KR20190120684A - Apparatus and method for monitoring bio-signal measuring condition, and apparatus and method for measuring bio-information - Google Patents

Abstract

Disclosed is a device for monitoring a measuring condition of a bio-signal by using the measured bio-signal. According to an embodiment of the present invention, the device for monitoring a measuring condition of a bio-signal comprises: a bio-signal receiving unit receiving a bio-signal which is measured from a user; and a processor extracting one or more characteristics from the bio-signal, determining whether the extracted characteristics are normal, and monitoring the measuring condition of the bio-signal based on a determined result.

Description

APPARATUS AND METHOD FOR MONITORING BIO-SIGNAL MEASURING CONDITION, AND APPARATUS AND METHOD FOR MEASURING BIO-INFORMATION}

The present invention relates to an apparatus and a method for monitoring a biosignal measurement state, and more particularly, to a technology for monitoring a measurement state using a measurement result of a biosignal itself.

Recently, due to the aging population, rapidly increasing medical expenses and shortage of specialized medical service personnel, research on IT-medical convergence technology combining IT technology and medical technology is being conducted. In particular, the monitoring of the health status of the human body is not limited to being performed only in a fixed place such as a hospital, but expanded to the mobile healthcare field that monitors the health status of the user anytime and anywhere in daily life such as home and office. It is becoming. Representative types of biosignals that represent the health of individuals include ECG (electrocardiogram, electrocardiography), PPG (photoplethysmogram), and EMG (electromyography, electromyography) signals. Signal sensors are being developed. However, when detecting the biosignal through the biosignal sensor, an accurate biosignal may not be detected depending on a wearing state of the biometric information measuring device or a posture of a user.

An apparatus and method for monitoring a biosignal measurement state using a measured biosignal without using an additional sensor are provided. Also, an apparatus and method for measuring biometric information using a monitoring result of a biosignal measurement state are provided.

According to an aspect, the apparatus for monitoring a biosignal measurement state extracts one or more features of a waveform, a period, and an amplitude from a biosignal receiving unit receiving a biosignal measured from a user and a biosignal, and sets a predetermined criterion based on the extracted feature The processor may include a processor configured to determine whether the extracted feature is normal and to monitor a measurement state of the biosignal based on the determination result.

The processor may include a feature determiner that determines whether the extracted waveform is normal by applying a personalized waveform self-reference to the user.

In this case, the waveform itself reference may include one or more of a reference section, a comparison sample number, a derivative order, and a failure condition.

When the waveform of the current section is extracted from the biosignal, the feature determiner obtains a first waveform and a second waveform from the waveform of the current section and the waveform of the reference section based on the differential order, respectively, and obtain the obtained first waveform and the second waveform. When the comparison result satisfies the failure condition by comparing the waveforms, the extracted waveform characteristics may be determined to be abnormal.

The processor may further include a buffer configured to store waveform data of the biosignal reference section.

The processor may further include a feature extractor configured to extract the waveform of the current section from the biosignal and update the waveform data of the reference section stored in the buffer by using the waveform data of the current time section when the preset update criterion is satisfied.

In this case, the failure condition may include one or more of the lowest limit of the similarity between waveforms, the number of consecutive failures of the lowest limit, the starting point of similarity comparison between the waveforms, and the total number of bits for the average similarity.

The feature determiner may calculate a similarity between the first waveform and the second waveform, and determine that the extracted waveform feature is abnormal when the calculated similarity is less than the minimum threshold.

The feature determiner may determine that the waveform feature is abnormal when the degree of similarity between the first waveform and the second waveform is less than the minimum threshold and the number of times the minimum threshold continuous failure is not exceeded is set in advance.

In this case, the similarity between the waveforms may include one or more of correlation coefficients, averages, and totals between the comparative samples of the first and second waveforms.

When the periodic feature is extracted from the biosignal, the processor determines whether the periodic feature is normal by applying at least one of a personalized periodic self criterion to the user and a periodic universal criterion, which is a general standard for biometric information to be measured through the biosignal. It may include a feature determination unit.

In this case, the periodic feature may include at least one of a current period of the biosignal and an average period for a predetermined time.

When the amplitude feature is extracted from the biosignal, the processor may include a feature determiner that determines whether the extracted amplitude feature is normal by applying a personalized amplitude self criterion to the user.

The processor may include a measurement state determination unit configured to output at least one of reliability and measurement state information of the biosignal measurement by considering the determination result of each feature in parallel or serially according to a preset priority for each feature. .

In this case, the priority may be set based on one or more of a location to be examined, a type of biosignal, a type of biometric information to be measured, and a computing capability of the biometric information measuring device.

The measurement state determination unit judges the noise state when the amplitude characteristic is normal and the period and waveform characteristics are abnormal, and determines the ambient optical noise state when the periodic characteristic is normal and the amplitude and waveform characteristics are abnormal, and the waveform characteristic is normal and the period and waveform characteristics are normal. If the amplitude characteristic is abnormal, it is judged as the non-measurement state of the biological signal.If the periodic characteristic is abnormal and the amplitude and waveform characteristics are normal, it is determined as arrhythmia.If the amplitude characteristic is abnormal and the period and waveform characteristics are normal, it is judged to be inadequate contact pressure. If the waveform characteristic is abnormal and the period and amplitude characteristics are normal, the defective contact state can be determined. If the period, amplitude and waveform characteristics are all normal, the normal measurement state can be determined.

According to an aspect, the method for monitoring a biosignal measurement state may include receiving a biosignal measured from a user, extracting one or more features of a waveform, a period, and an amplitude from the biosignal, and determining preset criteria according to the extracted feature. The method may include determining whether the extracted feature is normal and monitoring the measurement state of the biosignal based on the determination result.

The determining of whether the feature is normal may include determining whether the waveform feature is normal by applying a personalized waveform self criterion to the user when the waveform feature is extracted from the biosignal.

Determining whether the waveform characteristics are normal includes obtaining first and second waveforms from the waveform of the current period and the waveform of the reference period based on the derivative order information, and comparing the obtained first and second waveforms, respectively. And if the comparison result satisfies the failure condition, determining the extracted waveform feature as abnormal.

Comparing the waveforms may include calculating a similarity between the first waveform and the second waveform and determining whether the failure condition is satisfied based on the calculated similarity.

The determining of the normality of the feature may be performed by applying at least one of a personalized cycle self criterion and a periodic universal criterion, which is a general criterion for biometric information to be measured through the biosignal, when the periodic feature is extracted from the biosignal. It is possible to determine whether the feature is normal.

The determining of whether the feature is normal may include determining whether the extracted amplitude feature is normal by applying a personalized amplitude self criterion to the user when the amplitude feature is extracted from the biosignal.

The monitoring of the measurement state of the biosignal may output at least one of reliability and measurement state information of the biosignal measurement by considering the determination result of each feature in parallel or serially according to a predetermined priority for each feature. Can be.

According to an aspect, the apparatus for measuring biometric information may include: a biosignal measuring unit configured to radiate light onto a subject and receive light reflected from the subject, and measure one or more features from the biosignal; The processor may include a processor configured to monitor a measurement state of the biosignal by applying a predetermined determination criterion, and output a processing result of the processor and a processor to the display according to the monitoring result.

The biosignal measuring unit may include one or more light sources for irradiating light to the subject and one or more detectors for receiving light reflected from the subject.

