Sphygmomanometer

Abstract

A sphygmomanometer (100) is provided with: a blood pressure measurement unit (210) that measures the blood pressure of a user on the basis of a pulse wave signal superimposed on a cuff pressure signal detected during pressurization or decompression of cuff pressure indicating the internal pressure of a cuff worn on a site to be measured of the user; a pulse wave number measurement unit (220) that measures the pulse wave number of the user on the basis of the pulse wave signal; an interval calculation unit (230) that calculates a pulse wave interval data set on the basis of the pulse wave signal; a clustering unit (240) that clusters the pulse wave interval data group into one or more clusters using a threshold value; and a determination unit (250) that determines whether or not atrial fibrillation has occurred in the user on the basis of an index value indicating the size of discretization of the data group belonging to the cluster. A clustering unit (240) sets a threshold value on the basis of the pulse wave number.

Description

Technical Field

[0001] The present disclosure relates to a sphygmomanometer, and in particular to a sphygmomanometer capable of determining atrial fibrillation. Background Art

[0002] People hope to find atrial fibrillation (Atrial fibrillation), which is the cause of heart disease, as early as possible. In the past, a technology for estimating atrial fibrillation based on pulse wave information obtained by a sphygmomanometer has been proposed. Specifically, during one measurement opportunity using a sphygmomanometer, multiple blood pressure measurements are performed, thereby obtaining the interval between pulse wave signals obtained in each blood pressure measurement, i.e., the pulse wave interval, and detecting atrial fibrillation based on the pulse wave interval.

[0003] For example, US Patent Application Publication No. 2016 / 0228017 (Patent Document 1) discloses a blood pressure measurement device that can indicate the presence or absence of atrial fibrillation.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: U.S. Patent Application Publication No. 2016 / 0228017 Summary of the invention

[0007] Problems to be solved by the invention

[0008] In the device disclosed in Patent Document 1, in order to determine the presence or absence of atrial fibrillation, a sequence defined by a predetermined pulse number etc. needs to be repeated multiple times (for example, three times) in one measurement opportunity. Therefore, the time required for measurement becomes longer, and the measurement site is compressed by the cuff, giving the user a sense of restraint, which becomes a burden for the user.

[0009] In one aspect, the present disclosure provides a blood pressure meter that can reduce the burden on a user when measuring blood pressure and can determine the presence or absence of atrial fibrillation with high accuracy.

[0010] Solutions for solving problems

[0011] In one example of the present disclosure, a sphygmomanometer includes: a blood pressure measuring unit that measures a user's blood pressure based on a pulse wave signal superimposed on a cuff pressure signal detected during pressurization or depressurization of the cuff pressure, the cuff pressure indicating the internal pressure of a cuff worn on a measured part of the user; a pulse wave number measuring unit that measures the user's pulse wave number based on the pulse wave signal; an interval calculating unit that calculates a data group of pulse wave intervals based on the pulse wave signal; a clustering unit that clusters the data group of pulse wave intervals into one or more clusters using a threshold value; and a determination unit that determines whether the user has atrial fibrillation based on an index value indicating the discrete size of the data group belonging to the cluster. The clustering unit sets the threshold value based on the pulse wave number.

[0012] According to the above configuration, the burden on the user can be reduced when measuring blood pressure, and the presence or absence of atrial fibrillation can be determined with high accuracy.

[0013] In another example of the present disclosure, the clustering unit sets a larger threshold value as the pulse wave number decreases.

[0014] According to the above configuration, since the threshold value is appropriately set according to the pulse wave number, it is possible to perform appropriate atrial fibrillation determination for each user.

[0015] In other examples of the present disclosure, the threshold is set to be less than or equal to the average value of the data set of the pulse wave interval.

[0016] According to the above configuration, the possibility of misjudging arrhythmias other than atrial fibrillation (for example, extrasystoles) as atrial fibrillation can be reduced.

[0017] In another example of the present disclosure, when pulse wave interval data groups are clustered into one cluster, the determination unit determines that the user has atrial fibrillation if a first index value indicating the size of dispersion of the data groups belonging to the one cluster is greater than or equal to a predetermined value.

[0018] According to the above configuration, it is possible to perform atrial re-determination with higher accuracy.

[0019] In another example of the present disclosure, when the pulse wave interval data group is clustered into a plurality of clusters, the determination unit determines that the user has atrial fibrillation if a second index value indicating the size of the dispersion of the data groups belonging to the plurality of clusters is greater than or equal to a predetermined value.

[0020] According to the above configuration, it is possible to perform atrial re-determination with higher accuracy.

[0021] In another example of the present disclosure, when the second index value is smaller than a predetermined value, the determination unit determines that the user has suffered an arrhythmia other than atrial fibrillation.

[0022] According to the above configuration, it is also possible to determine whether or not arrhythmias other than atrial fibrillation have occurred.

[0023] Effects of the Invention

[0024] According to the present disclosure, the burden on the user can be reduced when measuring blood pressure, and the presence or absence of atrial fibrillation can be determined with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a diagram showing a blood pressure monitor according to this embodiment.

[0026] Figure 2 This is a block diagram showing an example of the hardware configuration of a blood pressure monitor.

[0027] Figure 3 This is a block diagram showing the functional configuration of a sphygmomanometer.

[0028] Figure 4 This is a diagram showing an example of a data group of pulse wave intervals.

[0029] Figure 5 This is a diagram used to illustrate the clustering method.

[0030] Figure 6 It is a graph showing the clustering results.

