's average blood pressure through an average blood pressure estimation equation as shown in Equation 8 below.

Here, MAP_est is the mean blood pressure estimate to be obtained, Δfeat_MAP is the rate of change of the mean blood pressure feature value transmitted from the feature value normalization unit 330 , and MAP_cal is the reference mean blood pressure value at the time of calibration. In addition, feat_MAP_current is the mean blood pressure characteristic value obtained based on the PPG signal obtained at the time of blood pressure estimation, feat_MAP_cal is the reference mean blood pressure characteristic value at the time of calibration, and SF_MAP is the mean blood pressure estimation related scale factor.

In this case, the average blood pressure feature value (feat_MAP_current) at the time of estimating the mean blood pressure may be a value obtained by combining the cardiac output-related feature value and the total vascular resistance-related feature value obtained as described above in the feature value acquisition unit 320 in a linear or non-linear manner. have. In this case, the cardiac output characteristic value and/or the total vascular resistance characteristic value may be any one of the plurality of characteristic points extracted as described above, the heart rate, or a statistical value combining them. A detailed description will be omitted. SF_MAP corresponds to a scale factor for estimating the mean blood pressure change rate compared to calibration, and the value of SF_MAP may be a constant within a certain range.

The blood pressure estimator 360 may estimate the user's systolic blood pressure or diastolic blood pressure.

For example, the blood pressure estimator 360 may estimate the user's systolic blood pressure or diastolic blood pressure based on the estimated user's average blood pressure and the estimated user's pulse pressure.

A process of estimating the user's systolic or diastolic blood pressure based on the user's average blood pressure and pulse pressure is exemplified in Equation 9 or 10 below, but is not limited thereto.

SBP_est in Equation 9 means the user's estimated systolic blood pressure, and DBP_est in Equation 10 means the user's estimated diastolic blood pressure. MAP_est represents the user's average blood pressure estimated through the above-described process, and PP_est represents the user's pulse pressure estimated through the above-described process. Also, k at this time may be a constant constant or a function that increases in proportion to an increase in heart rate (HR), but is not limited thereto.

As another example, the blood pressure estimator 360 calculates the change rate of the estimated mean blood pressure compared to the reference mean blood pressure value at the time of calibration, the rate of change of the estimated pulse pressure compared to the reference pulse pressure value at the time of calibration, and the systolic or diastolic blood pressure at the time of calibration. Based on the systolic blood pressure or the diastolic blood pressure of the user may be estimated.

An example of this is shown in Equation 11 or Equation 12 below, but is not limited thereto.

SBP _- _est in Equation 11 means the user's estimated systolic blood pressure, and DBP_est in Equation 12 means the user's estimated diastolic blood pressure.

ΔPP_est is the rate of change of the estimated pulse pressure compared to the reference pulse pressure at the time of calibration, that is, (PP_est - PP_cal). Here, PP_est is the user's pulse pressure estimated through the above-described process, and PP_cal is the reference pulse pressure value at the time of calibration as described above. In this case, ΔPP_est may be obtained based on the rate of change of the pulse pressure characteristic value illustrated in Equation 7, that is, Δfeat_PP, without estimating the user's pulse pressure.

ΔMAP_est is the rate of change of the estimated mean blood pressure compared to the mean blood pressure at the time of calibration, that is, (MAP_est - MAP_cal). Here, MAP_est is the user's average blood pressure estimated through the above-described process, and MAP_cal is the average blood pressure value at the time of calibration as described above. In this case, ΔMAP_est may be obtained based on the rate of change of the average blood pressure characteristic value illustrated in Equation 8, that is, Δfeat_MAP, without estimating the user's average blood pressure.

Also, k at this time may be a constant constant or a function that increases in proportion to an increase in the heart rate (HR), but is not limited thereto. SBP_cal and DBP_cal represent systolic blood pressure and diastolic blood pressure at the time of calibration, respectively.

As another example, the blood pressure estimator 360 may estimate the user's systolic blood pressure or diastolic blood pressure based on the reference feature value at the time of calibration, the rate of change of the feature value at the time of estimating the blood pressure, and the reference blood pressure.

For example, the blood pressure estimator 360 may estimate the user's systolic or diastolic blood pressure by linearly combining the rate of change of the cardiac output feature value, the change rate of the total vascular resistance feature value, the change rate of the pulse pressure feature value, and the reference blood pressure. have. In this case, the reference blood pressure means a reference systolic blood pressure or a reference diastolic blood pressure.