The processor may include a measurement state monitoring unit configured to determine whether the extracted feature is normal by applying at least one of a self criterion and a universal criterion included in the criterion, and output measurement state information based on the determination result.

The processor further includes a measurement control unit controlling the biosignal measurement unit to stop or remeasure the biosignal measurement based on the output measurement state information, and a biometric information measurement unit measuring biometric information using the biosignal according to the measurement state information. can do.

The biometric information may include one or more of heart rate, arrhythmia, blood pressure, vascular age, arteriosclerosis, aortic pressure waveform, vascular elasticity, stress index, and fatigue.

The biometric information measuring apparatus may further include a storage configured to store one or more of a determination criterion, a measured biosignal, a result of determining whether each feature is normal, a monitoring result of a biosignal measuring state, and a biometric measuring result.

The biometric information measuring apparatus may further include a communication unit configured to communicate at least one of a predetermined determination criterion, a measured biosignal, a result of determining whether each feature is normal, a monitoring result of a biosignal measurement state, and a biometric information measuring result with an external device. can do.

According to one aspect, a method of measuring biometric information includes irradiating light to a subject and receiving light reflected from the subject to measure a biosignal, extracting one or more features of a waveform, a period, and an amplitude from the biosignal; The method may include monitoring a measurement state of the biosignal by applying a predetermined determination criterion according to the extracted feature and performing a predefined operation according to the monitoring result.

The monitoring of the measurement state of the bio-signal may include determining whether the extracted feature is normal by applying at least one of self criteria and universal criteria included in the criterion; And outputting measurement state information including at least one of an ambient light noise state, a biosignal non-measurement state, an arrhythmia state, a contact pressure failure state, a contact failure state, and a normal measurement state.

The step of performing the predefined operation may control the stop or re-measurement of the biosignal based on the measurement state information, or measure the biometric information based on the measured biosignal.

The biometric information measuring method may further include outputting the biometric information measuring result.

It is possible to monitor the biosignal measurement state using the measured biosignal without using an additional sensor, thereby measuring accurate biometric information.

1 is a block diagram of an apparatus for monitoring a biosignal measurement state according to an exemplary embodiment.
FIG. 2 is an embodiment of a processor configuration of the monitoring apparatus according to the embodiment of FIG. 1.
3 is another embodiment of a processor configuration of the monitoring apparatus according to the embodiment of FIG. 1.
4A to 4C are diagrams for describing monitoring of a biosignal measurement state.
5 is a flowchart illustrating a method for monitoring biosignal measurement status according to an exemplary embodiment.
6 is a flowchart of a method for monitoring biosignal measurement status according to another exemplary embodiment.
7 is a block diagram of an apparatus for measuring biometric data according to an exemplary embodiment.
8 is a block diagram of an apparatus for measuring biometric information according to another exemplary embodiment.
FIG. 9 is an embodiment of a processor configuration in accordance with the embodiment of FIGS. 7 and 8.
10 is a flowchart illustrating a method of measuring biometric information according to an embodiment.
11 illustrates a wearable device to which the above-described biometric information measuring apparatus is applied.
12 illustrates a smart device to which the biometric information measuring apparatus is applied.

Specific details of other embodiments are included in the detailed description and the drawings. Advantages and features of the described technology, and methods of achieving them will be 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 and second may be used to describe various components, but the components should not be limited by the terms. The terms are only used to distinguish one component from another. Singular expressions include plural expressions unless the context clearly indicates otherwise. In addition, when a part is said to "include" a certain component, which means that it may further include other components, except to exclude other components unless otherwise stated. In addition, the terms “… unit”, “module”, etc. described in the specification mean a unit that processes at least one function or operation, which may be implemented in hardware or software, or a combination of hardware and software.

Hereinafter, a feature extraction apparatus and method for biometric information detection, and embodiments of the biometric information detection apparatus and wearable device will be described in detail with reference to the accompanying drawings.

1 is a block diagram of an apparatus for monitoring a biosignal measurement state according to an exemplary embodiment.

Referring to FIG. 1, the biosignal measurement state monitoring apparatus 100 may include a biosignal receiver 110 and a processor 120.

The biosignal receiver 110 may receive a biosignal of a user. At this time, the biosignal may be an electrocardiogram (Electorcardiography, ECG), photoelectric pulse wave (PPG) and EMG (Electormygraphy, EMG) signal and the like, but is not limited thereto.

For example, the biosignal receiving unit 110 may include a biosignal measuring sensor for measuring a biosignal from a user. As another example, the biosignal sensor may be connected to the biosignal measurement sensor via wired or wireless communication to receive a biosignal of the user from the biosignal measurement sensor. As another example, the biosignal receiver 110 may receive the biosignal data through wired or wireless communication from an external device. In this case, the external device may be an information processing device such as a wearable device, a smart phone, a tablet PC, a desktop PC, a notebook PC, and the like, and may be a device that processes and manages biosignal data.

When the biosignal of the user is received, the processor 120 may monitor a state of measuring the biosignal from the user by using the received biosignal. For example, the processor 120 may monitor a measurement state of the biosignal based on a predetermined criterion, wherein the preset criterion is personalized to a universal standard and a user, which are general criteria to be measured through the biosignal. Can include its own criteria.

For example, a biosignal which is generally measured repeatedly has a feature that is repeated similarly for a certain time. Typically, there are periods and amplitudes, and these features have characteristics that do not diverge or converge. In addition, like the biosignal waveform, there is a characteristic of repeating the biosignal only for a predetermined time. In this case, when the biometric information to be measured is a heart rate, there is a standard that can be determined to be normal with respect to a cycle, for example, a universal standard such as 30 bpm to 180 bpm. As such, there may be a universal standard applicable to most people according to the kind, characteristics, and the like of the biosignal, but the universal standard may not exist depending on the biosignal. In this case, according to one embodiment, a self criterion may be predefined based on a biosignal and a user's characteristics.

2 and 3, various embodiments of the processor 120 configuration will be described in more detail. However, the present invention is not limited thereto, and various modifications may be made to the configuration of the processor 120.

FIG. 2 is an embodiment of a processor configuration of the monitoring apparatus according to the embodiment of FIG. 1.

2, the processor 200 according to an embodiment may include a feature extractor 210, a feature determiner 220, a measurement state determiner 230, and a buffer 240.

When the biosignal is received, the feature extractor 210 may extract one or more features from the received biosignal. In this case, the feature may include an amplitude, a period, and a waveform feature, but is not limited thereto. When the biosignal is received, the feature extractor 210 may remove noise by filtering the biosignal as needed. In addition, the feature extractor 210 may perform a normalization process if necessary to compare the extracted feature with a determination criterion.

Meanwhile, the feature extractor 210 may store the currently extracted feature in the buffer 240 so that the extracted feature may be used as a reference for determining whether the extracted feature is normal.

For example, the feature extractor 210 may extract the difference between the maximum value and the minimum value as the amplitude feature in the biosignal or the filtered biosignal for a specific time. In addition, the extracted amplitude feature of the current view may be stored in the buffer 240 to be used as a reference for determining whether the amplitude feature of the next view is normal.