[0031] Figure 7 This is a diagram for explaining a method of setting a threshold value.

[0032] Figure 8 This is a diagram for explaining the upper limit value of the threshold value.

[0033] Fig. 9 This is a flowchart for explaining the processing procedure executed by the sphygmomanometer.

[0034] Fig.10 This is a flowchart showing an example of a blood pressure measurement process of a sphygmomanometer.

[0035] Fig.11 This is a flowchart showing another example of the blood pressure measurement process of the sphygmomanometer. DETAILED DESCRIPTION

[0036] Hereinafter, the embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, the same components are marked with the same reference numerals. Their names and functions are also the same. Therefore, they will not be described in detail again.

[0037] [Application examples]

[0038] Reference Figure 1 , an application example of the present invention is described. Figure 1It is a diagram showing a sphygmomanometer 100 according to the present embodiment.

[0039] Reference Figure 1 The sphygmomanometer 100 is an upper arm sphygmomanometer for measuring the blood pressure of a user, i.e., a subject. The sphygmomanometer 100 has a main body and a cuff (armband) as main components. It should be noted that the sphygmomanometer 100 may also be a wrist sphygmomanometer in which the main body and the cuff (armband) are integrated. Figure 1 Describe the processing content.

[0040] exist Figure 1 In the embodiment, it is assumed that a user uses the sphygmomanometer 100 to measure his / her own blood pressure. The sphygmomanometer 100 starts blood pressure measurement according to the blood pressure measurement instruction of the user (corresponding to Figure 1 (1)). Specifically, the sphygmomanometer 100 extracts a pulse wave signal (variation component) superimposed on a cuff pressure signal detected during the process of increasing or decreasing the cuff pressure, the cuff pressure indicating the internal pressure of the cuff worn on the measured part (e.g., arm) of the user, and calculates the blood pressure value by an oscillometric method based on the pulse wave signal. For example, the sphygmomanometer 100 performs blood pressure measurement using a pressurization measurement method for measuring blood pressure during the process of increasing the cuff pressure, or a decompression measurement method for measuring blood pressure during the process of decompression after the process of increasing the cuff pressure.

[0041] The sphygmomanometer 100 measures (counts) the pulse wave number (corresponding to the pulse wave number) based on the pulse wave signal obtained during blood pressure measurement (obtained during the pressurization process in the case of the pressurization measurement method, and obtained during the depressurization process in the case of the depressurization measurement method). Figure 1 (2)), and calculate the data set of pulse wave intervals (corresponding to Figure 1 (3)). Typically, the pulse wave interval is the peak-to-peak interval (or equivalently the trough-to-trough interval) of the pulse wave.

[0042] For example, after getting Figure 1 When the pulse wave signal Pa is obtained, the data set of pulse wave intervals ta1 to ta5 is calculated. Similarly, when the pulse wave signal Pb is obtained, the data set of pulse wave intervals tb1 to tb5 is calculated, and when the pulse wave signal Pc is obtained, the data set of pulse wave intervals tc1 to tc5 is calculated.

[0043] The pulse wave signal Pa is an example of a pulse wave signal indicating atrial fibrillation. The pulse wave intervals ta1 to ta5 in the pulse wave signal Pa are irregularly discrete as a whole, and the pulse wave is generated randomly. The pulse wave signal Pb is an example of a pulse wave signal indicating normal sinus rhythm. The pulse wave intervals tb1 to tb5 in the pulse wave signal Pb are substantially the same, and the pulse wave is generated regularly. The pulse wave signal Pc is an example of a pulse wave signal indicating an arrhythmia other than atrial fibrillation (e.g., extrasystoles). The pulse wave intervals tc1 to tc3 and tc5 in the pulse wave signal Pc are substantially the same, but only the size of the pulse wave interval tc4 is different, and the pulse wave is partially missing.

[0044] In this embodiment, the presence or absence of atrial fibrillation is determined by focusing on the fact that the pulse wave intervals in the pulse wave signal representing atrial fibrillation are irregularly discrete as a whole, and using an index value also called Cstd (Clustered Standard Deviation) as an example of an index value representing the size of the discreteness (hereinafter also referred to as a "discrete index value").

[0045] The sphygmomanometer 100 clusters the data set of the calculated pulse wave intervals using the threshold value Th to generate one or more clusters (corresponding to Figure 1 (4)). For example, the sphygmomanometer 100 clusters the data set of the pulse wave interval by comparing the difference between each pulse wave interval included in the data set of the pulse wave interval with the threshold value Th.

[0046] For example, the data group of pulse wave intervals ta1 to ta5 is classified into a cluster with a large discreteness between each data. The data group of pulse wave intervals tb1 to tb5 generates a cluster with a small discreteness between each data. The data group of pulse wave intervals tc1 to tc5 is classified into a cluster with a small discreteness of each data to which pulse wave intervals tc1 to tc3 and tc5 belong and a cluster to which pulse wave interval tc4 belongs.

[0047] The sphygmomanometer 100 determines the presence or absence of atrial fibrillation (corresponding to Figure 1 (5)). In the data group of pulse wave intervals ta1 to ta5 corresponding to atrial fibrillation, since the discreteness between each data is large, the discrete index value of the data group is large. On the other hand, in the data group of pulse wave intervals tb1 to tb5 corresponding to normal sinus rhythm and the data group of pulse wave intervals tc1 to tc5 corresponding to extrasystoles, the discreteness between each data belonging to the cluster is small, so the discrete index value of the data group is small. Therefore, when the discrete index value of the data group belonging to the cluster is greater than or equal to the specified value, the sphygmomanometer 100 determines that atrial fibrillation has occurred.

