Device and method for monitoring biological signal measurement status and measuring biological information

Abstract

Disclosed are a device and method for monitoring the measurement status of biological signals and measuring biological information. A device for monitoring the measurement status of biological signals includes: a biological signal receiver configured to receive a biological signal measured from a user; a processor configured to extract any one or any combination of waveform features, period features, and amplitude features from the received biological signal, use at least one predetermined determination reference corresponding to any one or any combination of the extracted waveform features, period features, and amplitude features to determine whether any one or any combination of the extracted waveform features, period features, and amplitude features is normal, and monitor the measurement status of the received biological signal based on whether any one or any combination of the extracted waveform features, period features, and amplitude features is determined to be normal.

Description

[0001] This application claims the benefit of Korean Patent Application No. 10-2018-0077656, filed in the Korean Intellectual Property Office on July 4, 2018, and U.S. Provisional Patent Application No. 62 / 658,137, filed in the U.S. Patent and Trademark Office on April 16, 2018, the disclosures of which are incorporated herein by reference in their entirety. Technical Field

[0002] An apparatus and a method consistent with the embodiments relate to an apparatus and a method for monitoring a biosignal measuring condition, and more particularly, to a technique for monitoring a measuring condition by using a measurement result of a biosignal. Background Art

[0003] Recently, with the aging of the population, the increasing medical expenses, and the lack of medical personnel for professional medical services, research on IT-medical fusion technology in which IT technology and medical technology are combined is being actively carried out. In particular, monitoring the health status of the human body is not limited to places such as hospitals, but has expanded to the field of mobile healthcare that can monitor the user's health status anytime and anywhere in daily life at home or in the office. Examples of biosignals indicating the health status of an individual may include: electrocardiogram (ECG) signals, photoplethysmography (PPG) signals, electromyography (EMG) signals, etc., and various biosignal sensors are being developed to measure these biosignals in daily life. However, when these biosignal sensors are used to detect biosignals, the measured biosignals may be inaccurate due to circumstances such as the wearing state of the bioinformation measuring device, the user's posture, etc. Summary of the invention

[0004] According to an embodiment, a device for monitoring a measurement status of a biological signal is provided, the device comprising: a biological signal receiver configured to: receive a biological signal measured from a user; a processor configured to: extract any one or any combination of waveform features, period features, and amplitude features from the received biological signal, use at least one predetermined determination reference corresponding to any one or any combination of the extracted waveform features, period features, and amplitude features to determine whether any one or any combination of the extracted waveform features, period features, and amplitude features is normal, and monitor the measurement status of the received biological signal based on whether any one or any combination of the extracted waveform features, period features, and amplitude features is determined to be normal.

[0005] The processor may also be configured to use a waveform self-reference personalized for the user to determine whether the extracted waveform feature is normal.

[0006] Waveform self-referencing may include any one or any combination of reference time intervals, number of comparison samples, order of differentiation, and failure conditions.

[0007] The processor can also be configured to: extract the waveform of the current time interval from the received biological signal, obtain a first waveform and a second waveform from the extracted waveform of the current time interval and the waveform of the reference time interval based on the order of differentiation, compare the obtained first waveform with the obtained second waveform, and determine that the extracted waveform feature is abnormal based on that the result of the comparison between the obtained first waveform and the obtained second waveform meets a failure condition.

[0008] The processor may further include: a buffer configured to store data of a waveform of a reference time interval of the biosignal.

[0009] The processor may be further configured to update the stored data of the waveform of the reference time interval using the data of the waveform of the current time interval based on the waveform of the current time interval satisfying a predetermined update reference.

[0010] The failure condition may include any one or any combination of the following: a minimum threshold for similarity between waveforms, the number of consecutive failures to reach the minimum threshold, a starting point for the similarity comparison between waveforms, and a total number of hops used to calculate an average similarity value.

[0011] The processor may also be configured to calculate a similarity between the obtained first waveform and the obtained second waveform, and determine that the extracted waveform feature is abnormal based on the calculated similarity being less than a minimum threshold.

[0012] The processor may also be configured to determine that the extracted waveform feature is abnormal based on the calculated similarity between the obtained first waveform and the obtained second waveform being less than a minimum threshold and the number of consecutive failures to reach the minimum threshold meeting a predetermined number of times.

[0013] The similarity between the waveforms may include any one or any combination of a correlation coefficient, an average value, and a total number of compared samples of the first waveform and the second waveform.

[0014] The processor may be further configured to determine whether the extracted periodic feature is normal using any one or both of a periodic self-reference personalized for the user and a periodic universal reference of the bio-information to be measured using the bio-signal.

[0015] The extracted period feature may include any one or both of a current period of the biosignal received during a predetermined period of time and an average period of the biosignal received.

[0016] The processor may also be configured to use an amplitude self-reference personalized for the user to determine whether the extracted amplitude feature is normal.

[0017] The processor may also be configured to output any one or both of the reliability of the measurement state of the biological signal and information on the measurement state based on whether any one or any combination of the extracted waveform features, period features, and amplitude features are determined to be normal in parallel or successively according to a predetermined priority of each of any one or any combination of the extracted waveform features, period features, and amplitude features.

[0018] The predetermined priority may be determined based on any one or any combination of the following: an examination location, a type of a bio-signal, a type of bio-information to be measured, and a calculation performance of a bio-information measuring device.

[0019] The processor may also be configured to: determine the measurement state as a motion noise state based on the extracted amplitude feature being determined to be normal, while the extracted period feature and the extracted waveform feature are determined to be abnormal; determine the measurement state as an ambient light noise state based on the extracted period feature being determined to be normal, while the extracted amplitude feature and the extracted waveform feature are determined to be abnormal; determine the measurement state as a state in which the biological signal is not measured based on the extracted waveform feature being determined to be normal, while the extracted period feature and the extracted amplitude feature are determined to be abnormal; determine the measurement state as an arrhythmia state based on the extracted period feature being determined to be abnormal, while the extracted amplitude feature and the extracted waveform feature are determined to be normal; determine the measurement state as an insufficient contact pressure state based on the extracted amplitude feature being determined to be abnormal, while the extracted period feature and the extracted waveform feature are determined to be normal; determine the measurement state as a contact failure state based on the extracted waveform feature being determined to be abnormal, while the extracted period feature and the extracted amplitude feature are determined to be normal; determine the measurement state as a normal measurement state based on the extracted period feature, the extracted amplitude feature, and the extracted waveform feature being determined to be normal.

[0020] According to an embodiment, a method for monitoring a measurement status of a biological signal is provided, the method comprising: receiving a biological signal measured from a user, extracting any one or any combination of waveform features, period features, and amplitude features from the received biological signal, using a predetermined determination reference corresponding to any one or any combination of the extracted waveform features, period features, and amplitude features to determine whether any one or any combination of the extracted waveform features, period features, and amplitude features is normal, and monitoring the measurement status of the received biological signal based on whether any one or any combination of the extracted waveform features, period features, and amplitude features is determined to be normal.

[0021] The step of determining whether any one or any combination of the extracted waveform features, period features, and amplitude features is normal may include: using a waveform self-reference personalized for the user to determine whether the extracted waveform features are normal.

[0022] The step of determining whether the extracted waveform feature is normal may include: extracting a waveform of a current time interval from a received waveform signal, obtaining a first waveform and a second waveform from the extracted waveform of the current time interval and a waveform of a reference time interval based on an order of differentiation, comparing the obtained first waveform with the obtained second waveform, and determining that the extracted waveform feature is abnormal based on that a result of the comparison between the obtained first waveform and the obtained second waveform satisfies a failure condition.

[0023] The step of comparing the obtained first waveform with the obtained second waveform may include: calculating the similarity between the obtained first waveform and the obtained second waveform, and the step of determining that the extracted waveform is abnormal may include: determining that the extracted waveform feature is abnormal based on the calculated similarity being less than a minimum threshold of the similarity between the waveforms.

[0024] The step of determining whether any one or any combination of the extracted waveform features, period features and amplitude features is normal may include: using any one or both of a period self-reference personalized for the user and a period universal reference of the biological information to be measured using the biological signal to determine whether the extracted period feature is normal.

[0025] The step of determining whether any one or any combination of the extracted waveform feature, period feature, and amplitude feature is normal may include: using an amplitude self-reference personalized for the user to determine whether the extracted amplitude feature is normal.

[0026] The step of monitoring the measurement status of the received biological signal may include: outputting any one or both of the reliability of the measurement status of the biological signal and information on the measurement status based on whether any one or any combination of the extracted waveform characteristics, period characteristics and amplitude characteristics are determined to be normal in parallel or successively according to a predetermined priority of each of any one or any combination of the extracted waveform characteristics, period characteristics and amplitude characteristics.

[0027] According to an embodiment, a device for measuring biological information is provided, the device comprising: a biological signal measurer configured to measure a biological signal by emitting a first light to an object and receiving a second light reflected from the object to which the first light is emitted; a processor configured to extract one or more features from the measured biological signal, monitor a measurement state of the measured biological signal using at least one predetermined determined reference corresponding to the extracted one or more features, and perform a predefined operation based on the monitored measurement state; and an output unit configured to output a processing result of the processor on a display.