4A illustrates a biosignal or a filtered biosignal, eg, a PPG signal, measured from a user. As shown in FIG. 4A, the amplitude of the amplitude maximum point Amax, which is the difference between the amplitude maximum point Amax and the amplitude minimum point Amin, for a time from 0 to 140, may be extracted as an amplitude feature. . Alternatively, the feature extractor 210 obtains the second differential signal by performing the second derivative of the biosignal, and obtains the time of the local minimum point having a minimum size for a specific time from the obtained second differential signal. The amplitude corresponding to the time of the local minimum point in the biosignal may be extracted as an amplitude feature. However, it is not limited thereto.

As an example, the feature extractor 210 may extract the current period of the biosignal and store it in the buffer 240. As shown in FIG. 4A, the feature extractor 210 extracts the interval between the time point 140 at which the amplitude magnitude becomes the first zero from the time point 0 when the amplitude magnitude becomes 0 from the received biosignal or the filtered biosignal in the current period. can do. However, the present invention is not limited thereto.

In addition, the feature extractor 210 may extract an average period of the biosignal and store it in the buffer 240. The feature extractor 210 obtains the total number of time points of zero amplitude magnitude during a specific time, and calculates an average period based on the obtained total number of times. For example, a time interval obtained by dividing a specific time by the total number of times may be calculated as an average period.

In addition, the feature extractor 210 extracts a waveform feature from the received biosignal or the filtered biosignal, and uses the extracted waveform feature of the current view as a reference for determining whether the extracted waveform feature is normal. The buffer 240 may be stored as much as possible.

For example, the feature extractor 210 may extract m values set to the number of comparison samples continuously in the current time interval to form a waveform feature. In this case, the extracted value may be the magnitude (eg, amplitude), n-th order differential value, or integral value of the biosignal. However, the present invention is not limited thereto and may be various values that may be extracted from the biosignal. At this time, the number of samples can be made constant. In addition, the length of the time interval to extract the waveform feature may be preset to any value. Alternatively, as described above, one period extracted in the period feature extraction process may be set as the length of the time interval. In this case, when each period, for example, the time period of the previous period and the current period is different, each period can be normalized so that the length of the time interval is the same, thereby making the number of signal samples extracted in each period equal. have. In addition, the number of m samples to be extracted may be predefined in the waveform self determination criteria.

When each feature is extracted by the feature extractor 210, the feature determiner 220 may determine whether the extracted feature is normal by using a universal standard and / or its own standard defined according to each feature. In this case, the universal standard and / or its own standard may be applied in series or in parallel. In this case, the feature determination unit 220 may determine whether the feature is normal by obtaining information related to the universal standard or the self standard defined according to each feature with reference to the buffer 240.

When the amplitude feature is extracted from the biosignal at the present time, the feature determiner 220 may determine whether the extracted amplitude feature is normal by using the amplitude self-reference. At this time, the amplitude self-reference is a difference between the amplitude characteristic value measured at the reference time point and the amplitude feature value measured at the present time point is out of a specific range, or the amplitude feature value at the current time point is out of a specific ratio with respect to the amplitude feature value at the reference time point. In this case, it may be set in advance to determine abnormality. However, the self standard may be variously set according to the characteristics of the biological signal, the type of the biological information, the personal characteristics of the user, for example, the state of health and the specificity of the test site.

However, the present invention is not limited thereto, and there may be an amplitude universal standard that can be commonly applied according to the type of the biosignal, the type of the biosignal information to be extracted, and the characteristics of the extracted biosignal. In this case, the feature determiner 220 may determine whether the amplitude feature is normal by applying the amplitude universal reference together with or separately from the amplitude itself reference.

When the current period and / or average period feature of the current time point is extracted, the feature determination unit 220 determines whether the period feature is normal by applying the current universal period and / or the average period feature to the period universal criterion and / or the period itself. can do. In this case, the periodic universal criterion may be a standard generally applied according to the biosignal and the biometric information. For example, when the heart rate is measured through the PPG signal, a universal criterion may be determined to be normal when satisfying 30 bpm to 180 bpm.

In addition, the cycle itself reference is preset in consideration of the user's personal characteristics such as gender, health status, age, the location of the test and the location of the test, and the difference between the current cycle value at the present time and the reference time If it is out of a specific range or the current period is out of a specific ratio of the period of the reference time point, it may be preset to determine that it is abnormal. In this case, the reference time point may mean a immediately preceding period extracted at the last time point. For example, when the previous period is 0.84 seconds (about 71 bpm), the period itself may be defined as a normal range between 0.67 seconds and 1.01 seconds, which is 20% of 0.84 seconds, and the feature determination unit 220 may determine that the extracted current period is If it is out of 1.07 seconds from 0.67 seconds, it can be determined as abnormal.

When the waveform feature of the current time interval is extracted, the feature determiner 220 obtains information on the waveform self-reference by referring to the buffer 240, and normalizes the extracted waveform feature by using the obtained information on the waveform self-reference. It can be determined.

The waveform self criterion may include a reference time interval, comparison sample count, derivative / integral order, failure condition, and the like. In this case, the reference time interval may be the immediately preceding time interval from which the waveform is extracted at the immediately preceding time point. In addition, the time interval may be a period unit. Hereinafter, for convenience of description, the reference time section and the current time section are limited to the reference period and the current period, but are not limited thereto.

In addition, the number of comparison samples may be preset based on a sampling rate, a buffer size, and the like as the number of samples to be extracted from the biosignal. For example, if the biosignal sampling rate is 250 Hz, 50 samples corresponding to a 20% rate may be set as the number of samples to be extracted. In addition, one or more failure conditions may be set, and when two or more are set, the waveform characteristics may be set to be determined abnormally when some or all predefined conditions are satisfied. For example, the failure condition may include information such as the lowest threshold of similarity, the number of consecutive failures of the lowest threshold, the similarity starting point, and the total number of bits for the average similarity. However, it is not limited thereto.

For example, when the waveform feature of the current period is extracted, the feature determiner 220 obtains the waveform feature of the reference period by referring to the buffer 240 and calculates the similarity between the waveform feature of the current period and the waveform feature of the reference period. Can be calculated. In this case, since the extracted both waveforms are m consecutive values, the correlation coefficient r _{x, y} may be calculated as the similarity as shown in Equation 1 below. In this case, an outlier may be excluded from m waveform features.

Where μ _x is the mean of population X, μ _y is the mean of population Y, σ _x is the standard deviation of population X, σ _y is the standard deviation of population Y, and m is the population of the population. The range of the correlation coefficient (r _{x, y} ) is -1 ≦ r _{x, y} ≦ 1. As the value of the correlation coefficient approaches 1, the two waveforms to be compared are similar. However, the present invention is not limited thereto, and statistical values such as an average value and a sum of the plurality of samples of both waveform features may be calculated with similarity.

The feature determiner 220 may determine that the calculated similarity is abnormal when the calculated similarity deviates from the lowest limit value of the waveform itself. Alternatively, when the waveform characteristic of the current cycle is abnormal and the determination result continuously determined for the previous cycles satisfies the number of consecutive failures of the lowest threshold, the waveform characteristic may be finally determined to be abnormal. The feature determiner 220 may calculate the similarity using values after the similarity comparison start point.

On the other hand, the feature determiner 220 differentials / integrates the waveform of the current period and the waveform of the reference period with corresponding orders based on the derivative / integral order information in the waveform self-reference information to obtain the first waveform and the second waveform, respectively. can do. In this case, when the derivative / integral order is set to 0, it may be the extracted waveform feature itself. The feature determiner 220 may compare the obtained first waveform and the second waveform to calculate similarity, and determine whether the current periodic waveform feature is normal using the similarity calculated as described above.