An example of the linear combination is weighted sum, which is exemplified in Equations 13 and 14.

In Equation 13, SBP_est is the systolic blood pressure at the time of blood pressure measurement estimated by the blood pressure estimator 360, and SBP_cal is the reference systolic blood pressure obtained at the time of calibration. Δfeat_CO is the rate of change of the characteristic value of cardiac output, Δfeat_TPR is the rate of change of the characteristic value of total vascular resistance, and Δfeat_PP is the rate of change of the characteristic value of pulse pressure. a, b, c, and d are real numbers, and may be different values, or two or more of them may be the same value. Also, at least one of a, b, c, and d may have a value of 1 or 0.

In Equation 14, DBP_est is the diastolic blood pressure at the time of blood pressure measurement estimated by the blood pressure estimator 360, and SBP_cal is the reference diastolic blood pressure obtained at the time of calibration. Δfeat_CO is the rate of change of the cardiac output characteristic value described through Equation 5, Δfeat_TPR is the rate of change of the total vascular resistance characteristic value described through Equation 6, and Δfeat_PP is the rate of change of the pulse pressure characteristic value described through Equation 7. a, b, c, and d are real numbers and are the same as defined in Equation (14). However, the present invention is not limited thereto, and the values of a, b, c, and d used in Equation 15 may be different from the values of a, b, c, and d used in Equation 14 by at least one. Also, in Equation 14, Δfeat_CO, Δfeat_TPR, and Δfeat_PP may be the same or different values from Δfeat_CO, Δfeat_TPR, and Δfeat_PP used in Equation 13, respectively.

5 is a flowchart of a method for estimating blood pressure according to an exemplary embodiment. The embodiment of FIG. 5 is an embodiment of a blood pressure estimating method performed by the blood pressure estimating apparatus of FIG. 1 or 2 . Since it has been described in detail above, it will be briefly described below.

First, the blood pressure estimating apparatus may measure the PPG signal including the PPG signal upon receiving the blood pressure estimation request ( 510 ). The blood pressure estimating apparatus 100 or 200 may provide an interface for performing various interactions with the user. The user may request pulse pressure estimation through an interface provided by the blood pressure estimating device. Alternatively, a blood pressure estimation request may be received from an external device. In this case, the blood pressure estimation request received from the external device may include a request for providing the blood pressure estimation result. When the external device is equipped with a blood pressure estimation algorithm, a request for providing the acquired feature value may be included. The external device may include a smartphone, a tablet PC, a notebook PC, and a wearable device carried by the user. The blood pressure estimating apparatus may control the sensor to measure the PPG signal including the pulse wave signal from the subject.

Then, a second derivative of the PPG signal may be obtained ( 520 ). Next, the position of the notch point may be detected based on the maximum and minimum points of the second differential signal of the PPG signal ( 530 ). As an example, the pair of the maximum and minimum points of the second differential signal of the PPG signal is determined, and the difference between the second derivative of the maximum and the second differential of the minimum is calculated from the pair of maximum and minimum points, and the difference is calculated. It is possible to detect the position of the notch based on the basis. As another example, a pair of maximal points having the largest difference between the second derivative value of the maximal point and the second derivative value of the local minima may be detected as the position of the notch point.

Next, a first value and a second value may be obtained from both sections divided based on the notch point of the PPG signal ( 540 ). For example, the first value and the second value are the PPG signal area in the corresponding section, the measurement time of each section, the PPG signal amplitude data of each section, and the intensity of the signal obtained by differentiating the PPG signal of each section by the nth order. It may include any one, but is not limited thereto.

A pulse pressure characteristic value may be obtained based on the next first value and the second value ( 550 ). In this case, the pulse pressure characteristic value may include a ratio between the first value and the second value, but is not limited thereto.

Next, the blood pressure may be estimated based on the pulse pressure characteristic value ( 560 ).

For example, the pulse pressure is estimated based on the pulse pressure characteristic value using a predefined pulse pressure estimation model, the average blood pressure is estimated based on the average blood pressure characteristic value, and the systolic or diastolic blood pressure is based on the estimated pulse pressure and the average blood pressure. blood pressure can be estimated.

As another example, the user's systolic or diastolic blood pressure may be estimated based on a rate of change of the estimated mean blood pressure relative to the reference mean blood pressure value at the time of calibration and the rate of change of the estimated pulse pressure compared to the reference pulse pressure value at the time of calibration.