[0048] Then, the sphygmomanometer 100 displays the measured blood pressure value and the determination result of atrial fibrillation on the display (corresponding to Figure 1 of (6)).

[0049] According to the above application example, blood pressure measurement and atrial fibrillation determination are performed simultaneously in one measurement opportunity, and it is not necessary to perform multiple blood pressure measurements for atrial fibrillation determination. As a result, in blood pressure measurement, the burden on the user, such as the repeated compression of the measurement site of the user and the prolonged blood pressure measurement time, can be reduced, and both blood pressure measurement and atrial fibrillation determination can be achieved. In addition, by using a discrete index value (e.g., Cstd), atrial fibrillation and arrhythmias other than atrial fibrillation can be distinguished, so the accuracy of atrial fibrillation determination can be improved.

[0050] [Configuration example]

[0051] <Hardware Configuration>

[0052] Figure 2 1 is a block diagram showing an example of the hardware configuration of the sphygmomanometer 100. Figure 2 The sphygmomanometer 100 includes a main body 10 and a cuff 20 as main components. The cuff 20 contains a fluid bag 22. The main body 10 includes a processor 110, an air system component 30 for blood pressure measurement, an A / D conversion circuit 310, a pump drive circuit 320, a valve drive circuit 330, a display 50, a memory 51, an operation unit 52, a communication interface 53, and a power supply unit 54.

[0053] The processor 110 is a calculation processing unit such as a CPU (Central Processing Unit) or an MPU (MultiProcessing Unit). The processor 110 realizes each process (step) of the blood pressure meter 100 described later by reading and executing a program stored in the memory 51. For example, the processor 110 controls the driving of the pump 32 and the valve 33 according to an operation signal from the operation unit 52. In addition, the processor 110 calculates the blood pressure value using an algorithm for blood pressure calculation by an oscillometric method, and displays the blood pressure value on the display 50.

[0054] The memory 51 is implemented by a RAM (Random Access Memory), a ROM (Read-Only Memory), a flash memory, etc. The memory 51 stores: a program for controlling the sphygmomanometer 100, data for controlling the sphygmomanometer 100, setting data for setting various functions of the sphygmomanometer 100, data of measurement results of blood pressure values, pulse wave numbers, pulse wave intervals, etc. In addition, the memory 51 is used as a working memory when executing a program, etc.

[0055] The air system assembly 30 supplies air to the fluid bag 22 contained in the cuff 20 or discharges air from the fluid bag 22 contained in the cuff 20 through the air piping. The air system assembly 30 includes a pressure sensor 31 for detecting the pressure in the fluid bag 22, and a pump 32 and a valve 33 as an expansion and contraction mechanism for expanding and contracting the fluid bag 22.

[0056] The pressure sensor 31 detects the pressure (cuff pressure) in the fluid bag 22, and outputs a signal (cuff pressure signal) corresponding to the detected pressure to the A / D conversion circuit 310. The pressure sensor 31 is, for example, a piezoresistive pressure sensor, and is connected to the pump 32, the valve 33, and the fluid bag 22 contained in the cuff 20 via an air pipe. In order to pressurize the cuff pressure, the pump 32 supplies air as a fluid to the fluid bag 22 via the air pipe. The valve 33 opens / closes in order to discharge the air in the fluid bag 22 or to seal the air into the fluid bag 22 via the air pipe to control the cuff pressure.

[0057] The A / D conversion circuit 310 converts the output value of the pressure sensor 31 (for example, a voltage value corresponding to the change in resistance caused by the piezoresistive effect) from an analog signal into a digital signal and outputs it to the processor 110. The processor 110 obtains a signal indicating the cuff pressure based on the output value of the A / D conversion circuit 310. The pump drive circuit 320 controls the drive of the pump 32 based on the control signal given by the processor 110. The valve drive circuit 330 controls the opening / closing of the valve 33 based on the control signal given by the processor 110.

[0058] The processor 110 performs blood pressure measurement by a pressurization measurement method or a decompression measurement method, wherein the pressurization measurement method measures the user's blood pressure based on a pulse wave signal during a pressurization process in which the cuff pressure is pressurized, and the decompression measurement method measures the user's blood pressure based on a pulse wave signal during a decompression process in which the cuff pressure is decompressed after a pressurization process in which the cuff pressure is pressurized to a pressure greater than a specified pressure (for example, the "estimated systolic blood pressure" described later).

[0059] For example, when measuring by the decompression measurement method, the following actions are roughly performed. The cuff 20 is wrapped around the user's measured part (wrist, arm, etc.) in advance. During the measurement, the pump 32 and the valve 33 are controlled to increase the cuff pressure to a level higher than the estimated systolic blood pressure, and then the cuff pressure is gradually reduced. During the decompression process, the cuff pressure is detected by the pressure sensor 31, and the change in arterial volume occurring in the artery of the measured part is taken out as a pulse wave signal. Based on the change in the amplitude of the pulse wave signal (mainly rising and falling) accompanied by the change in the cuff pressure at this time, the systolic blood pressure (maximum blood pressure) and the diastolic blood pressure (minimum blood pressure) are calculated.

[0060] The display 50 displays various information including blood pressure measurement results and atrial fibrillation determination results based on a control signal from the processor 110. The communication interface 53 exchanges various information with an external device. The power supply unit 54 supplies power to the processor 110 and various hardware.