Referring to FIG. 4B, when the similarity between the current waveform and the reference waveform extracted from the PPG signal is equal to or less than the value 0.7, the controller determines that it is abnormal and inputs '0' to the buffer 240. An example of inputting '1' at 240 is shown. It can be seen that the comparison result between the similarity and the lowest threshold at the present time point T7 is determined to be normal. If the minimum threshold continuous failure is set to '4', the determination result is abnormal (0) at the time T4, and since there have been four abnormal judgments consecutively including the time T4, the last of the waveform features acquired at the time T4. Judgment results will be abnormal.

Referring to FIG. 4C, when the similarity between the current waveform and the reference waveform obtained from the second derivative of the PPG signal of FIG. 4B is equal to or less than the value 0.6 set as the lowest threshold, it is determined to be abnormal and inputs “0” to the buffer 240. If it is greater than 0.6, it is determined that it is normal and '1' is input to the buffer 240.

The measurement state determination unit 230 monitors a state in which the bio signal is finally measured by the user in consideration of the determination result of each feature, and outputs at least one of reliability and measurement state information of the bio signal measurement state as a monitoring result. can do. In this case, the measurement state information may include at least one of a dynamic noise state, an ambient light noise state, a biosignal non-measured state, an arrhythmia state, a contact pressure misfit state, a poor contact state, and a normal measurement state. The measurement state determiner 230 may output reliability and / or measurement state information in consideration of the determination result of each feature in parallel. Alternatively, the final monitoring result may be output by serially determining in consideration of the priority of each feature set in advance.

For example, if the amplitude characteristic is normal and the period and waveform characteristics are abnormal, the measurement state determination unit 230 may determine that the measurement state is a dynamic noise state with much noise. Alternatively, when the periodic characteristic is normal and the amplitude and waveform characteristics are abnormal, it may be determined as an optical noise state indicating that there is much ambient optical noise. Alternatively, when the waveform characteristic is normal and the period and amplitude characteristics are abnormal, it may be determined that the biosignal non-measurement state indicates that the biosignal is not measured. Alternatively, if the periodic characteristic is abnormal and the amplitude and waveform characteristics are normal, it may be determined as an arrhythmia. Alternatively, if the amplitude characteristic is abnormal and the period and waveform characteristics are normal, it may be determined that the contact pressure is inadequate. Alternatively, when the waveform characteristic is abnormal and the period and amplitude characteristics are normal, it may be determined that the contact is in a bad state of contact or that there is a tremor. Alternatively, if the period, amplitude, and waveform characteristics are all normal, it may be determined as a normal measurement state. However, since this is only one example, a combination of various states is possible.

3 is another embodiment of a processor configuration of the monitoring apparatus according to the embodiment of FIG. 1. Since it has been described in detail with reference to Figure 2 will be described briefly below.

Referring to FIG. 3, the processor 300 according to an embodiment may include a time index calculator 311, an R-index detector 312, a current period extractor 313, an average period extractor 314, and an amplitude extractor. Unit 315, waveform extractor 316, average period determiner 321, current period determiner 322, amplitude determiner 323, waveform determiner 324, measurement state determiner 330, And an R-index buffer 341, a periodic buffer 342, an amplitude buffer 343, and a waveform buffer 344.

The time index calculator 311 may measure time when the biosignal data is input. For example, the rate at which biosignal data is input is determined according to a sampling rate and a buffer size, thereby enabling time measurement.

The R-index detector 312 may detect the R-peak index from the input biosignal or the filtered signal from which the noise is removed. The R-peak index is a reference value for the period measurement in the biosignal. For example, as described above, the point in which the biosignal changes from (-) to (+), (+) to (-), and the inflection It may be a point where it occurs. In addition, the R-index detector 312 may input the R-index buffer 314 when the R-peak index is detected.

The current period extractor 313 may extract the current period by referring to the R-peak index stored in the R-index buffer 314. The current period extractor 313 may store the extracted current period value in the period buffer 342 so that it can be used as a reference period of the next time point.

The average period extractor 314 may calculate an average period using period information stored in the period buffer 342 and time values measured by the time index calculator 311. For example, during a predetermined time (for example, 30 minutes) measured by the time index calculator 311, the current period extractor 313 is extracted into three cycles, for example, 10 minutes, 8 minutes, and 12 minutes, and the periodic buffer ( If stored in 342, the average period may be 10 minutes.

The amplitude extractor 315 may extract an amplitude feature value from the input biosignal or the filtered signal. For example, the amplitude extractor 315 may extract a difference between the maximum value and the minimum value within the current period, for example, as an amplitude value from the biosignal or the filtered biosignal for a specific time. In addition, the extracted amplitude value may be input to the amplitude buffer 343 to be used as a self-reference for comparison of the amplitude values at the next time point.

The waveform extractor 210 may extract waveform features from the received biosignal or the filtered biosignal. In this case, a plurality of samples may be extracted from the biosignal itself or the differential signal obtained by differentiating the biosignal. In this case, the plurality of samples may be extracted as a waveform feature by using the N-th order differential information and the comparison sample number information of the determination reference information. The extracted waveform feature of the current view may be input to the waveform buffer 344 to be used as a reference for determining whether the waveform feature of the next view is normal.

The average period determiner 321 may determine whether the average period extracted by the average period extractor 314 is normal by using a period universal reference among the input criteria. The current period determination unit 322 determines whether the current period value extracted by the current period extraction unit 313 is normal based on the reference period value stored in the period buffer 342 and the period itself reference among the input determination criteria. You can judge.

The amplitude determiner 323 may determine whether the current amplitude value extracted by the amplitude extractor 315 is normal by applying the reference amplitude value stored in the amplitude buffer 343 and the amplitude self criterion among the input determination criteria. have.

The waveform determination unit 316 may determine whether the current waveform extracted by the waveform extraction unit 316 is normal by applying the reference waveform stored in the waveform buffer 344 and the waveform itself reference among the input determination criteria. In this case, the similarity between the reference waveform and the current waveform may be calculated, and whether the current waveform is normal may be determined based on the calculated similarity.

When the determination result of the average period, the current period, the amplitude, and the waveform feature is input, the measurement state determiner 330 monitors the state in which the bio signal is finally measured by the user in consideration of the determination result of each feature in series / parallel. can do. Whether to consider serially or in parallel may be preset in the input determination criteria. When considered serially, the priority between each feature may be predefined.

The measurement state determiner 330 may output at least one of reliability and measurement state information of the biosignal measurement state as a monitoring result. In this case, the measurement state information may include at least one of a dynamic noise state, an ambient light noise state, a biosignal non-measured state, an arrhythmia state, a contact pressure misfit state, a poor contact state, and a normal measurement state.

For example, the measurement state determiner 330 may determine the noise state when the amplitude characteristic is normal and the period and waveform characteristics are abnormal, and the ambient light noise state when the period characteristic is normal and the amplitude and waveform characteristics are abnormal. You can judge. Alternatively, when the waveform characteristic is normal and the period and amplitude characteristics are abnormal, the biosignal non-measured state may be determined. When the periodic characteristic is abnormal and the amplitude and waveform characteristics are normal, the arrhythmia may be determined. Alternatively, if the amplitude characteristic is abnormal and the period and waveform characteristics are normal, it may be determined as a contact pressure incompatibility state. If the waveform characteristic is abnormal and the period and amplitude characteristics are normal, it may be determined as a contact failure state. In contrast, if the period, amplitude, and waveform characteristics are all normal, it can be determined as a normal measurement state.