[0028] The biosignal measurer may include: one or more light sources configured to emit first light onto the object; and one or more detectors configured to receive second light reflected from the object.

[0029] The processor may also be configured to determine whether one or more extracted features are normal using any one or both of a self-reference and a universal reference included in the at least one predetermined determination reference, and output information on the measurement status based on whether the one or more extracted features are determined to be normal.

[0030] The processor may be further configured to: control the biosignal measurer to stop and start measuring the biosignal based on the output information of the measurement state; and measure the bioinformation using the measured biosignal based on the output information of the measurement state.

[0031] The biological information may include any one or any combination of the following: heart rate, arrhythmia, blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, stress index, and degree of fatigue.

[0032] The device may also include: a storage unit configured to store any one or any combination of the following items: at least one predetermined determination reference, a measured biological signal, information related to whether each of the one or more extracted features is determined to be normal, a monitored measurement status, and measured biological information.

[0033] The apparatus may further include: a communicator configured to: send the following information to an external device, or receive the following information from an external device: at least one predetermined determination reference, a measured biological signal, information related to whether each of the extracted one or more features is determined to be normal, a monitored measurement status, and measured biological information.

[0034] According to an embodiment, a method for measuring biological information is provided, the method comprising: measuring a biological signal by emitting a first light to an object and receiving a second light reflected from the object onto which the first light is emitted, extracting one or more features from the measured biological signal, monitoring a measurement state of the measured biological signal using at least one predetermined determined reference corresponding to the extracted one or more features, and performing a predefined operation based on the monitored measurement state.

[0035] The step of monitoring the measurement status of the biological signal may include: using any one or both of the self-reference and the universal reference included in the at least one predetermined determination reference to determine whether the one or more extracted features are normal, and based on whether the one or more extracted features are determined to be normal, outputting information on the measurement status including any one or any combination of the following items: motion noise status, ambient light noise status, unmeasured biological signal status, arrhythmia status, insufficient contact pressure status, contact failure status and normal measurement status.

[0036] The performing of the predefined operation may include controlling stop and start of measuring the biosignal based on the output information of the measurement state, and measuring the bioinformation using the measured biosignal.

[0037] The method may further include outputting a result of measuring the biological information.

[0038] According to an embodiment, a device for monitoring a biological signal measurement status is provided, the device comprising: a biological signal receiver configured to: receive a biological signal measured from a user; a processor configured to: extract a waveform, a period and an amplitude from the received biological signal; determine whether the extracted waveform is normal by comparing the extracted waveform with a reference waveform; determine whether the extracted amplitude is normal by comparing the extracted amplitude with the reference amplitude; determine whether the extracted period is normal by comparing the extracted period with the reference period; based on the extracted amplitude being determined to be abnormal, control the output of any one or any combination of a contact pressure insufficient state, an ambient light noise state and a biological signal not measured state; based on one of the extracted period and the extracted waveform being determined to be abnormal, control the output of any one or any combination of a motion noise state, an arrhythmia state and a contact failure state; based on the extracted amplitude, the extracted period and the extracted waveform being determined to be normal, control the output of a normal measurement state.

[0039] The step of determining whether the extracted waveform is normal may include: determining that the extracted waveform is normal based on that the similarity between the extracted waveform and the reference waveform is greater than a threshold value; the step of determining whether the extracted amplitude is normal may include: determining that the extracted amplitude is normal based on that a first difference between the extracted amplitude and the reference amplitude is within a first range; the step of determining whether the extracted period is normal may include: determining that the extracted period is normal based on that a second difference between the extracted period and the reference period is within a second range. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a block diagram illustrating an apparatus for monitoring a biological signal measurement state according to an embodiment of the present disclosure.

[0041] Figure 2 It is shown Figure 1 A diagram of an example of a configuration of a processor of an apparatus for monitoring a biological signal measurement state.

[0042] Figure 3 It is shown Figure 1 A diagram of another example of a configuration of a processor of an apparatus for monitoring a measurement status.

[0043] Figure 4A , Figure 4B and Figure 4C : are diagrams for explaining an example of a measurement state of monitoring a biological signal.

[0044] Figure 5 is a flowchart illustrating a method of monitoring a biological signal measurement state according to an embodiment of the present disclosure.

[0045] Figure 6 is a flowchart illustrating a method of monitoring a biological signal measurement state according to another embodiment of the present disclosure.

[0046] Figure 7 is a block diagram illustrating an apparatus for measuring biological information according to an embodiment of the present disclosure.

[0047] Figure 8 is a block diagram illustrating an apparatus for measuring biological information according to another embodiment of the present disclosure.

[0048] Fig. 9 It is shown Figure 7 and Figure 8 A block diagram of an example of a configuration of a processor.

[0049] Fig.10 is a flowchart illustrating a method for measuring biological information according to an embodiment of the present disclosure.

[0050] Fig.11 is a diagram showing a wearable device to which the above-mentioned apparatus for measuring biological information is applied.

[0051] Fig.12 is a diagram showing a smart device to which the above-described apparatus for measuring biological information is applied. DETAILED DESCRIPTION

[0052] Details of the embodiments are included in the following detailed description and drawings. From the embodiments described in detail below with reference to the drawings, the advantages, features and methods of implementing the embodiments will be more clearly understood. Throughout the drawings and detailed description, unless otherwise described, the same reference numerals will be understood to represent the same elements, features and structures.

[0053] It will be understood that although the terms first, second, etc. can be used to describe various elements here, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. Unless otherwise explicitly stated, any reference to the singular may include the plural. In addition, unless explicitly described to the contrary, expressions such as "including" or "comprising" will be understood to indicate that the elements stated are included, but any other elements are not excluded. In addition, terms such as "portion" or "module" etc. should be understood as units that perform at least one function or operation and can be implemented as hardware, software, or a combination thereof.

[0054] Hereinafter, embodiments of an apparatus and method for extracting features for detecting biological information, embodiments of an apparatus for detecting biological information, and embodiments of a wearable device will be described in detail with reference to the accompanying drawings.

[0055] Figure 1 is a block diagram illustrating an apparatus for monitoring a biological signal measurement state according to an embodiment of the present disclosure.

[0056] Reference Figure 1 , the apparatus 100 for monitoring a biological signal measurement state includes a biological signal receiver 110 and a processor 120 .

[0057] The biosignal receiver 110 may receive a biosignal of the user. In this case, the biosignal may be an electrocardiogram (ECG) signal, a photoplethysmogram (PPG) signal, an electromyogram (EMG) signal, etc., but the biosignal is not limited thereto.

[0058] For example, the biosignal receiver 110 may include a biosignal measurement sensor for measuring a biosignal from a user. In another example, the biosignal receiver 110 may be connected to the biosignal measurement sensor via wired or wireless communication to receive the user's biosignal from the biosignal measurement sensor. In another example, the biosignal receiver 110 may be connected to an external device via wired or wireless communication to receive biosignal data from the 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 computer, a laptop computer, etc.), and may be a device for processing and managing biosignal data.

[0059] Once the bio-signal of the user is received, the processor 120 may monitor the measurement status of the bio-signal measured from the user by using the received bio-signal. For example, the processor 120 may monitor the measurement status of the bio-signal based on a predetermined determination reference, wherein the predetermined determination reference may include a general reference that may be applied according to the bio-signal to be measured and bio-information and a self-reference personalized for each user.

[0060] For example, a repeatedly measured biosignal has features that are similarly repeated over a predetermined period of time. Examples of features include periods, amplitudes, etc. whose values ​​do not converge or diverge; some other features of the biosignal (such as biosignal waveforms, etc.) are similarly repeated over a predetermined period of time. In this case, if the bioinformation to be measured is heart rate, there may be a universal reference for the period, for example, a heart rate ranging from 30bpm to 180bpm that can be determined to be normal. As described above, there may be a universal reference that can be applied to most people based on the type and characteristics of the biosignal, etc. However, according to an embodiment of the present disclosure, in some cases where a self-reference can be predefined based on the individual characteristics of the user and the biosignal, such a universal reference that depends on the biosignal may not exist.

[0061] In the following, reference is made to Figure 2 and Figure 3 , various embodiments of the configuration of the processor 120 will be described in further detail. However, the processor 120 is not limited to the embodiments and may be modified in various ways.

[0062] Figure 2 It is shown Figure 1 A diagram of an example of a configuration of a processor of an apparatus for monitoring a biological signal measurement state. Figure 3 It is shown Figure 1 A diagram of another example of a configuration of a processor of an apparatus for monitoring a measurement status. Figure 4A , Figure 4B and Figure 4C : are diagrams for explaining an example of a measurement state of monitoring a biological signal.

[0063] Reference Figure 2 , the processor 200 includes a feature extractor 210 , a feature determiner 220 , a measurement state determiner 230 , and a buffer 240 .

[0064] Once the biosignal is received, the feature extractor 210 may extract one or more features from the received biosignal. In this case, the features may include amplitude features, period features, waveform features, etc., but are not limited thereto. According to an embodiment, the feature extractor 210 may extract any one or any combination of amplitude features, period features, and waveform features. Once the biosignal is received, the feature extractor 210 may remove noise by filtering the received biosignal as needed. In addition, the feature extractor 210 may perform normalization to compare the extracted features with a determined reference.