[0061] The operation unit 52 inputs an operation signal corresponding to an instruction from the user to the processor 110. For example, the operation unit 52 includes a measurement switch 52A for accepting an instruction from the user to start blood pressure measurement.

[0062] (Functional composition)

[0063] Figure 3 is a block diagram showing the functional configuration of the sphygmomanometer 100. Figure 3 The sphygmomanometer 100 includes a blood pressure measuring unit 210, a pulse wave number measuring unit 220, an interval calculating unit 230, a clustering unit 240, a determining unit 250, and an output control unit 260 as main functional components. These functions are implemented, for example, by causing the processor 110 of the sphygmomanometer 100 to execute a program stored in the memory 51. It should be noted that some or all of these functions may also be implemented by hardware.

[0064] The blood pressure measurement unit 210 controls the cuff pressure in accordance with a measurement start instruction (for example, pressing the measurement switch 52A) from the user via the operation unit 52. Specifically, the blood pressure measurement unit 210 controls the pump 32 to be driven via the pump drive circuit 320 and the valve 33 to be driven via the valve drive circuit 330. The valve 33 is opened / closed in order to discharge or seal air in the fluid bag 22 and control the cuff pressure.

[0065] The blood pressure measuring unit 210 receives the cuff pressure signal detected by the pressure sensor 31, and extracts a pulse wave signal representing the pulse wave of the measured part superimposed on the cuff pressure signal. That is, the blood pressure measuring unit 210 detects the pressure component, i.e., the pulse wave, superimposed on the cuff pressure signal in synchronization with the heart beat of the user from the cuff pressure signal.

[0066] The blood pressure measuring unit 210 measures the user's blood pressure based on the pulse wave signal superimposed on the cuff pressure signal detected during the process of increasing or decreasing the cuff pressure. Specifically, the blood pressure measuring unit 210 measures the user's blood pressure by a pressurization measurement method or a decompression measurement method according to the oscillometric method. For example, in the case of a decompression measurement method in which the pulse wave is detected when the fluid bag 22 is decompressed, the blood pressure measuring unit 210 calculates the systolic blood pressure based on the cuff pressure when the amplitude of the pulse wave signal increases sharply (increases) and the diastolic blood pressure based on the cuff pressure when the amplitude of the pulse wave signal decreases sharply (increases). It should be noted that the blood pressure measuring unit 210 may also adopt a so-called pressurization measurement method in which the pulse wave is detected when the fluid bag 22 is pressurized.

[0067] The pulse wave number measurement unit 220 measures the pulse wave number N of the user based on the pulse wave signal obtained when the blood pressure is measured by the blood pressure measurement unit 210. Specifically, when the blood pressure is measured by the pressurization measurement method, the pulse wave number measurement unit 220 measures the pulse wave number N based on the pulse wave signal during the pressurization process of the cuff pressure. When the blood pressure is measured by the decompression measurement method, the pulse wave number measurement unit 220 measures the pulse wave number N based on the pulse wave signal during the decompression process of the cuff pressure.

[0068] The interval calculation unit 230 calculates a data set of pulse wave intervals based on the pulse wave signal. Specifically, when the blood pressure is measured by the pressurization measurement method, the interval calculation unit 230 calculates a data set of pulse wave intervals represented by the pulse wave signal based on the pulse wave signal during the cuff pressure pressurization process. When the blood pressure is measured by the decompression measurement method, the interval calculation unit 230 calculates a data set of pulse wave intervals represented by the pulse wave signal based on the pulse wave signal during the cuff pressure decompression process. For example, when the Figure 1 In the case of the pulse wave signal Pa in , the data group of the pulse wave intervals is the pulse wave intervals ta1 to ta5.

[0069] The clustering unit 240 clusters the data group of the pulse wave interval into one or more clusters using the threshold value Th. Specifically, the clustering unit 240 sorts the data group of the pulse wave interval in ascending or descending order, and compares the difference between the front and back of each data (pulse wave interval) with the threshold value Th, thereby clustering the data group of the pulse wave interval to generate one or more clusters.

[0070] In addition, the clustering unit 240 sets a threshold value Th based on the pulse wave number N. Specifically, the smaller the pulse wave number N is, the larger the threshold value Th is set by the clustering unit 240. However, the threshold value Th is set to be less than or equal to the average value of the data group of the pulse wave interval. The details of the clustering method of the data group of the pulse wave interval will be described later.

[0071] The determination unit 250 receives input of cluster information from the clustering unit 240. The cluster information includes the number of clusters, information indicating the data group belonging to each cluster, etc. The determination unit 250 calculates the discrete index value of the data group belonging to the cluster based on the cluster information, and determines whether the user has atrial fibrillation based on the discrete index value.

[0072] In one aspect, when the data groups of pulse wave intervals are clustered into one cluster, if the discrete index value of the data group belonging to the one cluster is greater than or equal to a predetermined value, the determination unit 250 determines that the user has atrial fibrillation.

[0073] When the number of clusters is one, any one of the standard deviation, variance, mean absolute deviation, and median absolute deviation is used as the dispersion index value. Specifically, the determination unit 250 calculates any one of the standard deviation, variance, mean absolute deviation, and median absolute deviation of the data group belonging to the one cluster as the dispersion index value.