5 is a flowchart illustrating a method for monitoring biosignal measurement status according to an exemplary embodiment.

FIG. 5 may be an embodiment of a method performed by the biosignal measurement state monitoring apparatus 100 according to the embodiment of FIG. 1. Since it was described in detail with reference to Figure 1 below it will be briefly described.

Referring to FIG. 5, the device 100 may receive a biosignal of a user (510). In this case, the biosignal may be a PPG signal measured from a user's test site. However, the type of the biosignal is not limited thereto. The biosignal measured from the user may be received from the biosignal measuring sensor. Alternatively, the biosignal may be received from an external device that receives the biosignal from the biosignal measuring sensor. In this case, when the biosignal is input, the biosignal may be filtered to remove noise as necessary.

Next, one or more features of amplitude, period, and waveform may be extracted from the input biosignal (520). The amplitude characteristic may be a difference value between the maximum value and the minimum value for a specific time as described above. The periodic feature may include a current period and an average period value. In addition, a value corresponding to a predetermined number of comparison samples for a predetermined time interval may be extracted from the biosignal as a waveform feature. In this case, a plurality of samples may be extracted from the biosignal, the filtered signal itself, or the differential signal.

Next, it may be determined whether each feature extracted in operation 520 is normal by applying a predetermined determination criterion (530). In this case, the predetermined determination criterion may be set for each feature, and may include a universal standard applicable to the biosignal and the biometric information to be measured, and a self criterion specialized for the user. The apparatus 100 may determine whether each feature is normal by applying the universal standard and its own standard in series or in parallel according to each feature.

In operation 540, the biosignal measurement state may be determined based on the result determined in operation 530. In step 530, if it is determined whether the amplitude, period, and waveform characteristics are normal, the determination result is applied in parallel or in series according to a predefined priority to determine a state in which the bio signal is measured from the user. can do.

Next, the measurement state determination result may be output (550). For example, the device 100 may output in a non-visual method or a visual method such as voice, vibration, and touch through an external display, a haptic, a speaker module, or the like directly mounted or connected to the device 100. Alternatively, the measurement state determination result may be transmitted to the external device that has requested the determination of the bio signal measurement state.

6 is a flowchart of a method for monitoring biosignal measurement status according to another exemplary embodiment. FIG. 6 may be an embodiment of a biosignal measurement state monitoring method performed by the biosignal measurement state monitoring apparatus 100 according to the embodiment of FIG. 1. Since it has been described in detail with reference to Figure 1 below it will be briefly described.

First, the device 100 may receive a user's biosignal (610). In this case, the biosignal is a signal measured from a user's test site and may be received from a biosignal measuring sensor or an external device.

Next, one or more features of amplitude, period, and waveform may be extracted from the input biosignal (620).

Next, when the amplitude feature is extracted in step 620, it may be determined whether the amplitude feature is normal by applying the amplitude self criterion (631). In this case, the amplitude self criterion is previously defined in consideration of personalization characteristics to the user, and may include error range information for determining the reference time point and abnormality. In this case, the reference error range may be range information that is determined to be abnormal when the difference between the amplitude feature value at the reference time point and the amplitude feature value measured at the present time point or the ratio of the amplitude feature value at the current time point to the amplitude feature value at the reference time point is out of range. .

In operation 620, when the periodic feature is extracted, whether or not the periodic feature is normal may be determined by applying at least one of the periodic self criterion and the periodic universal criterion. For example, the periodic feature may include an average period and a current period, the average period may apply the period universal criterion, and the current period may apply the period itself criterion. For example, as described above, in the case of heart rate measurement, when the average period satisfies 30bpm to 180bpm, it may be determined as normal. In addition, as described above, when the current period value is out of the range of 20% of the previous period value, it may be determined to be abnormal.

In addition, when the waveform feature is extracted in operation 620, it may be determined whether the extracted waveform feature is normal by applying the waveform self-reference. The waveform self criterion may include a reference time interval, comparison sample count, derivative / integral order, failure condition, and the like. In this case, the failure condition may be set to determine abnormality when the similarity between the two waveforms is out of a predetermined minimum threshold. At this time, the device 100 calculates the similarity between the waveform of the reference time interval and the waveform of the current time interval, or the similarity between the two differential waveforms obtained by differentiating the two waveforms, and compares the calculated similarity with the lowest threshold to determine normality. can do.

Steps 631 to 633 are not necessarily present in order, but may be performed simultaneously or sequentially depending on the setting.

Next, the apparatus 100 may determine whether the determination result of the amplitude characteristic is normal or abnormal (640), and if the determination result is abnormal, output the 'measurement state 3' as the final determination result of the biosignal measurement state ( 673). In this case, the 'measurement state 3' may be, but is not limited to, a contact pressure incompatibility state, an ambient light noise state, or a biosignal nonmeasurement state. For example, FIG. 6 shows only the movement to step 673 immediately when the amplitude characteristic is abnormal in step 640. However, in the case where the amplitude characteristic is abnormal, the result of determining whether the periodic characteristic and the waveform characteristic are normal will be considered. As a result, the definition of 'measurement state 3' may be variously modified.

Next, as a result of confirming whether the amplitude feature is normal in step 640, the periodic feature may be considered in case of normality (650). For example, the process of checking whether the average period is normal (651) and the process of checking whether the current period is normal (652) is performed in parallel, and if both the average period and the current period is normal to determine whether the waveform characteristics are normal In operation 660, if any one is abnormal, the measurement state 1 may be output (671). In this case, the 'measurement state 1' may be a dynamic noise state, arrhythmia state or poor contact state, but is not limited thereto. For example, unlike in FIG. 6, even if the periodic feature is abnormal, the waveform feature may be additionally considered normal, and according to the result, the definition of 'measurement state 1' may be variously modified.

Next, when the determination result of the periodic feature is normal in step 650, the result of the determination of the waveform feature is checked (660), and if it is normal, it outputs' measurement state 2 '(672), and if abnormal,' measurement state 1 'Can be output (671). In this case, the 'measurement state 2' may be a normal measurement state.

7 is a block diagram of an apparatus for measuring biometric data according to an exemplary embodiment. 8 is a block diagram of an apparatus for measuring biometric information according to another exemplary embodiment.

The biometric information measuring apparatuses 700 and 800 of FIGS. 7 and 8 measure a biosignal such as a PPG signal from a user, and use the measured biosignal to measure heart rate, arrhythmia, blood pressure, vascular age, arteriosclerosis, and aortic pressure. It may be a device for measuring biometric information including at least one of waveform, vascular elasticity, stress index and fatigue. The biometric information measuring apparatuses 700 and 800 according to the exemplary embodiments may be equipped with various technical aspects for monitoring the aforementioned biosignal measuring state.

Referring to FIG. 7, the biosignal measuring unit 710, the processor 720, and the output unit 730 may be included.