[0065] The feature extractor 210 may store the currently extracted feature in the buffer 240 to use the feature as a reference for determining whether a feature extracted at a subsequent time is normal.

[0066] For example, the feature extractor 210 may extract the difference between the maximum and minimum values ​​of the biosignal or the filtered biosignal over a period of time as an amplitude feature. In addition, the feature extractor 210 may store the currently extracted feature in the buffer 240 to use the feature as a reference for determining whether the feature extracted at a subsequent time is normal.

[0067] Figure 4A The bio-signal measured from the user or the filtered bio-signal (eg, PPG signal) is shown. Figure 4A As shown in , the feature extractor 210 may extract the amplitude value at the maximum amplitude point Amax as the amplitude feature, wherein the amplitude value at the maximum amplitude point Amax is the difference between the maximum amplitude point Amax and the amplitude minimum point Amin during the time period between the time index 0 and the time index 140. Optionally, the feature extractor 210 may perform a second-order differential of the biosignal to obtain a second-order differential signal, and may obtain the time of a local minimum point where the amplitude is at the minimum during a period of time in the obtained second-order differential signal from the obtained second-order differential signal, and may extract the amplitude value corresponding to the time of the local minimum point as the amplitude feature. However, the feature is not limited thereto.

[0068] For example, the feature extractor 210 may extract a current period of the biosignal and may store the extracted current period in the buffer 240. Figure 4A As shown in , the feature extractor 210 may extract an interval between a point 0 where the amplitude value is zero (0) for the first time and a point 140 where the amplitude value is zero (0) for the second time thereafter as the current period, but is not limited thereto.

[0069] In addition, the feature extractor 210 may extract an average period of the biosignal and store the extracted average period in the buffer 240. The feature extractor 210 may obtain the total number of times that the amplitude value is zero (0) during a period of time and may calculate the average period based on the total number of times obtained. For example, the feature extractor 210 may calculate the time interval as the average period by dividing the time by the total number of times.

[0070] In addition, the feature extractor 210 may extract waveform features from the received biosignal or the filtered biosignal, and may store the extracted waveform features in the buffer 240 to use the currently extracted waveform features as a reference for determining whether the features extracted at a subsequent time are normal. According to one embodiment, the feature extractor 210 may update the stored data of the waveform of the reference time interval using the data of the waveform of the current time interval based on the waveform of the current time interval satisfying a predetermined update reference.

[0071] For example, the feature extractor 210 may continuously extract m (m is set to the number of comparison samples) values ​​in the current time interval, and the extracted values ​​may be used as waveform features. In this case, the extracted value may be an nth order differential value or an integral value, etc. However, the value is not limited thereto, and may be various values ​​that can be extracted from a biological signal. In this case, the number of comparison samples may be maintained at a constant value. In addition, the length of the time interval in which the waveform feature is extracted may be pre-set to a random value. In addition, as described above, the cycle extracted in the process of extracting the periodic feature may be set to the length of the time interval. In the case where each cycle (e.g., the previous cycle and the current cycle) has a different time length, each cycle may be normalized so that the length of the time interval may be equal to each other. In this way, the number of signal samples extracted in each cycle may be equal to each other. In addition, the m samples to be extracted may be pre-defined in the waveform self-reference.

[0072] Refer again Figure 2 Once the feature extractor 210 extracts each feature, the feature determiner 220 may determine whether each feature is normal by using a common reference and / or a self-reference defined for each feature. In this case, the common reference and / or the self-reference may be applied in series or in parallel. By referring to the buffer 240, the feature determiner 220 may obtain information associated with the common reference and / or the self-reference defined for each feature, and may determine whether each feature is normal.

[0073] Once the amplitude feature is extracted from the biosignal at the current time, the feature determiner 220 can determine whether the extracted amplitude feature is normal by using the amplitude self-reference. In this case, the amplitude self-reference can be pre-defined as: if the difference between the amplitude feature value measured at the reference time and the amplitude feature value measured at the current time falls outside a predetermined range, or if the amplitude feature value measured at the current time falls outside a predetermined percentage of the amplitude feature value measured at the reference time, the amplitude feature is determined to be abnormal. However, such a self-reference can be set differently according to the characteristics of the biosignal, the type of bio-information, the individual characteristics of the user (e.g., health status, specificity of the inspection part, etc.).

[0074] However, the reference is not limited thereto, and there may be an amplitude universal reference that can be applied according to the type of the biosignal, the type of bio-information to be extracted, the characteristics of the extracted biosignal, etc. In this case, the feature determiner 220 may determine whether the amplitude feature is normal by applying the amplitude universal reference alone or in combination with the amplitude self-reference.

[0075] Once the current cycle feature and / or average cycle feature at the current time is extracted, the feature determiner 220 may determine whether the current cycle feature and / or average cycle feature is normal by applying a cycle universal reference and / or a cycle self-reference. In this case, the cycle universal reference is a reference applied based on bio-signals and bio-information. For example, in the case of measuring heart rate by using a PPG signal, there may be a universal reference for determining whether a heart rate ranging from 30 bpm to 180 bpm is normal.

[0076] In addition, the cycle self-reference is preset by considering the individual characteristics of the user (e.g., the user's gender, health status, age, examination location, characteristics of the examination location, etc.). The cycle self-reference may be preset such that if the difference between the current cycle value at the current time and the cycle value at the reference time falls outside a predetermined range, or if the current cycle falls outside a predetermined percentage of the cycle at the reference time, the cycle characteristic is determined to be abnormal. In this case, the reference time may represent a previous cycle extracted at a previous time. For example, in the case where the previous cycle is 0.84 seconds (approximately 71 bpm), the cycle self-reference may define a range of 0.672 seconds to 1.008 seconds within a range of ±20% of 0.84 seconds as a normal range; and if the extracted current cycle falls outside the range of 0.672 seconds to 1.008 seconds, the feature determiner 220 may determine that the cycle characteristic is abnormal.

[0077] Once the waveform features in the current time are extracted, the feature determiner 220 may obtain information associated with the waveform self-reference by referring to the buffer 240 and determine whether the extracted waveform features are normal by using the obtained information associated with the waveform self-reference.

[0078] The waveform self-reference may include a reference time interval, the number of comparison samples, the order of differentiation or integration, a failure condition, etc. In this case, the reference time interval may be a previous time interval in which the waveform was extracted at a previous time. In addition, the time interval may be divided in units of cycles. Hereinafter, for convenience of explanation, the reference time interval and the current time interval will be described as a reference cycle and a current cycle, but are not limited thereto.

[0079] In addition, the number of comparison samples is the number of samples to be extracted, and the number of comparison samples can be predefined based on the sampling rate, buffer size, etc. For example, in the case where the sampling rate of the biological signal is 250Hz, the number of samples to be extracted can be set to 50 corresponding to 20% of the sampling rate. In addition, there may be one or more failure conditions, and in the case where there are two or more failure conditions, the conditions can be set to: if some or all of the predefined conditions are met, the waveform feature is determined to be abnormal. For example, the failure condition may include any one or any combination of the following items: a minimum threshold value for similarity, the number of consecutive failures to reach the minimum threshold value, a starting point for similarity comparison, a total number of heartbeat counts used to calculate an average similarity value, etc., but is not limited thereto.

[0080] For example, once the waveform features of the current cycle are extracted, the feature determiner 220 may obtain the waveform features of the reference cycle by referring to the buffer 240, and may calculate the similarity between the waveform features of the current cycle and the waveform features of the reference cycle. In this case, the two extracted waveforms are m consecutive values, so that the correlation coefficient r x,y It can be calculated as the similarity as shown in the following Equation 1. In this case, outliers can be excluded from the m waveform features.

[0081] [Equation 1]

[0082]

[0083]

[0084] Here, μ x represents the mean value of population X, μ y represents the mean value of the population Y, σ x represents the standard deviation of population X, σ y represents the standard deviation of the population Y, and m represents the number of individuals in the population. The correlation coefficient is -1≤r x,y Within the range of ≤1, as the value of the correlation coefficient is closer to 1, the two waveforms are similar to each other. However, calculation of the similarity is not limited thereto, and statistical values ​​of multiple samples of waveform features (such as an average value, a total number, etc.) may be calculated as the similarity.

[0085] In the case where the calculated similarity is less than the minimum threshold value among the waveform self-references, the feature determiner 220 may determine that the waveform feature is abnormal. Alternatively, in the case where the waveform feature of the current cycle is abnormal and the determination result obtained by continuously determining the features of the previous cycle satisfies the number of times that the minimum threshold value has been continuously failed to be reached, the feature determiner 220 may finally determine that the waveform feature is abnormal. The feature determiner 220 may calculate the similarity by using a value obtained after the starting point of the similarity comparison.