[0074] In another aspect, when the data group of pulse wave intervals is clustered into a plurality of clusters, if the discrete index value of the data group belonging to the plurality of clusters is greater than or equal to a predetermined value, the determination unit 250 determines that the user has atrial fibrillation. Furthermore, if the discrete index value is less than a predetermined value, the determination unit 250 determines that the user has an arrhythmia other than atrial fibrillation.

[0075] When there are multiple clusters, any one of Cstd, "Clustered Variance (also called "CVar" for convenience: cluster variance), "Clustered Absolute Deviation (also called "CAD" for convenience: cluster absolute deviation), the average value of standard deviation, the average value of variance, the average value of mean absolute deviation, and the average value of median absolute deviation is used as a discrete index value. Specifically, the determination unit 250 calculates any one of Cstd, CVar, CAD, the average value of standard deviation, the average value of variance, the average value of mean absolute deviation, and the average value of median absolute deviation as a discrete index value for a data group belonging to multiple clusters.

[0076] Assume that Cstd is used as the discrete index value. In this case, the determination unit 250 calculates the sum of squares of the deviations of the data groups belonging to each cluster, and calculates the square root of the value obtained by dividing the total value of the sum of squares of the deviations by the total number of pulse wave interval data as Cstd. More specifically, the total number of pulse wave interval data is N, the number of clusters is m, and the average value of the data groups in the cluster is x. av , set the number of data in the data group to n, and set the data value contained in the data group to x i(where i = 1 to n), and the sum of squared deviations of the data set is set to S k (where k=1 to m) In this case, Cstd is calculated using the following equations (1) and (2).

[0077] [Formula 1]

[0078]

[0079] Assume that CVar is used as the discrete index value. In this case, the determination unit 250 calculates the sum of squares of the deviations of the data groups belonging to each cluster, and calculates the value obtained by dividing the total value of the sum of squares of the deviations by the total number of data of the pulse wave interval as CVar. More specifically, CVar is calculated using equation (1) and the following equation (3).

[0080] [Formula 2]

[0081]

[0082] Assume that CAD is used as the discrete index value. In this case, the determination unit 250 calculates the absolute deviation sum of the data group belonging to each cluster, and calculates the value obtained by dividing the total value of each absolute deviation sum by the total data of the pulse wave interval as CAD. More specifically, if the absolute deviation sum of the data group in the cluster is set to T k (where k = 1 to m), the CAD is calculated using the following equations (4) and (5). It should be noted that other variables (such as x av The variables used in equation (1) are the same as those used in equation (1).

[0083] [Formula 3]

[0084]

[0085] The average value of the standard deviation, the average value of the variance, the average value of the mean absolute deviation, and the average value of the median absolute deviation used as the dispersion index value are calculated as follows. Specifically, the determination unit 250 calculates the standard deviation of the data group belonging to each cluster, and calculates the value obtained by dividing the total value of each standard deviation by the number of clusters m as the "average value of the standard deviation". The determination unit 250 calculates the variance of the data group belonging to each cluster, and calculates the value obtained by dividing the total value of each variance by the number of clusters m as the "average value of the variance".

[0086] The determination unit 250 calculates the mean absolute deviation (the value obtained by dividing the sum of the absolute deviations by the number of data n) of the data groups belonging to each cluster, and calculates the value obtained by dividing the total value of the mean absolute deviations by the number of clusters m as the "average value of the mean absolute deviations". The determination unit 250 calculates the median absolute deviation of the data groups belonging to each cluster, and calculates the value obtained by dividing the total value of the median absolute deviations by the number of clusters m as the "average value of the median absolute deviations". It should be noted that the details of the determination method of atrial fibrillation will be described later.

[0087] The output control unit 260 displays the measurement results (e.g., systolic blood pressure value and diastolic blood pressure value) of the blood pressure measurement unit 210 and the determination results (e.g., the determination result of whether atrial fibrillation occurs) of the determination unit 250 on the display 50. It should be noted that the output control unit 260 may send the measurement results and the determination results to an external device via the communication interface 53, or may be configured to output sound via a speaker (not shown).

[0088] (Clustering and determination of atrial fibrillation)

[0089] Figure 4 is a diagram showing an example of a data set of pulse wave intervals. Specifically, Figure 4 (a) is an example of a data set representing pulse wave intervals in a pulse wave signal of atrial fibrillation. Figure 4 (b) is an example of a data set representing pulse wave intervals in a pulse wave signal of a normal sinus rhythm. Figure 4 (c) is an example of a data set representing the pulse wave interval in the pulse wave signal of extrasystole. Figure 4 (a)~ Figure 4 In (c), the vertical axis represents the value obtained by normalizing the pulse wave interval, and the horizontal axis represents the order of the generated pulses.

[0090] Figure 4 The value represented by the vertical axis of is a value normalized by dividing the value of each pulse wave interval included in the data set of pulse wave intervals by the average value of each pulse wave interval. Therefore, when the pulse wave interval T is the same as the average value, the value obtained by normalizing the pulse wave interval T is "1".

[0091] Reference Figure 4 In (a), the pulse wave interval data set is irregularly discrete between about 0.6 and 1.5. This is consistent with Figure 1 The data groups ta1 to ta5 of the pulse wave intervals in the pulse wave signal Pa have the same tendency.

[0092] Reference Figure 4In (b), there is no discreteness in the pulse wave interval data set, and each data exists near 1.0. This is consistent with Figure 1 The data groups tb1 to tb5 of the pulse wave intervals in the pulse wave signal Pb have the same tendency.