The biosignal measuring unit 710 may measure various biosignals from the subject OBJ. For example, the biosignal may be an electrocardiogram (Electorcardiography, ECG), a photoplethysmogram (PPG), an electromyography (Electormygraphy, EMG) signal, or the like, but is not limited thereto. Hereinafter, the PPG signal will be described as an example. In this case, the subject OBJ may be a position where the capillary blood or the venous blood of the upper wrist and the finger pass. However, the present invention is not limited thereto, and the radial artery of the lower wrist may pass.

The biosignal measuring unit 710 detects one or more light sources 711 for irradiating light to the subject and light from which the light irradiated onto the subject by the one or more light sources 711 is scattered or reflected from the subject. It may include one or more detector 712.

One or more light sources 710 may be formed of a light emitting diode (LED), a laser diode (LD), a phosphor, or the like. However, it is not limited thereto. In this case, when formed of a plurality of light sources, each light source may be formed to irradiate light of different wavelengths. In addition, each light source may be disposed on a different distance from the detector 712. The one or more detectors 712 may be formed of a photo diode, a photo transistor (PTr), an image sensor (eg, a CMOS image sensor), or the like.

The processor 720 may be electrically connected to the biosignal measuring unit 710. The processor 720 may receive the biosignal measured from the subject OBJ. In addition, the processor 720 may determine a state in which the biosignal measuring unit 710 measures the biosignal from the subject OBJ based on the received biosignal. In addition, various predefined operations may be performed based on a result of determining the biosignal measurement state. Various embodiments of the processor 720 configuration will be described in more detail with reference to FIG. 9.

The output unit 730 may output a processing result of the processor 720, for example, a bio signal measurement state determination result, a biometric information measurement result, etc. in various visual and non-visual manners. For example, the output unit 730 may visually output through the display. For example, when the measured blood pressure deviates from the user's usual blood pressure, the blood pressure value may be displayed in red or the vibration may be warned through the haptic module. Alternatively, the user may be notified that an abnormal situation has occurred by voice, and guide the action to be taken by the user. In addition, a speaker module, a haptic module, or the like may be used to output non-visually in a manner such as voice, touch, and vibration.

Referring to FIG. 8, the biometric information measuring apparatus 800 may further include a storage unit 810 and a communication unit 820 in addition to the biosignal measuring unit 710, the processor 720, and the output unit 730.

The storage unit 810 may store various reference information and the processing result of the biosignal measuring unit 710 or the processor 720. In this case, the various reference information includes user information such as user's age, gender, health status, linear functional formula or biometric information measuring model for measuring biometric information, criteria for determining each feature such as amplitude self standard, periodic universal standard, periodic self standard and It may include information such as waveform self-reference.

In this case, the storage unit 810 may be a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (eg, SD or XD memory). Etc.), Random Access Memory (RAM), Random Random Access Memory (SRAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Programmable Read-Only Memory (PROM), Magnetic Storage media such as memory, magnetic disks, optical disks, and the like, but are not limited thereto.

The communication unit 820 may communicate with the external device 850 under the control of the processor 720 to cooperate with various operations related to the measurement of the biometric information. In this case, the external device 470 may include a smartphone, a tablet PC, a desktop PC, a notebook PC, and the like, and may include a device of a medical institution including a cuff-type blood pressure measuring device, but is not limited thereto.

For example, the communicator 820 may transmit a biosignal measurement result or a processing result of the processor 720 to the external device 850 to allow the external device 850 to manage the biometric information history for the user and the user's health state. Monitoring, biometric information history, and output of health status monitoring results can be performed. As another example, the communication unit 820 may receive information about a linear functional formula or a biometric information measuring model required for measuring biometric information from the external device 850. The received information may be stored in the storage 810.

In this case, the communication unit 820 may include Bluetooth communication, BLE (Bluetooth Low Energy) communication, Near Field Communication (Near Field Communication), WLAN communication, Zigbee communication, Infrared Data Association (IrDA) communication. Can communicate with external devices using WFD (Wi-Fi Direct), UWB (ultra-wideband), Ant +, WIFI, Radio Frequency Identification (RFID), 3G, 4G, and 5G have. However, this is only an example and is not limited thereto.

FIG. 9 is an embodiment of a processor configuration in accordance with the embodiment of FIGS. 7 and 8. Referring to FIG. 9, the processor 720 may include a biosignal receiver 721, a measurement state monitoring unit 722, a measurement control unit 723, and a biometric information measurement unit 724.

The biosignal receiver 721 may receive a biosignal from the biosignal measuring unit 710. The biosignal receiver 721 may remove noise by filtering the received biosignal as needed.

When the biosignal is received, the measurement state monitoring unit 722 may monitor the measurement state of the biosignal from the user's subject based on the received biosignal. For example, the measurement state monitoring unit 722 may extract an amplitude, a period, and a waveform feature from the biosignal, and monitor the measurement state of the biosignal based on the extracted feature. As described above, when each feature is extracted, it is determined whether or not it is normal for each feature by applying one or more of a predetermined universal standard and its own standard according to each feature, and the biosignal measurement state is comprehensively considered in consideration of the determination result of each feature. Can finally determine and output the determination result. In this case, the determination result of the output biosignal measurement state may include biosignal measurement reliability information and / or measurement state information. The measurement state monitoring unit 722 may be an embodiment of the biosignal measurement state monitoring apparatus 100 described above, and thus will be omitted below.

The measurement control unit 723 stops the biosignal measurement by controlling the biosignal measurement unit 710 when the reliability of the determination result of the measurement state monitoring unit 722 is equal to or less than a preset threshold or the measurement state monitoring result is not a normal measurement state. You can either do it or remeasure it.

The biometric information measuring unit 724 may measure the biometric information using the measured biosignal when the reliability of the determination result of the measurement state monitoring unit 722 exceeds a preset threshold or the measurement state monitoring result is a normal measurement state. Can be. For example, the biometric information measuring unit 724 may measure the blood pressure by applying a predefined measurement model or a linear function to the measured PPG signal.

10 is a flowchart illustrating a method of measuring biometric information according to an embodiment.

FIG. 10 may be an embodiment of a biometric information measuring method performed by the biometric information measuring apparatuses 700 and 800 of FIGS. 7 and 8.

Referring to FIG. 10, the biometric information measuring apparatuses 700 and 800 may receive a biometric information measuring request (1011). The biometric information measurement request may be input from the user. Or it may be received from an external device connected to the communication. However, the present invention is not limited thereto and may determine that a request for measuring biometric information is automatically received when a predetermined period is reached.

In operation 1012, the biosignal may be measured from the subject of the user by controlling the light source and the detector of the biosignal measuring unit.

Next, if the biosignal is measured in step 1012, one or more features such as amplitude, period, and waveform may be extracted from the measured biosignal (1013). In this case, the type of feature to be extracted may be defined according to the type of the biosignal and the biometric information to be measured.

next. In operation 1014, whether the extracted feature is normal may be determined by applying a predetermined determination criterion according to each extracted feature. In this case, the determination criteria may be variously defined according to the extracted feature, the biosignal, the type of the biometric information, and the personalized characteristics of the user. For example, it may be defined for each characteristic such as amplitude self-reference, periodic universal reference, periodic self-reference and waveform self-reference. The determination of each feature may be determined in series in a predefined order, but is not limited thereto and may be determined in parallel.

Next, in operation 1015, the state in which the biosignal is measured may be monitored in consideration of the result of determining whether each feature is normal in operation 1014. For example, the measurement status may be monitored by considering the amplitude, the current period, the average period, and the result of the determination of the normality of the waveform in parallel or serially according to a predetermined priority. This may be variously defined according to criteria such as a bio signal, a type of bio information, a health state of a user, and a personal characteristic of a subject.