[0086] Based on the information related to the order of differentiation / integration among the waveform self-reference information, the feature determiner 220 can obtain the first waveform and the second waveform by performing differentiation / integration of the waveform of the current cycle and the waveform of the reference cycle based on the corresponding order of differentiation / integration. The order of differentiation / integration set to "0" can indicate the extracted waveform feature itself. The feature extractor 220 can calculate the similarity by comparing the obtained first waveform with the obtained second waveform, and can determine whether the waveform feature of the current cycle is normal by using the calculated similarity as described above.

[0087] Reference Figure 4B , the following example is shown: in this example, when the similarity between the current waveform extracted from the PPG signal (i.e., order N=0) and the reference waveform is less than or equal to 0.7, which is a value set as the minimum threshold, the waveform feature is determined to be abnormal and "0" is input to the buffer 240; when the similarity is greater than 0.7, the waveform feature is determined to be normal and "1" is input to the buffer 240. Figure 4B , it can be seen that at the current time T7, the result of the comparison between the similarity and the minimum threshold is determined to be normal. In the case where the number of consecutive failures to reach the minimum threshold is set to "4", the result of the comparison at time T4 is determined to be abnormal (0), and there are four consecutive determinations of abnormal results including the result at T4, so that the final determination result can indicate that the waveform feature obtained at T4 is abnormal.

[0088] Reference Figure 4C , shows the following example: In this example, after executing Figure 4B When the similarity between the current waveform obtained by the second differential signal (i.e., order N=2) obtained by the second differential of the PPG signal and the reference waveform is less than or equal to 0.6, which is the value set as the minimum threshold, the waveform feature is determined to be abnormal and “0” is input to the buffer 240; when the similarity is greater than 0.6, the waveform feature is determined to be normal and “1” is input to the buffer 240.

[0089] Refer again Figure 2By comprehensively considering the determination results of each feature of the multiple features, the monitoring state determiner 230 can monitor the final measurement state of the biological signal measured from the user, and can output one or more of the reliability and measurement state information of the biological signal measurement state as the monitoring result. In this case, the measurement state information may include any one or any combination of the following items: a motion noise state, an ambient light noise state, a state of unmeasured biological signals, a state of arrhythmia, a state of insufficient contact pressure, a contact failure condition, and a normal measurement state. By considering the determination results of each feature of the multiple features in parallel, the measurement state determiner 230 can output reliability and / or measurement state information. Optionally, by successively considering the determination results of each feature of the multiple features according to the predetermined priority of the features, the measurement state determiner 230 can output the final monitoring result.

[0090] For example, in response to determining that the amplitude characteristic is normal, while the period characteristic and the waveform characteristic are abnormal, the measurement state determiner 230 may determine the measurement state as a motion noise state. Alternatively, in response to determining that the period characteristic is normal, while the amplitude characteristic and the waveform characteristic are abnormal, the measurement state determiner 230 may determine the measurement state as an optical noise state in which a large amount of ambient optical noise exists. In addition, in response to determining that the waveform characteristic is normal, while the period characteristic and the amplitude characteristic are abnormal, the measurement state determiner 230 may determine the measurement state as a state of unmeasured biosignal in which no biosignal is measured. In addition, in response to determining that the period characteristic is abnormal, while the amplitude characteristic and the waveform characteristic are normal, the measurement state determiner 230 may determine the measurement state as a state of arrhythmia. In addition, in response to determining that the amplitude characteristic is abnormal, while the period characteristic and the waveform characteristic are normal, the measurement state determiner 230 may determine the measurement state as a state of insufficient contact pressure. In addition, in response to determining that the waveform characteristic is abnormal, while the period characteristic and the amplitude characteristic are normal, the measurement state determiner 230 may determine the measurement state as a contact failure state or a contact failure state in which vibration exists in the contact portion. Furthermore, in response to determining that the period feature, the amplitude feature, and the waveform feature are all normal, the measurement state determiner 230 may determine the measurement state as a normal measurement state. However, the states are examples and may be combined in various ways.

[0091] Reference Figure 3 The processor 300 includes: a time index calculator 311, an R index detector 312, a current period extractor 313, an average period extractor 314, an amplitude extractor 315, a waveform extractor 316, an average period determiner 321, a current period determiner 322, an amplitude determiner 323, a waveform determiner 324, a measurement state determiner 330, an R index buffer 341, a period buffer 342, an amplitude buffer 343 and a waveform buffer 344.

[0092] The time index calculator 311 may measure time in response to input of the biosignal data, for example, based on the input speed of the biosignal data determined according to the sampling rate and the buffer size, so that time may be measured based on the input speed of the biosignal data.

[0093] The R index detector 312 may detect an R peak index from an input biosignal or a filtered signal from which noise is removed. The R peak index is a value used as a reference for measuring a period of the biosignal, and may be a point at which a negative (-) value is changed to a positive (+) value, a point at which a positive (+) value is changed to a negative (-) value, an inflection point, etc. In addition, when the R peak index is detected, the R index detector 312 may input the detected R peak index to the R index buffer 341.

[0094] The current cycle extractor 313 may extract the current cycle by referring to the R peak index stored in the R index buffer 341. The current cycle extractor 313 may store the extracted current cycle value in the cycle buffer 342 to use the current cycle value as a reference cycle for a subsequent time.

[0095] The average period extractor 314 may calculate the average period by using the period information stored in the period buffer 342 and the time value measured by the time index calculator 311. For example, in the case where three periods (e.g., 10 minutes, 8 minutes, and 12 minutes) are extracted by the current period extractor 313 and stored in the period buffer 342 during a predetermined time (e.g., 30 minutes) measured by the time index calculator 311, the average period extractor 314 may calculate that the average period is 10 minutes.

[0096] The amplitude extractor 315 may extract an amplitude feature value from the input biosignal or the filtered biosignal. For example, the amplitude extractor 315 may extract, from the input biosignal or the filtered biosignal, the difference between the maximum value and the minimum value during a period of time as an amplitude value. In addition, the extracted amplitude value may be stored in the amplitude buffer 343 to be used as a self-reference for comparing the amplitude value at a subsequent time.

[0097] The waveform extractor 316 may extract waveform features from the received biosignal or the filtered biosignal. In this case, the waveform extractor 316 may extract multiple samples from the biosignal itself or a differential signal obtained by differentiating the biosignal. In this case, the waveform extractor 316 may extract multiple samples as waveform features by using information on whether the nth order differentiation is performed and information related to the number of comparison samples in the determination reference. The waveform features extracted at the current time may be input to the waveform buffer 344 to be used as a self-reference for determining whether the waveform features at a subsequent time are normal.

[0098] The average period determiner 321 may determine whether the average period extracted by the average period extractor 314 is normal by using a period common reference among predetermined determination references. The current period determiner 322 may determine whether the current period value extracted by the current period extractor 313 is normal based on the reference period value stored in the period buffer 342 and a period self-reference among predetermined determination references.

[0099] 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 an amplitude self-reference among predetermined determination references.

[0100] The waveform determiner 324 may determine whether the current waveform extracted by the waveform extractor 316 is normal by applying the reference waveform stored in the waveform buffer 344 and the waveform self-reference among the predetermined determination references. In this case, the waveform determiner 324 may calculate the similarity between the reference waveform and the current waveform, and may determine whether the current waveform is normal based on the calculated similarity.

[0101] In response to the input of the determination results of the average period, the current period, the amplitude feature, and the waveform feature, the measurement state determiner 330 can monitor the final measurement state of the biological signal measured from the user by considering the determination results of each feature successively or in parallel. Information about whether to consider the results successively or in parallel can be predetermined in a predetermined determination reference. In the case of considering successively, the priority of the features can be predefined. According to an embodiment, the priority can be determined based on any one or any combination of the following items: the inspection location, the type of the biological signal, the type of biological information to be measured, and the computing performance of the biological information measuring device.

[0102] The measurement state determiner 330 may output one or more of the reliability of the biosignal monitoring state and the measurement state information as the monitoring result. In this case, the measurement state information may include any one or any combination of the following items: motion noise state, ambient light noise state, state of no biosignal measurement, state of arrhythmia, state of insufficient contact pressure, state of contact failure, and normal measurement state.

[0103] For example, in response to determining that the amplitude feature is normal, while the period feature and the waveform feature are abnormal, the measurement state determiner 330 may determine the measurement state as a motion noise state. Alternatively, in response to determining that the period feature is normal, while the amplitude feature and the waveform feature are abnormal, the measurement state determiner 330 may determine the measurement state as an ambient light noise state. In addition, in response to determining that the waveform feature is normal, while the period feature and the amplitude feature are abnormal, the measurement state determiner 330 may determine the measurement state as a state in which the biosignal is not measured. In addition, in response to determining that the period feature is abnormal, while the amplitude feature and the waveform feature are normal, the measurement state determiner 330 may determine the measurement state as a state of arrhythmia. In addition, in response to determining that the amplitude feature is abnormal, while the period feature and the waveform feature are normal, the measurement state determiner 330 may determine the measurement state as a state of insufficient contact pressure. In addition, in response to determining that the waveform feature is abnormal, while the period feature and the amplitude feature are normal, the measurement state determiner 330 may determine the measurement state as a contact failure state. In addition, in response to determining that the period feature, the amplitude feature, and the waveform feature are all normal, the measurement state determiner 330 may determine the measurement state as a normal measurement state.