[0093] Reference Figure 4 (c) In the data set of pulse wave intervals, some data are discrete. Specifically, many data are near 1.0, but some data (such as the 2nd, 3rd, 15th, 16th, 22nd, and 23rd data) are slightly different values. This is related to Figure 1 The data groups tc1 to tc5 of the pulse wave intervals in the pulse wave signal Pc have the same tendency.

[0094] The sphygmomanometer 100 (clustering unit 240) Figure 4 The data set of pulse wave intervals represented by the clustering method is clustered to generate more than one cluster. First, use Figure 5 The clustering method is described.

[0095] Figure 5 This is a diagram used to illustrate the clustering method. Figure 5 , assuming a scenario where data groups D1 to D15 are clustered. Data groups D1 to D15 are formed by rearranging the data groups of pulse wave intervals in the pulse wave signal in descending order. That is, data D1 is the largest and data D15 is the smallest.

[0096] Clustering is performed by comparing the difference between the data before and after with the threshold value Th. For example, the sphygmomanometer 100 (e.g., the clustering unit 240) determines whether the difference between data D1 and data D2 after (adjacent to) data D1 is greater than or equal to the threshold value Th. Since the difference is greater than or equal to the threshold value Th, data D1 is classified into a cluster different from data D2. Figure 5 In the example, data D1 belongs to cluster C1.

[0097] Similarly, since the difference between data D2 and data D3 is less than the threshold value Th, the clustering unit 240 classifies data D2 and data D3 into the same cluster. Next, since the difference between data D3 and data D4 is greater than or equal to the threshold value Th, the clustering unit 240 classifies data D3 into a cluster different from data D4. Figure 5 In the example, data D2 and data D3 belong to cluster C2.

[0098] By repeatedly performing the above process, data D1 belongs to cluster C1, data D2 and D3 belong to cluster C2, data D4 to D6 belong to cluster C3, and data D7 to D15 belong to cluster C4. Figure 5In the example of , the clustering unit 240 clusters the pulse wave interval data groups D1 to D15 into four clusters C1 to C4 using the threshold value Th.

[0099] Figure 6 is a graph representing the clustering results. Specifically, Figure 6 Indicates the use of threshold Th Figure 4 (a)~ Figure 4 (c) shows the result of clustering the pulse wave interval data sets. Figure 5 The clustering method described in Figure 4 The data set of pulse wave intervals associated with atrial fibrillation shown in (a) is clustered into a cluster X1. Figure 4 The data set of pulse wave intervals associated with normal sinus rhythm shown in (b) is clustered into a cluster Y1. Figure 4 The data set of pulse wave intervals related to extrasystoles shown in (c) is clustered into three clusters Z1 to Z3.

[0100] Since the data set of pulse wave intervals related to atrial fibrillation is clustered into one cluster X1, any one of the four index values ​​(i.e., standard deviation, variance, mean absolute deviation, and median absolute deviation) is used as the discrete index value Sdx of the data set. Figure 6 As shown in FIG. 1 , since the data group belonging to cluster X1 has a large discreteness, the discrete index value Sdx of the data group becomes larger. Similarly, since the data group of pulse wave intervals related to normal sinus rhythm is clustered into a cluster Y1, any one of the above four index values ​​is used as the discrete index value Sdy of the data group. The discrete index values ​​Sdx and Sdy use the same type of index value. Figure 6 As shown, since the discreteness of the data group belonging to cluster Y1 is small, the discrete index value Sdy of the data group becomes small.

[0101] Since the data set of pulse wave intervals corresponding to extrasystoles is clustered into three clusters Z1 to Z3, any one of Cstd, CVar, CAD, the average of standard deviation, the average of variance, the average of mean absolute deviation, and the average of median absolute deviation is used as the discrete index value Sdz of the data set. Figure 6 As shown in FIG. 1 , the dispersion of the data group belonging to each of the clusters Z1 to Z3 is small. Therefore, the dispersion index value Sdz of the data group of the pulse wave interval corresponding to the extrasystole becomes small.

[0102] Therefore, when atrial fibrillation occurs, the discrete index value calculated in the above manner becomes larger. Therefore, the sphygmomanometer 100 (determination unit 250) calculates the discrete index value of the data group belonging to the clustered cluster, and determines that atrial fibrillation has occurred when the discrete index value is greater than a predetermined value.

[0103] It should be noted that when the data group of the pulse wave interval is clustered into a plurality of clusters, if the discrete index value of the data group belonging to the plurality of clusters is greater than or equal to a predetermined value, the sphygmomanometer 100 (determination unit 250) determines that atrial fibrillation has occurred. This is because it is considered that although a plurality of clusters are generated, the discreteness of the data group belonging to each cluster is large, and the data group of the pulse wave interval is irregularly discrete as a whole (that is, the discrete index value is large).

[0104] On the other hand, when the discrete index value of the data group belonging to the plurality of clusters is smaller than the predetermined value, the sphygmomanometer 100 (determination unit 250 ) determines that an arrhythmia other than atrial fibrillation (eg, extrasystoles) has occurred.

[0105] Furthermore, when the data groups of pulse wave intervals are clustered into one cluster and the discrete index value of the data groups belonging to the cluster is smaller than a predetermined value, the sphygmomanometer 100 (determination unit 250 ) can determine that the user's pulse is normal (eg, normal sinus rhythm).

[0106] In order to appropriately determine the presence or absence of atrial fibrillation as described above, clustering needs to be performed using an appropriate threshold value Th. The following describes how to set the threshold value Th.