As another example, the user's systolic blood pressure or diastolic blood pressure may be estimated based on a change rate of the acquired pulse pressure characteristic value compared to the user's reference pulse pressure characteristic value. In this case, the user's systolic blood pressure is further based on the rate of change of the characteristic value of cardiac output compared to the characteristic value of the reference cardiac output, the rate of change of the characteristic value of total vascular resistance compared with the characteristic value of reference total vascular resistance, and the reference systolic blood pressure or the reference diastolic blood pressure. Blood pressure or diastolic blood pressure can be estimated. A detailed description will be omitted.

6 illustrates an embodiment of the step 530 of detecting the notch point location of FIG. 5 .

First, at least one of the period of the PPG signal and the time to the first minimum point of the second differential signal of the PPG signal is determined as the reference time, and the time range for detecting the position of the notch point can be set based on the determined reference time. There is (610). In this case, the time range may have a value obtained by multiplying a reference time by the first constant as a starting point and a value obtained by multiplying a reference time by a second constant as an end point, but is not limited thereto.

Next, it is possible to determine a pair of maxima and minima in the second differential signal of the PPG signal ( 620 ). In this case, the initially detected maximum point and the initially detected minimum point may be determined as one pair, and then the detected maximum and minimum points may be determined as other pairs according to time sequence.

Here, it is determined whether the determined number of pairs is less than a predetermined number (eg, three), and when the determined number is less than the predetermined number, the user may request a re-measurement of the PPG signal.

Next, in the pair of maxima and minima, the difference between the second derivative of the maxima and the second derivative of the minima may be calculated ( 630 ).

Next, a pair of maximal points having the largest difference between the second differential value of the maximal point and the second differential value of the local minima may be detected as the position of the notch point ( 640 ). In this case, when the difference between the pair having the largest difference between the second differential value of the maximum point and the second differential value of the minimum point is less than or equal to the threshold value, the user may request re-measurement of the PPG signal.

7 illustrates a wearable device according to an exemplary embodiment. Various embodiments of the above-described blood pressure estimating apparatus 100 and 200 may be mounted on a smart watch worn on a wrist. However, the shape of the wearable device is not limited to the illustrated example.

Referring to FIG. 7 , the wearable device 700 includes a body 710 and a strap 720 .

The strap 720 may be formed of a flexible material. The strap 720 may be connected to both ends of the main body 710 and wrap the user's wrist to bring the main body 710 into close contact with the upper wrist. At this time, the strap 720 may be formed to have elasticity in accordance with the change in pressure applied to the wrist, or may be formed to include an air bag or air inside, and may transmit the pressure change of the wrist to the body 710 .

A battery for supplying power to the wearable device 700 may be built in the body 710 or the strap 720 . In addition, the sensor unit 730 may be mounted on the rear surface of the main body 710 . The sensor unit 730 may include one or more light sources and detectors.

The processor is mounted inside the main body 710 , and obtains a second differential signal of the PPG signal measured by the sensor unit 730 to estimate pulse pressure and/or blood pressure. For example, the position of the notch point is detected based on the maxima and minima of the second differential signal of the PPG signal, and a first value and a second value are obtained from both sections divided based on the notch point of the PPG signal, A pulse pressure characteristic value may be obtained based on the first value and the second value, and blood pressure may be estimated based on the pulse pressure characteristic value.

The processor is mounted inside the main body 710 and may estimate the user's blood pressure by acquiring the second differential signal of the PPG signal measured by the sensor unit 730 . For example, the processor obtains the second differential signal of the PPG signal, detects the position of the notch point based on the maximum and minimum points of the second differential signal of the PPG signal, and divides the The first value and the second value may be obtained, the pulse pressure characteristic value may be obtained based on the first value and the second value, and the blood pressure may be estimated based on the pulse pressure characteristic value.

In addition, a display unit is mounted on the front surface of the main body 710 , and the display unit may display a pulse pressure estimation result, a blood pressure estimation result, and the like. In this case, the display unit may include a touch screen capable of a touch input.

In addition, a storage unit may be mounted inside the main body 710 , and various reference information for pulse pressure estimation or blood pressure estimation and/or results processed by the processor may be stored in the storage unit.

In addition, a manipulation unit 740 that receives a user's control command and transmits it to the processor may be mounted on the side of the main body 710 , and the manipulation unit 740 inputs a command to turn on/off the power of the wearable device 700 . It may include a function to In addition, the manipulation unit 740 may be equipped with a PPG sensor to obtain a PPG signal from the finger when the finger makes contact.