[0104] Figure 5 is a flowchart illustrating a method of monitoring a biological signal measurement state according to an embodiment of the present disclosure.

[0105] The method for monitoring the measurement status of the biological signal can be Figure 1 An example of a method performed by the apparatus 100 for monitoring a biological signal measurement state will be referred to as Figure 1 The invention is described in detail with reference to the following drawings, so that a description thereof will be briefly given below.

[0106] Reference Figure 5 In 510, the apparatus 100 for monitoring the biological signal measurement state may receive a biological signal from a user. In this case, the biological signal may be a PPG signal measured from an inspection part of the user. However, the type of the biological signal is not limited thereto. The biological signal measured from the user may be received by a biological signal measurement sensor. Alternatively, the biological signal may be received from an external device that receives the biological signal from the biological signal measurement sensor. In response to the input of the biological signal, the apparatus 100 for monitoring the biological signal measurement state may remove noise by filtering the biological signal as needed.

[0107] Then, in 520, the device 100 for monitoring the measurement state of the biological signal may extract one or more of an amplitude feature, a period feature, and a waveform feature from the input biological signal. As described above, the amplitude feature may be the difference between a maximum value and a minimum value during a period of time. The period feature may include a current period value and an average period value. In addition, the device 100 for monitoring the measurement state of the biological signal may extract a value corresponding to a predetermined number of comparison samples during a predetermined time interval from the biological signal as a waveform feature. In this case, the device 100 for monitoring the measurement state of the biological signal may extract multiple samples from the biological signal or the filtered signal itself, or the differential signal.

[0108] Subsequently, in 530, the apparatus 100 for monitoring the biological signal measurement state may determine whether each feature extracted in 520 is normal by applying a predetermined determination reference. In this case, the predetermined determination reference may be set for each feature and may include a general reference that may be applied according to the biological signal and biological information to be measured and a self-reference personalized for each user. The apparatus 100 for monitoring the biological signal measurement state may determine whether each feature is normal by applying the general reference or the self-reference successively or in parallel according to each feature.

[0109] Then, in 540, the apparatus 100 for monitoring the biosignal measurement state may determine the biosignal measurement state based on the determination result in 530. When determining whether the amplitude characteristic, the period characteristic, and the waveform characteristic are normal in 530, the apparatus 100 for monitoring the biosignal measurement state may determine the biosignal measurement state by applying the determination results in parallel or successively according to a predefined priority.

[0110] Then, in 550, the apparatus 100 for monitoring the measurement state of a biological signal may output the determination result of the measurement state. For example, the apparatus 100 for monitoring the measurement state of a biological signal may output the determination result visually or in a non-visual manner through voice, vibration, touch, etc. using an external display module, a tactile module, a speaker module, etc. directly installed in the apparatus 100 or connected to the apparatus 100. Alternatively, the apparatus 100 for monitoring the measurement state of a biological signal may send the determination result of the measurement state to an external device that requests the measurement state of the biological signal.

[0111] Figure 6 is a flowchart illustrating a method of monitoring a biological signal measurement state according to another embodiment of the present disclosure. Figure 6 The method for monitoring the measurement status of a biological signal may be composed of Figure 1 An example of a method performed by the apparatus 100 for monitoring a biological signal measurement state will be referred to as Figure 1The invention is described in detail with reference to the following drawings, so that a description thereof will be briefly given below.

[0112] The apparatus 100 for monitoring a biosignal measurement state may receive a biosignal from a user in 610. In this case, the biosignal may be a signal measured from an examination part of the user, and may be received from a biosignal measurement sensor or an external device.

[0113] Then, in 620 , the apparatus 100 for monitoring a biosignal measurement state may extract one or more of an amplitude feature, a period feature, and a waveform feature from the input biosignal.

[0114] Subsequently, when the amplitude feature is extracted in 620, in 631, the device 100 for monitoring the measurement state of the biological signal can determine whether the amplitude feature is normal by applying the amplitude self-reference. In this case, the amplitude self-reference is predefined by considering the individual characteristics of the user, and the amplitude self-reference may include a reference time and a reference error margin (margin of error) information for determining abnormal features. In this case, the reference error margin may be information including the difference between the amplitude feature value measured at the reference time and the amplitude feature value measured at the current time, or the reference error margin may be range information for determining that the amplitude feature value is abnormal when the amplitude feature value at the current time falls outside a predetermined percentage of the amplitude feature value at the reference time.

[0115] In addition, when the period feature is extracted in 620, in 632, the device 100 for monitoring the measurement state of the biological signal may determine whether the period feature is normal by applying any one or both of the period self-reference and the period universal reference. For example, the period feature may include an average period and a current period, the period universal reference may be applied to the average period, and the period self-reference may be applied to the current period. For example, as described above, in the case of measuring the heart rate, when the average period is within the range of 30bpm to 180bpm, the device 100 for monitoring the measurement state of the biological signal may determine that the period feature is normal. In addition, as described above, in the case where the current period value falls outside the range of 20% of the previous period value, the device 100 may determine that the period feature is abnormal.

[0116] In addition, when the waveform feature is extracted in 620, in 633, the device 100 for monitoring the measurement state of the biological signal may determine whether the extracted waveform feature is normal by applying waveform self-reference. The waveform self-reference may include any one or any combination of the following items: a reference time interval, the number of comparison samples, the order of differentiation / integration, a failure condition, etc. In this case, the failure condition may be defined as: when the similarity between the two waveforms is less than a minimum threshold, the waveform feature is determined to be abnormal. In this case, the device 100 for monitoring the measurement state of the biological signal may calculate the similarity between the waveform of the reference time interval and the waveform of the current time interval, or the similarity between two differential waveforms obtained by differentiating the two waveforms, and may determine whether the waveform feature is normal by comparing the calculated similarity with the minimum threshold.

[0117] Operations 631 to 633 are not necessarily required to be performed in order, but may be performed simultaneously or sequentially.

[0118] Then, in 640, the device 100 may confirm whether the determination result of the amplitude characteristic is normal or abnormal. When confirming that the determination result is abnormal, in 673, the device 100 for monitoring the biological signal measurement state may output "measurement state 3" as the final determination result of the biological signal measurement state. In this case, "measurement state 3" may indicate a state of insufficient contact pressure, a state of ambient light noise, or a state in which the biological signal is not measured, but is not limited thereto. For example, Figure 6 Only an example is shown in which processing directly enters operation 673 in response to determining that the amplitude characteristic is abnormal in 640; however, even when the amplitude characteristic is abnormal, the device 100 for monitoring the measurement state of a biological signal may further consider the result of determining whether the period characteristic and the waveform characteristic are normal; and based on the result, the definition of "measurement state 3" may be modified in various ways.

[0119] Subsequently, when it is confirmed in 640 that the determination result is normal, in 650, the device 100 for monitoring the measurement state of the biological signal may consider the periodic characteristics. For example, when the operation 651 of confirming whether the average cycle is normal and the operation 652 of confirming whether the current cycle is normal are performed in parallel, when both the average cycle and the current cycle are normal, in 660, the device 100 for monitoring the measurement state of the biological signal may confirm whether the waveform characteristics are normal; when any one of the average cycle and the current cycle is abnormal, in 671, the device 100 for monitoring the measurement state of the biological signal may output "measurement state 1". In this case, "measurement state 1" may be a motion noise state, an arrhythmia state, or a contact failure state, but is not limited thereto. For example, with Figure 6Unlike the embodiments, even when the periodic characteristics are abnormal, the device 100 for monitoring the measurement state of a biological signal may further consider determining whether the waveform characteristics are normal; and based on this determination, the definition of "measurement state 1" may be modified in various ways.

[0120] Then, when it is determined that the periodic feature is normal in 650, the apparatus 100 for monitoring the measurement state of a biological signal may confirm the result of the determination of the waveform feature in 660; when it is confirmed that the waveform feature is normal, the apparatus 100 for monitoring the measurement state of a biological signal may output "measurement state 2" in 672, and when it is confirmed that the waveform feature is abnormal, the apparatus 100 for monitoring the measurement state of a biological signal may output "measurement state 1" in 671. In this case, "measurement state 2" may be a normal measurement state.

[0121] Figure 7 is a block diagram illustrating an apparatus for measuring biological information according to an embodiment of the present disclosure. Figure 8 is a block diagram illustrating an apparatus for measuring biological information according to another embodiment of the present disclosure.

[0122] Figure 7 and Figure 8 The device 700 and the device 800 for measuring biological information may be biological information measuring devices that measure biological signals (such as PPG signals, etc.) from a user, and may measure biological information by using the measured biological signals, wherein the biological information includes one or more of the following items: heart rate, arrhythmia, blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, stress index, and degree of fatigue. The device 700 and the device 800 for measuring biological information according to an embodiment of the present disclosure may include various technical aspects of monitoring the above-mentioned biological signal measurement status.

[0123] Reference Figure 7 , the apparatus 700 for measuring biological information includes a biological signal measurer 710 , a processor 720 , and an output unit 730 .