[0107] Figure 7 This is a diagram for explaining a method of setting a threshold value. Figure 7 (a) and Figure 7 (b) and (c) all represent the results of clustering the data set of pulse wave intervals related to atrial fibrillation according to the threshold value Th. Figure 7 (a) shows the clustering result when the number of pulse waves is large. Figure 7 (b) shows the clustering result when the number of pulse waves is small.

[0108] exist Figure 7 In (a), a cluster Ca is generated, and the data set of pulse wave intervals belonging to cluster Ca has large dispersion, so the dispersion index value (such as standard deviation, variance, mean absolute deviation or median absolute deviation) of the data set becomes large. Therefore, it is correctly determined that atrial fibrillation has occurred.

[0109] On the other hand, Figure 7 In (b), three clusters Cb1 to Cb3 are generated, and the discreteness of the data groups of pulse wave intervals belonging to clusters Cb1 to Cb3 is small. Therefore, the discrete index values ​​of the data groups in the multiple clusters Cb1 to Cb3 (for example, Cstd, CVar, CAD, the average value of the standard deviation, the average value of the variance, the average value of the mean absolute deviation, or the average value of the median absolute deviation) also become small. Therefore, it is erroneously determined that an arrhythmia other than atrial fibrillation has occurred.

[0110] In order to prevent such erroneous determination, the sphygmomanometer 100 (clustering unit 240) changes the threshold value Th according to the pulse wave number. Specifically, the clustering unit 240 sets the threshold value Th to be larger as the pulse wave number decreases. Figure 7 As shown in (b), when the pulse wave number is small, the threshold value Th becomes larger, so the clustering unit 240 generates one cluster Cb instead of three clusters Cb1 to Cb3. The data group of pulse wave intervals belonging to cluster Cb has large dispersion, so the dispersion index value of the data group becomes larger. Therefore, it is correctly determined that atrial fibrillation has occurred.

[0111] It should be noted that the use of Figure 8 , the upper limit value of the threshold Th can be considered as follows.

[0112] Figure 8 is a diagram for explaining the upper limit value of the threshold. Figure 8 , shows an example where one pulse is missing from the pulse wave signal Pd. As described above, if the pulse wave interval is the same as the average value of the data set of the pulse wave interval, the value obtained by normalizing the pulse wave interval is "1". Figure 8 In the example, the pulse wave intervals Ta and Tc are "1". Next, when one pulse is missing, the pulse wave intervals Tb before and after it are "2". Therefore, the difference between adjacent pulse wave intervals is "1" (i.e., 2-1=1), which is consistent with the average value of the data set of pulse wave intervals.

[0113] The phenomenon of pulse loss is a common phenomenon in arrhythmias other than atrial fibrillation (e.g., extrasystoles). Therefore, when the threshold value Th is set to "1" or more, the data group related to extrasystoles may be clustered into a single cluster instead of a plurality of clusters. In this case, arrhythmias other than atrial fibrillation may be misjudged as "atrial fibrillation". Therefore, the upper limit of the threshold value Th is set to the average value of the data group of pulse wave intervals.

[0114] (Processing process)

[0115] Fig. 9 2 is a flowchart for explaining the processing procedure executed by the sphygmomanometer 100. Fig. 9 When the process starts, the cuff 20 is worn on the user's measured part.

[0116] Reference Fig. 9, the processor 110 of the sphygmomanometer 100 receives an operation signal based on the user's operation of the measurement switch 52A from the operation unit 52 (step S10). The processor 110 starts the blood pressure measurement process in response to the operation signal (step S20). In the blood pressure measurement process, a data set of the blood pressure value, the pulse wave number N, and the pulse wave interval is calculated based on the pulse wave signal. The details of the blood pressure measurement process will be described later.

[0117] The processor 110 performs atrial fibrillation determination processing based on the data set of the pulse wave number N and the pulse wave interval (step S30). Specifically, the processor 110 sets a threshold value Th for clustering based on the pulse wave number N, and clusters the data set of the pulse wave interval into one or more clusters using the threshold value Th. Next, the processor 110 determines whether atrial fibrillation has occurred based on the discrete index value of the data set belonging to the cluster.

[0118] The processor 110 displays the blood pressure measurement result (eg, systolic blood pressure and diastolic blood pressure) and the result of the atrial fibrillation determination process on the display 50 (step S40 ).

[0119] Fig.10 1 is a flowchart showing an example of a blood pressure measurement process performed by the sphygmomanometer 100 . Fig.10 The blood pressure measurement process shown (corresponding to Fig. 9 Step S20) is a process of measuring blood pressure by a pressure measurement method.

[0120] Reference Fig.10 The processor 110 of the sphygmomanometer 100 initializes the pressure sensor 31 (step S102 ). Specifically, the processor 110 initializes the processing storage area, and performs 0 mmHg adjustment (setting the atmospheric pressure to 0 mmHg) of the pressure sensor 31 while the pump 32 is disconnected (stopped) and the valve 33 is open.

[0121] Next, the processor 110 closes the valve 33 via the valve drive circuit 330 (step S104), and starts the pump 32 via the pump drive circuit 320, thereby starting to pressurize the cuff 20 (fluid bag 22) (step S106). At this time, the processor 110 controls the pressurization speed of the cuff pressure, which is the pressure in the fluid bag 22, based on the output of the pressure sensor 31 while supplying air from the pump 32 to the fluid bag 22 through the air piping. Thus, the pressurization process starts.