In addition, a communication unit for transmitting and receiving data with an external device may be mounted inside the main body 710 . The communication unit may communicate with an external device, such as a user's smartphone, a cuff-type pulse pressure device, or a cuff-type blood pressure device, to transmit and receive pulse pressure estimation or various data related to blood pressure estimation.

8 illustrates a smart device according to an embodiment. In this case, the smart device 800 may include a smart phone and a tablet PC. The smart device 800 may include various embodiments of the blood pressure estimation apparatus 100 and 200 described above.

Referring to FIG. 8 , the smart device 800 may have a sensor unit 830 mounted on the rear surface of the main body 810 . The sensor unit 830 may include a light source 831 and a detector 832 . The sensor unit 830 may be mounted on the rear surface of the main body 810 as shown, but is not limited thereto. For example, the sensor unit 830 may be formed on a front fingerprint sensor, a part of a touch panel, or a power button, a volume button, etc. mounted on the side or upper side of a smart device.

In addition, a display unit for displaying various information such as a pulse pressure estimation result, a blood pressure estimation result, and contact state guide information may be mounted on the front surface of the main body 810 .

On the other hand, the body 810 may be equipped with an image sensor 820 as shown, and the image sensor 820 generates an image of a finger when a user approaches the sensor unit 830 with a finger to measure a pulse wave signal. You can take a picture and send it to the processor. In this case, the processor may determine the relative position of the finger compared to the actual position of the sensor unit 830 from the image of the finger, and guide the relative position information of the finger to the user through the display unit.

The processor may estimate the pulse pressure or blood pressure through the measured PPG signal and the second differential signal of the PPG signal. As described above, the pulse pressure, the mean blood pressure, the systolic blood pressure, or the diastolic blood pressure can be more accurately estimated by using the PPG signal and the second differential signal of the PPG signal in consideration of the physiological and mechanical properties of the blood vessel. A detailed description will be omitted.

Meanwhile, the present embodiments can be implemented as computer-readable codes on a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices in which data readable by a computer system is stored.

Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, etc. include In addition, the computer-readable recording medium may be distributed in a network-connected computer system, and the computer-readable code may be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the present embodiments can be easily inferred by programmers in the technical field to which the present invention pertains.

Those of ordinary skill in the art to which the present disclosure pertains will understand that the disclosed technical spirit or essential features may be embodied in other specific forms without changing. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

100, 200: blood pressure estimating device 110: sensor unit
120: processor 210: storage
220: output unit 230: communication unit
240: external device 310: notch point position detection unit
320: feature value acquisition unit 330: calibration unit
340: feature value normalization unit 350: pulse pressure estimation unit
360: blood pressure estimator 700: wearable device
800: smart device

Claims (20)