[0124] The biosignal measurer 710 may measure various biosignals from the user's object OBJ. For example, the biosignal may be one or more of an electrocardiogram (ECG) signal, a photoplethysmogram (PPG) signal, an electromyogram (EMG) signal, etc., but is not limited thereto. Hereinafter, the following description will be made using a PPG signal as an example, in which the object OBJ may be the top of a wrist or finger through which a vein or capillary passes. However, the object OBJ is not limited thereto and may be the bottom of a wrist through which a radial artery passes.

[0125] The biosignal measurer 710 may include one or more light sources 711 that emit light onto an object and one or more detectors 712 that detect light emitted onto the object by the one or more light sources 711 and scattered or reflected from the object.

[0126] One or more light sources 710 may include light emitting diodes (LEDs), laser diodes (LDs), phosphors, etc., but are not limited thereto. In the case of providing multiple light sources, each of the multiple light sources may be configured to emit light of different wavelengths. In addition, each of the multiple light sources may be arranged at a different distance from the detector 712. One or more detectors 712 may include photodiodes, phototransistors (PTr), image sensors (e.g., CMOS image sensors, etc.).

[0127] The processor 720 may be electrically connected to the biosignal measurer 710. The processor 720 may receive the biosignal measured from the object OBJ. In addition, the processor 720 may determine the measurement state of the biosignal measured from the object OBJ by the biosignal measurer 710 based on the received biosignal. In addition, the processor 720 may perform various predefined operations based on the result of the determination of the biosignal measurement state. Fig. 9 Various embodiments of processor 720 are described in further detail.

[0128] The output unit 730 can output the processing results of the processor 720 by using various visual / non-visual methods, for example, the results of the determination of the biological signal measurement state, the measurement results of biological information, etc. For example, the output unit 730 can output information visually on the display. For example, in the case where the measured blood pressure value falls outside the normal blood pressure range of the user, the output unit 730 can display the blood pressure value in red, or can use a tactile module to provide a warning by vibration. Optionally, the output unit 730 can inform the user of the abnormality by voice, and can provide guidance as the action to be taken by the user. In addition, the output unit 730 can use a speaker module, a tactile module, etc. to output information in a non-visual manner (such as voice, touch, vibration, etc.).

[0129] Reference Figure 8In addition to the biological signal measurer 710 , the processor 720 , and the output unit 730 , the apparatus 800 for measuring biological information further includes a storage unit 810 and a communicator 820 .

[0130] The storage unit 810 may store various types of reference information and processing results of the bio-signal measurer 710 or the processor 720. In this case, the various types of reference information may include: user information including the user's age, health status, etc., a linear function equation or a bio-information measurement model for measuring bio-information, a determination reference of each feature (e.g., amplitude self-reference, period universal reference, period self-reference, waveform self-reference), etc.

[0131] In this case, the storage unit 810 may include at least one storage medium of the following items: flash memory, hard disk memory, multimedia card micro memory, card-type memory (for example, SD memory, 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 memory, magnetic disk and optical disk, etc., but the storage medium is not limited to this.

[0132] The communicator 810 may communicate with the external device 850 under the control of the processor 710 to cooperate with the external device 850 in various operations associated with the measurement of bio-information. In this case, examples of the external device 850 may include a smartphone, a tablet PC, a desktop computer, a laptop computer, a device of a medical institution including a cuff-type blood pressure measurement device, etc., but the external device 850 is not limited thereto.

[0133] For example, the communicator 820 may send the measurement results of the bio-signal, the processing results of the processor 720, etc. to the external device 850, so that the external device 850 can manage the user's bio-information history, monitor the user's health status, output the monitoring results of the bio-information history and the health status, etc. In another example, the communicator 820 may receive a linear function equation for measuring bio-information, information about a bio-information measurement model, etc. from the external device 850. The received information may be stored in the storage unit 810.

[0134] In this case, the communicator 820 may communicate with the external device 850 by using Bluetooth communication, Bluetooth low energy (BLE) communication, near field communication (NFC), WLAN communication, Zigbee communication, infrared data association (IrDA) communication, Wi-Fi direct (WFD) communication, ultra-wideband (UWB) communication, Ant+ communication, WIFI communication, radio frequency identification (RFID) communication, 3G communication, 4G communication, 5G communication, etc. However, this is merely exemplary and is not intended to be limiting.

[0135] Fig. 9 It is shown Figure 7 and Figure 8 A block diagram of an example of a configuration of a processor. Fig. 9 The processor 720 includes a biological signal receiver 721, a measurement status monitoring unit 722, a measurement controller 723, and a biological information measurer 724.

[0136] The biosignal receiver 721 may receive a biosignal from the biosignal measurer 710. The biosignal receiver 721 may remove noise from the biosignal by filtering the received biosignal as needed.

[0137] Once the biosignal is received, the measurement state monitoring unit 722 may monitor the measurement state of the biosignal measured from the user's object based on the received biosignal. For example, the measurement state monitoring unit 722 may extract amplitude features, period features, waveform features, etc. from the biosignal, and may monitor the measurement state of the biosignal based on the extracted features. As described above, when each feature is extracted, the measurement state monitoring unit 722 may determine whether each feature is normal by applying one or more of a universal reference and a self-reference predetermined for each feature, and may finally determine the measurement state of the biosignal by comprehensively considering the determination results of each feature, and may output the determination result. In this case, the output determination result of the biosignal measurement state may include the reliability of the biosignal measurement state and / or the measurement state information of the biosignal. The measurement state monitoring unit 722 may be an example of the above-mentioned device 100 for monitoring the measurement state of the biosignal, which is described in detail above, so that its description will be omitted.

[0138] In response to the measurement state monitoring section 722 determining that the reliability is lower than or equal to a predetermined value or the monitoring result of the measurement state is not a normal measurement state, the measurement controller 723 may control the biosignal measurer 710 to stop measuring or remeasure the biosignal.

[0139] In response to the measurement state monitoring unit 722 determining that the reliability is higher than a predetermined value, or the monitoring result of the measurement state is a normal measurement state, the bio-information measurer 724 may measure bio-information by using the measured bio-signal. For example, the bio-information measurer 724 may measure blood pressure by applying the measured PPG signal to a predefined measurement model or linear function equation.

[0140] Fig.10 is a flowchart illustrating a method for measuring biological information according to an embodiment of the present disclosure.

[0141] Fig.10 The method for measuring biological information can be composed of Figure 7 and Figure 8 An example of a biological information measuring method performed by the apparatus 700 and the apparatus 800 for measuring biological information.

[0142] Reference Fig.10 In 1011, the apparatus 700 and the apparatus 800 for measuring biological information may receive a request for measuring biological information. The request for measuring biological information may be input by a user, or may be received from an external device connected through communication. However, the request for measuring biological information is not limited thereto, and it may be automatically determined at a predetermined interval of receiving a request for measuring biological information.

[0143] Then, in 1012 , the apparatus 700 and the apparatus 800 for measuring bio-information may control a light source and a detector of a bio-signal measurer to measure a bio-signal from an object of a user.

[0144] Subsequently, when the biosignal is measured in 1012, the apparatus 700 and the apparatus 800 for measuring bioinformation may extract one or more features, such as an amplitude feature, a period feature, and a waveform feature, from the measured biosignal in 1013. In this case, the type of feature to be extracted may be defined according to the biosignal, the type of bioinformation to be measured, and the like.

[0145] Then, in 1014, the apparatus 700 and the apparatus 800 for measuring bio-information may determine whether the extracted features are normal by applying a predetermined determination reference according to each feature. In this case, the determination reference may be defined in various ways according to the extracted features, bio-signals, types of bio-information, individual characteristics of the user, etc. For example, the determination reference may be defined for each feature (such as amplitude self-reference, period universal reference, period self-reference, and waveform self-reference). Features may be determined successively according to a predefined order, but the determination is not limited thereto, and features may be determined in parallel.

[0146] Then, in 1015, the apparatus 700 and the apparatus 800 for measuring biological information may monitor the measurement state of the biological signal measured in 1012 by comprehensively considering the result of determining whether each feature is normal. For example, the apparatus 700 and the apparatus 800 for measuring biological information may monitor the measurement state by considering the result of determining whether the amplitude, the current cycle, the average cycle, and the waveform are normal in parallel or by considering the determined results successively according to a predefined priority. The determination reference may be defined in various ways according to the biological signal, the type of biological information, the health status of the user, the individual characteristics of the user, etc.

[0147] Subsequently, in 1016, the apparatus 700 and the apparatus 800 for measuring biological information may perform a predefined operation according to the monitoring result in 1015. For example, if the monitoring result in 1015 indicates that the measurement state of the biological signal is normal, the apparatus 700 and the apparatus 800 for measuring biological information may measure the biological information based on the biological signal measured in 1012; or otherwise, the apparatus 700 and the apparatus 800 for measuring biological information may stop measuring the biological signal or may return to 1012 to re-measure the biological signal.

[0148] Then, in 1017 , the apparatus 700 and the apparatus 800 for measuring biological information may output monitoring results, measurement results of biological information, etc., and may provide the results to a user.