Next, a predefined operation may be performed according to the monitoring result of step 1015 (1016). For example, if the measurement state of the biosignal is normal as a result of monitoring in step 1015, the biosignal information may be measured based on the biosignal measured in step 1012. Otherwise, the measurement can be stopped or moved back to step 1012 to re-measure the biosignal.

Thereafter, the monitoring result and the biometric information measurement result may be output and provided to the user (1017).

11 illustrates a wearable device to which the above-described biometric information measuring apparatuses 700 and 800 are applied. As described above, various embodiments of the biometric information measuring apparatuses 700 and 800 may be mounted on a smart watch or a smart band type wearable device worn on a wrist. However, since this is only one example for convenience of description, the present embodiments are not limited to being applied only to a smart watch or a smart band type wearable device.

Referring to FIG. 11, the wearable device 1100 may include a device body 1110 and a strap 1130.

The strap 1130 may be configured to be flexible and be connected to both ends of the main body 1110 to be bent in the form of wrapping around the user's wrist or bent in the form of being separated from the user's wrist. Alternatively, the strap 1130 may be configured in the form of a band that is not separated. In this case, the strap 1130 may be formed to include air pockets or an air bag to have elasticity according to a change in pressure applied to the wrist, and may transmit a pressure change of the wrist to the body 1110.

A battery for supplying power to the wearable device 1100 may be built in the main body 1110 or the strap 1130.

In addition, the wearable device 1100 includes a biosignal measuring unit 1120 for measuring a pulse wave signal and a contact pressure signal from a subject, and a biosignal measurement state using the biosignal measured by the biosignal measuring unit 1120. A processor is built in that monitors and measures the user's biometric information based on the results.

The biosignal measuring unit 1120 may include a PPG sensor mounted on the lower portion of the main body 1110, that is, exposed to a portion contacting the subject (eg, a user's wrist) to measure the biosignal from the subject. In addition, when necessary for the measurement of biometric information, such as blood pressure, it may further include a contact pressure sensor mounted inside the main body 1110 to measure a contact pressure signal between the PPG sensor and the subject.

The PPG sensor may include one or more light sources for irradiating light to the subject and one or more detectors for detecting light emitted from the subject, and may measure PPG signals of a plurality of different wavelengths from the subject.

The processor generates a control signal according to a user's biometric information measurement request to control the biosignal measurement unit 1120, and uses a PPG signal and / or a contact pressure signal measured by the biosignal measurement unit 1120 to control the biosignal information. Biometric information can be measured.

When the biosignal measuring unit 1120 measures the biosignal from the user, the processor may monitor a measurement state of the biosignal using the measured biosignal. In this case, the processor may extract features such as amplitude, period, and waveform from the measured biosignal, and monitor the measurement state of the biosignal using various predefined criteria. The detailed description is omitted since it has been described above.

The display unit may be mounted on the front surface of the main body 1110, and may visually output a bio signal measurement state monitoring result and / or a bio information measurement result.

The user may adjust the pressure and the contact state between the biosignal measuring unit 1120 and the subject and measure the biosignal according to the monitoring result of the biosignal measuring state displayed on the display unit.

The wearable device 1100 may further include an operation unit 1140 that receives a user's control command and transmits the same to a processor. The operation unit 1140 may be mounted on the side of the main body 1110, and may include a function for inputting a command to turn on / off the power of the wearable device 1100.

In addition, the wearable device 1100 may be equipped with a communication unit that transmits and receives various data with an external device and various modules for performing additional functions provided by the wearable device 1100.

12 illustrates a smart device to which the biometric information measuring apparatuses 700 and 800 are applied. As shown in the drawings, various embodiments of the above-described biometric information measuring apparatus 700 and 800 may be applied to a smart device such as a smart phone, a tablet PC, and the like.

Referring to FIG. 12, the smart device 1200 may be mounted on the rear surface of the main body 1210 in a form in which the biosignal measuring unit 1230 is exposed to the outside. In this case, the biosignal measuring unit 1230 may include one or more light sources 1231 and one or more detectors 1232. Each light source 1231 may be formed of a light emitting diode (LED) or the like, and at least some of the light sources may be formed to emit light having different wavelengths. The detector 1232 may be formed of a photo diode, a photo transistor, or the like.

In addition, the display unit may be mounted on the front surface of the main body 1210. The display unit may visually output a biosignal measurement status monitoring result, a biometric information measurement result, and the like.

Meanwhile, the image sensor 1220 may be mounted on the main body 1210. When the user approaches the subject (eg, a finger) to the biosignal measuring unit 1230 to measure the biosignal, the image sensor 1220 may photograph the finger and transmit the same to the processor. At this time, the processor determines the relative position of the finger relative to the actual position of the bio-signal measuring unit 1230 from the image of the finger, and provides the relative position information of the finger to the user through the display unit to guide the bio-signal measurement more accurately. Can be.

Various modules for performing various functions of the above-described biometric information measuring apparatus may be mounted in the smart device 1200, and a detailed description thereof will be omitted.

In the meantime, the embodiments may be embodied as computer readable codes on a computer readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which data that can be read by a computer system is stored.

Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage devices, and the like, which may also be implemented in the form of carrier waves (for example, transmission over the Internet). Include. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. And functional programs, codes and code segments for implementing the embodiments can be easily inferred by programmers in the art to which the present invention belongs.

Those skilled in the art will appreciate that the present disclosure may be embodied in other specific forms without changing the disclosed technical spirit or essential features. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

100: bio-signal measurement state monitoring apparatus 110: bio-signal receiver
120, 200, 300: processor 210: feature extraction unit
220: feature determination unit 230: measurement state determination unit
240: buffer 311: time index calculation unit
312: R-index detector 313: current period extractor
314: average period extractor 315: amplitude extractor
316: waveform extraction unit 321: average period determination unit
322: current period determination unit 323: amplitude determination unit
324: waveform determination unit 330: measurement state determination unit
341: R-index buffer 342: periodic buffer
343: amplitude buffer 344: waveform buffer
1100: wearable device 1110: main body
1120: biosignal sensor 1130: strap
1140: operation unit 1200: smart device
1210: main body 1220: image sensor
1230: biosignal sensor 1231: light source
1232: Detector

Claims (34)