a sensor unit for measuring the PPG signal from the subject;
The position of the notch point is detected based on the maxima and minima of the second differential signal of the PPG signal, and a first value and a second value are obtained from both sections divided based on the notch point of the PPG signal, and the A blood pressure estimating apparatus comprising: a processor for acquiring a pulse pressure-related feature value based on a first value and a second value, and estimating a blood pressure based on a change rate of the obtained pulse-pressure-related feature value compared to a reference pulse pressure-related feature value.
According to claim 1,
the processor
Determine the pair of maxima and minima of the second derivative signal, calculate the difference between the second derivative of the maxima and the second derivative of the minima in the pair of maxima and minima, and based on the difference, the notch point A blood pressure estimating device that detects the position of
3. The method of claim 2,
The processor is
A blood pressure estimating apparatus for detecting a time point of a pair of maxima having the largest difference between the second derivative value of the maximal point and the second derivative value of the minima as the position of the notch point.
3. The method of claim 2,
The processor is
The number of pairs of maxima and minima of the second differential signal of the determined PPG signal is less than or equal to a predetermined number, or the difference between the second derivative of the calculated pair of maxima and minima and the second derivative of the minima is less than or equal to a threshold In this case, the blood pressure estimating device requests the user to re-measure the PPG signal.
According to claim 1,
The processor is
Determining at least one of the period of the PPG signal and the time to the first minimum point of the second differential signal of the PPG signal as a reference time, and setting a time range for detecting the position of the notch point based on the determined reference time blood pressure estimator.
6. The method of claim 5,
The time range is
A blood pressure estimating apparatus in which a value obtained by multiplying the reference time by a first constant is a starting point, and a value obtained by multiplying the reference time by a second constant is an end point.
The method of claim 1,
The pulse pressure-related characteristic value is,
A blood pressure estimating apparatus including a ratio between the first value and the second value.
The method of claim 1,
The first value and the second value are
A blood pressure estimating apparatus comprising any one of an area of a PPG signal in each corresponding section, a measurement time of each section, PPG signal amplitude data of each section, and an intensity of a signal obtained by differentiating the PPG signal of each section by an nth order.
9. The method of claim 8,
The amplitude data of the PPG signal is
The maximum value of the PPG signal amplitude in each section, the average value of the PPG signal amplitude in each section, and the maximum value or the average value in each section of the n-squared value of the PPG signal amplitude. blood pressure estimator.
9. The method of claim 8,
The intensity of the signal obtained by differentiating the PPG signal by the nth order is
An apparatus for estimating blood pressure that is the sum of absolute values of signals obtained by differentiating the PPG signal in the nth order within each section.
The method of claim 1,
The processor is
estimating the user's pulse pressure based on the change rate and the reference pulse pressure obtained at the time of calibration;
extracting a mean blood pressure-related feature value from the PPG signal, and estimating the mean blood pressure based on the extracted mean blood pressure-related feature value;
A blood pressure estimator for estimating a user's systolic or diastolic blood pressure based on the estimated average blood pressure and pulse pressure.
The method of claim 1,
The processor is
Based on the rate of change of the mean blood pressure at the time of blood pressure estimation compared to the reference mean blood pressure value at the time of calibration, the rate of change of the estimated pulse pressure compared to the reference pulse pressure value at the time of calibration, and the reference systolic or diastolic blood pressure at the time of calibration, respectively, the user's systolic blood pressure or A blood pressure estimator for estimating diastolic blood pressure.
13. The method of claim 12,
The processor is
calculating the rate of change of the pulse pressure based on the rate of change of the obtained pulse pressure-related characteristic value compared to the obtained reference pulse pressure-related characteristic value;
A blood pressure estimating apparatus for calculating a change rate of the mean blood pressure based on a change rate of the obtained mean blood pressure-related feature value compared to a reference mean blood pressure-related feature value.
The method of claim 1,
The processor is
The rate of change of the acquired pulse pressure-related feature value compared to the reference pulse pressure-related feature value, the change rate of the acquired cardiac output-related feature value compared to the reference cardiac output-related feature value, and the acquired total vascular resistance-related feature compared to the reference total vascular resistance-related feature value A blood pressure estimator for estimating a user's systolic or diastolic blood pressure based on the rate of change of the value.
measuring the PPG signal from the subject;
obtaining a second differential signal of the PPG signal;
detecting the position of the notch point based on the maximum and minimum points of the second differential signal of the PPG signal;
obtaining a first value and a second value from both sections divided based on the notch point of the PPG signal;
obtaining a pulse pressure-related feature value based on the first value and the second value; and
A method for estimating blood pressure, comprising estimating a blood pressure based on a rate of change of the acquired pulse pressure-related feature value compared to a reference pulse pressure-related feature value
16. The method of claim 15,
The step of detecting the position of the notch point,
determining a pair of maxima and minima of the second differential signal of the PPG signal; and
and calculating a difference between a second differential value of a maximum point and a second differential value of a minimum point in the pair of the maximum and minimum points, and detecting the position of the notch point based on the difference.
17. The method of claim 16,
The step of detecting the position of the notch point based on the difference is,
A blood pressure estimation method for detecting a pair of maxima having the largest difference between the second derivative value of the maximal point and the second derivative value of the local minima as the position of the notch point.
16. The method of claim 15,
The number of pairs of maxima and minima of the second differential signal of the determined PPG signal is less than or equal to a predetermined number, or the difference between the second derivative of the calculated pair of maxima and minima and the second derivative of the minima is less than or equal to a threshold case, requesting the user to re-measure the PPG signal.
16. The method of claim 15,
Determining at least one of the period of the PPG signal and the time to the first minimum point of the second differential signal of the PPG signal as a reference time, and setting a time range for detecting the position of the notch point based on the determined reference time Blood pressure estimation method further comprising the step.
16. The method of claim 15,
The step of obtaining a pulse pressure-related feature value based on the first value and the second value includes:
A blood pressure estimation method for obtaining a ratio between the first value and the second value as a pulse pressure-related feature value.

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