[0149] Fig.11 is a diagram showing a wearable device to which the above-mentioned device for measuring bio-information is applied. Various embodiments of the above-mentioned device 700 and device 800 for measuring bio-information may be embedded in the described smart watch or smart ring type wearable device worn on the wrist. However, this is an example for convenience of explanation, and the type of wearable device is not specifically limited thereto.

[0150] Reference Fig.11 , the wearable device 1100 includes a main body 1110 and a strap 1130.

[0151] The band 1130 may be flexible and may be connected to both ends of the body 1110 to be bent around the user's wrist or may be bent in a manner that allows the band 1130 to be separated from the user's wrist. Alternatively, the band 1130 may be formed as a non-detachable band. In this case, air may be injected into the band 1130 or an air bag may be included in the band 1130 so that the band 1130 may have elasticity according to changes in pressure applied to the wrist, and changes in pressure of the wrist may be sent to the body 1110.

[0152] A battery that supplies power to the wearable device 1100 may be embedded in the body 1110 or the band 1130 .

[0153] In addition, the wearable device 1100 includes: a biosignal meter 1120 that measures a pulse wave signal and a contact pressure signal from an object, and a processor that monitors the measurement state of the biosignal by using the biosignal measured by the biosignal meter 1120 and measures the user's bio-information based on the monitoring result.

[0154] The biosignal measurer 1120 may include a PPG sensor installed to be exposed to the bottom of the body 1110 (i.e., a portion to be in contact with an object (e.g., a user's wrist)) to measure a biosignal from the object. In addition, the biosignal measurer 1120 may further include a contact pressure sensor installed inside the body 1110 to measure a contact pressure signal between the PPG sensor and the object.

[0155] The PPG sensor may include one or more light sources that emit light onto an object and one or more detectors that detect light scattered or reflected from the object; and the PPG sensor may measure a plurality of PPG signals from the object at different wavelengths.

[0156] In response to a request to measure the user's bio-information, the processor may generate a control signal to control the bio-signal measurer 1120 , and may measure the bio-information such as blood pressure by using the PPG signal and / or the contact pressure signal measured by the bio-signal measurer 1120 .

[0157] Once the biosignal measurer 1120 measures the biosignal from the user, the processor can monitor the measurement state of the biosignal by using the measured biosignal. In this case, the processor can extract amplitude features, period features, and waveform features from the measured biosignal, and can monitor the measurement state of the biosignal using various predetermined determination references, which are described in detail above, and thus the description thereof will be omitted.

[0158] The display may be installed on the front side of the body 1110 and may visually output a monitoring result of a biosignal measurement state and / or a measurement result of bioinformation.

[0159] Based on the monitoring result of the biosignal measurement state displayed on the display, the user may adjust the pressure, contact state, etc. between the biosignal measurer 1120 and the object, and may control the biosignal measurer 1120 to re-measure the biosignal.

[0160] The wearable device 1100 may further include a manipulator 1140 that receives a user's control command and sends the received control command to the processor. The manipulator 1140 may be installed on the side of the body 1110 and may include a function for inputting a command for turning on / off the wearable device 1100.

[0161] In addition, the wearable device 1100 may include: a communicator for sending and receiving various data to and from an external device, and various other modules for performing additional functions provided by the wearable device 1100.

[0162] Fig.12 700 and 800 for measuring biological information may be applied to a smart device such as a smart phone, a tablet PC, etc.

[0163] Reference Fig.12 , the smart device 1200 may be mounted on the back of the main body 1210 so that the biosignal measurer 1230 may be exposed to the outside. In this case, the biosignal measurer 1230 may include one or more light sources 1231 and one or more detectors 1232. Each light source 1231 may include a light emitting diode (LED) or the like, and at least some of the light sources 1231 are configured to emit light of different wavelengths. The detector 1232 may include a photodiode, a phototransistor, or the like.

[0164] In addition, a display may be installed on the front side of the body 1210. The display may visually display a monitoring result of a biosignal measurement state, a measurement result of bioinformation, and the like.

[0165] In addition, the image sensor 1220 may be installed in the body 1210. When an object (e.g., a finger) of a user approaches the biosignal measurer 1230 to measure a biosignal, the image sensor 1220 may capture an image of the finger and transmit the captured image to the processor. In this case, based on the image of the finger, the processor may recognize the relative position of the finger relative to the actual position of the biosignal measurer 1230, and may provide the user with the relative position of the finger through a display, thereby providing guidance for more accurately measuring the biosignal.

[0166] Various other modules for performing many functions of the above-described apparatus for measuring biological information may be installed in the smart device 1220 , and a detailed description thereof will be omitted.

[0167] The embodiments may be implemented as computer-readable codes written on a computer-readable recording medium. The computer-readable recording medium may be any type of recording device that stores data in a computer-readable manner.

[0168] Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic disks, floppy disks, optical data storage, and carrier waves (e.g., data transmission via the Internet). Computer-readable recording media may be distributed over a plurality of networked computer systems so that computer-readable codes are written therein and executed therefrom in a decentralized manner. Those of ordinary skill in the art may easily derive functional programs, codes, and code segments for implementing the embodiments.

[0169] Embodiments have been described herein. However, it will be apparent to those skilled in the art that various changes and modifications may be made without changing the technical concepts and features of the present disclosure. Therefore, it is clear that the above embodiments are exemplary in all aspects and are not intended to limit the present disclosure.

Claims

1. A device for monitoring a biological signal measurement state, the device comprising: a bio-signal receiver configured to: receive a bio-signal measured from a user; The processor is configured as: extracting features from the received biosignal; determining whether the extracted feature is normal using at least one predetermined determination reference corresponding to the extracted feature, wherein the at least one predetermined determination reference includes any one or both of a universal reference applied according to a bio-signal and bio-information to be measured and a self-reference personalized for each user; monitoring the measurement status of the received biosignal based on whether the extracted feature is determined to be normal, wherein the extracted features include extracted period features, or the extracted features include at least one of extracted waveform features and extracted amplitude features and extracted period features, Wherein, the extracted periodic features include: any one or both of the current period of the biological signal received during a predetermined period of time and the average period of the received biological signal, and the processor is also configured to: determine whether the average period is normal by using a period universal reference of the biological information to be measured using the biological signal among the predetermined determination references, and / or determine whether the current period is normal by using a period self-reference personalized for the user among the predetermined determination references.

2. The device according to claim 1, wherein The processor is further configured to use a waveform self-reference personalized for the user to determine whether the extracted waveform feature is normal.

3. The device according to claim 2, wherein: Waveform self-referencing includes any one or any combination of reference time interval, number of comparison samples, order of differentiation, and failure conditions.

4. The device according to claim 3, wherein: The processor is also configured to: extracting a waveform of a current time interval from the received biological signal; obtaining a first waveform and a second waveform from the extracted waveform of the current time interval and the waveform of the reference time interval based on the order of differentiation; comparing the obtained first waveform with the obtained second waveform; Based on the result of comparing the obtained first waveform with the obtained second waveform satisfying a failure condition, it is determined that the extracted waveform feature is abnormal.

5. The device according to claim 4, wherein: The processor further includes a buffer configured to store data of a waveform of a reference time interval of the biosignal.

6. The device according to claim 5, wherein: The processor is further configured to update the stored data of the waveform of the reference time interval using the data of the waveform of the current time interval based on the waveform of the current time interval satisfying a predetermined update reference.

7. The device according to claim 4, wherein: The failure conditions include any one or any combination of the following: a minimum threshold value for similarity between waveforms, the number of consecutive failures to reach the minimum threshold value, a starting point for the similarity comparison between waveforms, and a total number of heartbeats used to calculate an average similarity value.

8. The device according to claim 7, wherein: The processor is also configured to: Calculating the similarity between the obtained first waveform and the obtained second waveform; Based on the calculated similarity being less than a minimum threshold, it is determined that the extracted waveform feature is abnormal.

9. The device according to claim 8, wherein: The processor is further configured to determine that the extracted waveform feature is abnormal based on the calculated similarity between the obtained first waveform and the obtained second waveform being less than a minimum threshold and the number of consecutive failures to reach the minimum threshold meeting a predetermined number of times.

10. The device according to claim 8, wherein: The similarity between the waveforms includes any one or any combination of a correlation coefficient, an average value, and a total number of compared samples of the first waveform and the second waveform.

11. The device according to claim 1, wherein: The processor is further configured to use an amplitude self-reference personalized for the user to determine whether the extracted amplitude feature is normal.

12. The device according to claim 1, wherein: The processor is further configured to output any one or both of reliability of the measurement state of the biosignal and information of the measurement state based on whether the extracted features are determined to be normal in parallel or successively according to a predetermined priority of each of the extracted features.

13. The device according to claim 12, wherein: The predetermined priority is determined based on any one or any combination of the following items: an examination location, a type of a biological signal, a type of biological information to be measured, and a calculation performance of a biological information measuring device.