A biosignal receiver configured to receive a biosignal measured from a user; And
Extracting one or more features of a waveform, a period, and an amplitude from the biosignal, and determining whether the extracted feature is normal by applying a predetermined determination criterion according to the extracted feature, and based on the determination result. Biological signal measurement status monitoring device comprising a processor for monitoring the measurement status of the. The method of claim 1,
The processor is
And a feature determiner configured to determine whether the extracted waveform is normal by applying a personalized waveform self-reference to the user. The method of claim 2,
The waveform itself reference
A biosignal measurement state monitoring device including at least one of a reference time interval, a comparison sample number, a derivative order, and a failure condition. The method of claim 3,
The feature determination unit
When the waveform of the current time interval is extracted from the biosignal, first and second waveforms are obtained from the waveform of the current time interval and the waveform of the reference time interval, respectively, based on the differential order, and the obtained first waveform and And comparing a second waveform to determine the extracted waveform characteristic as abnormal when a comparison result satisfies the failure condition. The method of claim 4, wherein
The processor is
And a buffer for storing waveform data of a reference time interval of the biosignal. The method of claim 5,
The processor is
The apparatus may further include a feature extractor configured to extract the waveform of the current time interval from the biosignal and update waveform data of the reference time interval stored in the buffer by using waveform data of the current time interval when a preset update criterion is satisfied. Bio-signal measurement status monitoring device. The method of claim 4, wherein
And wherein the failure condition comprises at least one of a lowest threshold of similarity between waveforms, a number of consecutive non-compliances of the lowest threshold, a starting point of similarity comparison between waveforms, and a total number of bits for average similarity. The method of claim 7, wherein
The feature determination unit
And calculating a similarity between the first waveform and the second waveform, and determining the waveform characteristic as abnormal when the calculated similarity is less than a minimum threshold. The method of claim 8,
The feature determination unit
And determining the waveform characteristics as abnormal when the similarity between the first waveform and the second waveform is less than a minimum threshold and the minimum number of consecutive successive failures satisfies a preset number. The method of claim 8,
And the similarity between the waveforms includes one or more of correlation coefficients, averages, and sums between comparative samples of the first and second waveforms. The method of claim 1,
The processor is
When the periodic feature is extracted from the biosignal, whether the periodic feature is normal by applying at least one of a personalized periodic self criterion to the user and a periodic universal criterion, which is a general standard for biometric information to be measured through the biosignal. Biological signal measurement state monitoring device comprising a feature determination unit for determining. The method of claim 11,
The cycle feature is
And at least one of a current period of the biosignal and an average period for a predetermined time. The method of claim 1,
The processor is
And a feature determiner configured to determine whether the extracted amplitude feature is normal by applying a personalized amplitude self criterion to the user when the amplitude feature is extracted from the biosignal. The method of claim 1,
The processor is
A biosignal including a measurement state determiner configured to output at least one of reliability and measurement state information of the biosignal measurement by considering the determination result of each feature in parallel or serially according to a preset priority for each feature Measurement status monitoring device. The method of claim 14,
The priority is
A biosignal measurement state monitoring apparatus is set based on at least one of a location to be examined, a type of biosignal, a type of biometric information to be measured, and a computing capability of the biometric information measuring apparatus. The method of claim 14,
The measurement state determination unit
If the amplitude characteristic is normal and the period and waveform characteristics are abnormal, it is judged to be a dynamic noise state, and if the periodic characteristic is normal and the amplitude and waveform characteristics are abnormal, it is determined to be the ambient optical noise state, and the waveform characteristic is normal and the period and amplitude characteristics are If it is abnormal, it is judged as a non-measurement state of the biosignal, and if the periodic characteristic is abnormal and the amplitude and waveform characteristics are normal, it is determined to be arrhythmic. If the amplitude characteristic is abnormal and the period and waveform characteristics are normal, the contact pressure is not considered. A biosignal measurement state monitoring apparatus for determining a bad contact state when the characteristic is abnormal and the period and amplitude characteristics are normal, and determining the normal measurement state when the period, amplitude and waveform characteristics are all normal. Receiving a biosignal measured from a user;
Extracting one or more features of waveform, period, and amplitude from the biosignal;
Determining whether the extracted feature is normal by applying a predetermined determination criterion according to the extracted feature; And
And monitoring a measurement state of the biosignal based on the determination result. The method of claim 17,
Determining whether the feature is normal
And if the waveform feature is extracted from the biosignal, determining whether the waveform feature is normal by applying a personalized waveform self criterion to the user. The method of claim 18,
Determining whether the waveform features are normal
Obtaining a first waveform and a second waveform from the waveform of the current period and the waveform of the reference period, respectively, based on differential order information;
Comparing the obtained first waveform and second waveform; And
And determining the waveform characteristic as abnormal when the comparison condition satisfies a failure condition. The method of claim 19,
Comparing the waveforms
Calculating a similarity between the first waveform and the second waveform; And
And determining whether the failure condition is satisfied based on the calculated similarity. The method of claim 17,
Determining whether the feature is normal
If the periodic feature is extracted from the biosignal, the user may determine whether the periodic feature is normal by applying at least one of a personalized periodic self criterion and a periodic universal criterion, which is a general criterion for biometric information to be measured through the biosignal. Bio-signal measurement status monitoring method comprising the step of determining. The method of claim 17,
Determining whether the feature is normal
And if the amplitude feature is extracted from the biosignal, determining whether the extracted amplitude feature is normal by applying a personalized amplitude self criterion to the user. The method of claim 17,
Monitoring the measurement state of the bio-signal
And at least one of reliability and measurement state information of the biosignal measurement by outputting the determination result of each feature in parallel or serially according to a priority set in advance for each feature. A biosignal measuring unit configured to measure a biosignal by irradiating light onto a subject and receiving light reflected from the subject;
A processor configured to extract at least one feature from the biosignal, apply a predetermined determination criterion according to the extracted feature, monitor a measurement state of the biosignal, and perform a predefined operation according to a monitoring result; And
And an output unit configured to output a processing result of the processor to a display. The method of claim 24,
The biosignal measuring unit
One or more light sources for irradiating light to the subject; And
And at least one detector for receiving light reflected from the subject. The method of claim 24,
The processor is
A biometric information measuring device including a measurement state monitoring unit configured to determine whether the extracted feature is normal by applying at least one of a self criterion and a universal criterion included in the criterion, and output measurement state information based on the determination result . The method of claim 26,
The processor is
A measurement controller configured to control the biosignal measurement unit to stop measuring the biosignal or remeasure the biosignal based on the output measurement state information; And
And a biometric information measuring unit configured to measure biometric information using the measured biosignal according to the output measurement state information. The method of claim 27,
The biometric information is
A biometric information measuring device including at least one of heart rate, arrhythmia, blood pressure, blood vessel age, arteriosclerosis, aortic pressure waveform, vascular elasticity, stress index, and fatigue degree. The method of claim 24,
And a storage unit which stores at least one of the determination criteria, the measured bio-signals, a result of determining whether each feature is normal, a monitoring result of the bio-signal measurement state, and a bio-information measurement result. The method of claim 24,
Biometric information further comprises a communication unit for communicating at least one of the predetermined determination criteria, the measured bio-signal, the result of determining whether each feature is normal, the monitoring result of the bio-signal measurement state and the biometric information measurement result with an external device Measuring device. Irradiating light onto a subject and receiving light reflected from the subject to measure a biosignal;
Extracting one or more features of waveform, period, and amplitude from the biosignal;
Monitoring a measurement state of the biosignal by applying a predetermined determination criterion according to the extracted feature; And
And performing a predefined operation according to the monitoring result. The method of claim 31, wherein
Monitoring the measurement state of the bio-signal
Determining whether the extracted feature is normal by applying at least one of a self criterion and a universal criterion included in the criterion; And
Measurement state information including at least one of a dynamic noise state, an ambient light noise state, a biosignal non-measurement state, an arrhythmia state, a contact pressure failure state, a poor contact state, and a normal measurement state Biometric information measuring method comprising the step of outputting. 33. The method of claim 32,
Performing the predefined operation is
A method of measuring biometric information based on the measurement state information, controlling stopping or re-measurement of a biosignal or measuring biometric information based on the measured biosignal; The method of claim 33, wherein
And outputting the biometric information measurement result.

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