14. The apparatus according to claim 12, wherein: The processor is also configured to: Based on the extracted amplitude feature being determined as normal, while the extracted period feature and the extracted waveform feature being determined as abnormal, the measurement state is determined as a motion noise state; Based on the extracted period feature being determined as normal, while the extracted amplitude feature and the extracted waveform feature being determined as abnormal, the measurement state is determined as an ambient light noise state; Based on the extracted waveform feature being determined as normal, while the extracted period feature and the extracted amplitude feature being determined as abnormal, the measurement state is determined as a state where the biological signal is not measured; Based on the extracted period feature being determined as abnormal, while the extracted amplitude feature and the extracted waveform feature being determined as normal, the measurement state is determined as an arrhythmia state; Based on the extracted amplitude feature being determined to be abnormal, while the extracted period feature and the extracted waveform feature being determined to be normal, the measurement state is determined to be a state of insufficient contact pressure; Based on the extracted waveform feature being determined as abnormal, while the extracted period feature and the extracted amplitude feature being determined as normal, the measurement state is determined as a contact failure state; Based on the extracted period feature, the extracted amplitude feature, and the extracted waveform feature being determined to be normal, the measurement state is determined to be a normal measurement state.

15. A method for monitoring a biological signal measurement state, the method comprising: receiving a biological signal measured from a user; extracting features from the received biosignal; determining whether the extracted feature is normal using at least one predetermined determination reference corresponding to the extracted feature, wherein the at least one predetermined determination reference includes any one or both of a universal reference applied according to a bio-signal and bio-information to be measured and a self-reference personalized for each user; monitoring the measurement status of the received biosignal based on whether the extracted feature is determined to be normal, wherein the extracted features include extracted period features, or the extracted features include at least one of extracted waveform features and extracted amplitude features and extracted period features, Wherein, the extracted periodic features include: any one or both of the current period of the biological signal received during a predetermined period of time and the average period of the received biological signal, and the step of determining whether the extracted features are normal includes: determining whether the average period is normal by using a universal reference of the period of biological information to be measured using the biological signal among the predetermined determination references, and / or determining whether the current period is normal by using a period self-reference personalized for the user among the predetermined determination references.

16. The method according to claim 15, wherein: The step of determining whether the extracted features are normal includes: using a waveform self-reference personalized for the user to determine whether the extracted waveform features are normal.

17. The method according to claim 16, wherein: The steps of determining whether the extracted waveform features are normal include: extracting a waveform of a current time interval from the received biological signal; obtaining a first waveform and a second waveform from the extracted waveform of the current time interval and the waveform of the reference time interval based on the order of differentiation; comparing the obtained first waveform with the obtained second waveform; Based on the result of comparing the obtained first waveform with the obtained second waveform satisfying a failure condition, it is determined that the extracted waveform feature is abnormal.

18. The method according to claim 17, wherein: The step of comparing the obtained first waveform with the obtained second waveform includes: calculating the similarity between the obtained first waveform and the obtained second waveform; The step of determining that the extracted waveform feature is abnormal includes: determining that the extracted waveform feature is abnormal based on the calculated similarity being less than a minimum threshold of similarities between waveforms.

19. The method according to claim 15, wherein: The step of determining whether the extracted feature is normal includes: using an amplitude self-reference personalized for the user to determine whether the extracted amplitude feature is normal.

20. The method according to claim 15, wherein: The step of monitoring the measurement state of the received biological signal includes outputting any one or both of the reliability of the measurement state of the biological signal and information on the measurement state based on whether the extracted features are determined to be normal in parallel or successively according to a predetermined priority of each of the extracted features.

21. A device for measuring biological information, the device comprising: a biosignal measurer configured to measure a biosignal by emitting a first light to a subject and receiving a second light reflected from the subject to which the first light was emitted; The processor is configured as: extracting one or more features from the measured biological signal; monitoring a measurement state of the measured biosignal using at least one predetermined determination reference corresponding to the extracted one or more features, wherein the at least one predetermined determination reference includes any one or both of a universal reference applied according to the biosignal to be measured and bioinformation and a self-reference personalized for each user; Execute predefined actions based on monitored measurement status; The output unit is configured to: output the processing result of the processor on the display, Wherein, the extracted one or more features include: any one or both of a current cycle of a biological signal measured during a predetermined period of time and an average cycle of the measured biological signal, and the processor is further configured to: determine whether the average cycle is normal by using a cycle common reference of biological information to be measured using the biological signal among predetermined determination references, and / or determine whether the current cycle is normal by using a cycle self-reference personalized for the user among predetermined determination references.

22. The apparatus according to claim 21, wherein Biosignal measuring instruments include: One or more light sources configured to: emit a first light onto the object; One or more detectors are configured to receive the second light reflected from the object.

23. The apparatus of claim 21, wherein: The processor is also configured to: determining whether the extracted one or more features are normal using any one or both of a self-reference and a universal reference included in the at least one predetermined determination reference; Information on the measurement status is output based on whether the extracted one or more features are determined to be normal.

24. The apparatus of claim 23, wherein: The processor is also configured to: Based on the output information of the measurement status, the biological signal measuring device is controlled to stop and re-measure the biological signal; Based on the output information of the measurement state, the biological information is measured using the measured biological signal.

25. The apparatus of claim 24, wherein: The biological information includes any one or any combination of the following items: heart rate, arrhythmia, blood pressure, vascular age, arterial stiffness, aortic pressure waveform, vascular compliance, stress index and degree of fatigue.

26. The apparatus of claim 24, further comprising: A storage unit configured to store any one or any combination of the following items: at least one predetermined determination reference, a measured biological signal, information related to whether each of the one or more extracted features is determined to be normal, a monitored measurement status, and measured biological information.

27. The apparatus of claim 24, further comprising: A communicator configured to send the following information to an external device, or receive the following information from an external device: at least one predetermined determination reference, a measured biological signal, information related to whether each of the one or more extracted features is determined to be normal, a monitored measurement status, and measured biological information.

28. A method for measuring biological information, the method comprising: measuring a biosignal by emitting a first light to an object and receiving a second light reflected from the object to which the first light was emitted; extracting one or more features from the measured biological signal; monitoring a measurement state of the measured biosignal using at least one predetermined determination reference corresponding to the extracted one or more features, wherein the at least one predetermined determination reference includes any one or both of a universal reference applied according to the biosignal to be measured and bioinformation and a self-reference personalized for each user; Execute predefined actions based on monitored measurement status, Wherein, the extracted one or more features include: any one or both of a current cycle of a biological signal measured during a predetermined period of time and an average cycle of the measured biological signal, and the step of monitoring the measurement status of the measured biological signal includes: determining whether the average cycle is normal by using a cycle universal reference of biological information to be measured using the biological signal among predetermined determination references, and / or determining whether the current cycle is normal by using a cycle self-reference personalized for the user among predetermined determination references.

29. The method according to claim 28, wherein: The steps of monitoring the measurement status of the biological signal include: determining whether the extracted one or more features are normal using any one or both of a self-reference and a universal reference included in the at least one predetermined determination reference; Based on whether one or more extracted features are determined to be normal, information on the measurement status including any one or any combination of the following items is output: motion noise status, ambient light noise status, unmeasured biological signal status, arrhythmia status, insufficient contact pressure status, contact failure status, and normal measurement status.

30. The method of claim 29, wherein: The performing of the predefined operation includes: controlling to stop and re-measure the biological signal based on the output information of the measurement state, or measuring the biological information using the measured biological signal.

31. The method of claim 30, further comprising: Output the result of measuring biological information.

32. A device for monitoring a biological signal measurement status, the device comprising: a bio-signal receiver configured to: receive a bio-signal measured from a user; The processor is configured as: extracting waveform, period, and amplitude from received biosignals; By comparing the extracted waveform with the reference waveform, it is determined whether the extracted waveform is normal; By comparing the extracted amplitude with the reference amplitude, it is determined whether the extracted amplitude is normal; By comparing the extracted cycle with the reference cycle, it is determined whether the extracted cycle is normal; Based on the extracted amplitude being determined to be abnormal, controlling the output of any one or any combination of a contact pressure insufficient state, an ambient light noise state, and a state where the bio-signal is not measured; Based on one of the extracted period and the extracted waveform being determined to be abnormal, controlling any one or any combination of an output motion noise state, an arrhythmia state, and a contact failure state; Based on the extracted amplitude, extracted period, and extracted waveform being determined to be normal, the control output is in a normal measurement state, wherein any one of the reference waveform, the reference amplitude, and the reference period includes any one or both of a universal reference applied according to the biosignal and bioinformation to be measured and a self-reference personalized for each user, Wherein, the extracted period includes: any one or both of the current period of the biological signal received during a predetermined period of time and the average period of the received biological signal, and the processor is also configured to: determine whether the average period is normal by using a universal reference of the period of the biological information to be measured using the biological signal among the reference periods, and / or determine whether the current period is normal by using a period self-reference personalized for the user among the reference periods.

33. The apparatus of claim 32, wherein: The step of determining whether the extracted waveform is normal includes: determining that the extracted waveform is normal based on the similarity between the extracted waveform and the reference waveform being greater than a threshold; The step of determining whether the extracted amplitude is normal includes: determining that the extracted amplitude is normal based on a first difference between the extracted amplitude and the reference amplitude being within a first range; The step of determining whether the extracted cycle is normal includes: determining that the extracted cycle is normal based on a second difference between the extracted cycle and the reference cycle being within a second range.

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