[0122] Next, the processor 110 extracts a pulse wave signal from the cuff pressure signal detected by the pressure sensor 31 , attempts to calculate the systolic blood pressure and the diastolic blood pressure based on the pulse wave signal, and determines whether the blood pressure calculation is complete (step S108 ).

[0123] If the blood pressure calculation cannot be completed due to insufficient data ("No" in step S108), the processor 110 repeats the processing of steps S106 and S108 unless the cuff pressure reaches a predetermined upper limit pressure (for example, 300 mmHg). If the blood pressure calculation is completed ("Yes" in step S108), the processor 110 performs the following control: the pump 32 is stopped (i.e., the pressurization process is stopped) (step S110), the valve 33 is opened (step S112), and the air in the cuff 20 is exhausted.

[0124] The processor 110 calculates a data set of the pulse wave number N and the pulse wave interval based on the pulse wave signal obtained during the compression process (step S114 ). The processor 110 stores the calculated data set of the pulse wave number N and the pulse wave interval in the memory 51 .

[0125] Fig.11 : is a flowchart showing another example of the blood pressure measurement process of the sphygmomanometer 100 . Fig.11 The blood pressure measurement process shown (corresponding to Fig. 9 Step S20) is a process of measuring blood pressure by a decompression measurement method.

[0126] Reference Fig.11 The processing of steps S122 to S126 is respectively the same as Fig.10 The processing of steps S102 to S106 is the same, so the detailed description thereof will not be given again.

[0127] The processor 110 estimates the systolic blood pressure based on the pulse wave signal obtained during the pressurization (step S128). The processor 110 determines whether the cuff pressure has reached or exceeded the pressure P (step S130). Typically, the pressure P is set to a value that is a fixed value (e.g., 40 mmHg) higher than the estimated systolic blood pressure value.

[0128] When the cuff pressure is less than the pressure P ("No" in step S130), the processor 110 returns to step S126. When the cuff pressure is greater than or equal to the pressure P ("Yes" in step S130), the processor 110 controls to stop the pump 32 (step S132) and gradually open the valve 33 (step S134). Thus, the process of pressurization is changed to the process of decompression (i.e., the process of decompression is started), and the cuff pressure is gradually reduced.

[0129] During the decompression process, the processor 110 extracts the pulse wave signal from the cuff pressure signal detected by the pressure sensor 31, attempts to calculate the systolic blood pressure and the diastolic blood pressure based on the pulse wave signal, and determines whether the blood pressure calculation is completed (step S136). If the blood pressure calculation is not completed ("No" in step S136), the processor 110 repeatedly performs the processing of steps S134 and S136. If the blood pressure calculation is completed ("Yes" in step S136), the processor 110 performs the following control: the valve 33 is fully opened (step S138) to rapidly exhaust the air in the cuff 20.

[0130] The processor 110 calculates a data set of the pulse wave number N and the pulse wave interval based on the pulse wave signal obtained during the decompression process (step S140 ). The processor 110 stores the calculated data set of the pulse wave number N and the pulse wave interval in the memory 51 .

[0131] <Other Implementation Methods>

[0132] (1) In the above embodiment, a program for causing a computer to function to execute the control described in the above flowchart can also be provided. Such a program can be recorded in a non-temporary computer-readable recording medium such as a floppy disk, a CD-ROM (Compact Disk Read Only Memory), a secondary storage device, a main storage device, and a memory card attached to the computer, and provided as a program product. Alternatively, the program can be provided by recording in a recording medium such as a hard disk built into the computer. In addition, the program can also be provided by downloading via a network.

[0133] (2) The configurations illustrated as examples in the above-mentioned embodiments are examples of the configurations of the present invention, and can be combined with other known technologies, or can be modified by omitting a portion of the configurations without departing from the gist of the present invention. In addition, in the above-mentioned embodiments, the processes and configurations described in other embodiments can be appropriately adopted for implementation.

[0134] [Note]

[0135] As described above, the present embodiment includes the following disclosures.

[0136] [Composition 1]

[0137] A sphygmomanometer (100) comprises: a blood pressure measuring unit (210) for measuring a user's blood pressure based on a pulse wave signal superimposed on a cuff pressure signal detected during a process of increasing or decreasing cuff pressure, wherein the cuff pressure represents the internal pressure of a cuff (20) worn on a measured part of the user; a pulse wave number measuring unit (220) for measuring the user's pulse wave number based on the pulse wave signal; an interval calculating unit (230) for calculating a data group of pulse wave intervals based on the pulse wave signal; a clustering unit (240) for clustering the data group of pulse wave intervals into one or more clusters using a threshold; and a determination unit (250) for determining whether the user has atrial fibrillation based on an index value representing the discrete size of the data group belonging to the cluster, wherein the clustering unit (240) sets the threshold based on the pulse wave number.

[0138] [Composition 2]

[0139] The sphygmomanometer (100) according to configuration 1, wherein the clustering unit (240) sets the threshold value to a larger value as the pulse wave number decreases.

[0140] [Composition 3]

[0141] The sphygmomanometer (100) according to configuration 1 or 2, wherein the threshold value is set to be less than or equal to an average value of the data group of the pulse wave interval.

[0142] [Composition 4]

[0143] According to the blood pressure meter (100) described in any one of structures 1 to 3, when the data group of the pulse wave interval is clustered into a cluster, when the first indicator value representing the discrete size of the data group belonging to the cluster is greater than or equal to a specified value, the determination unit (250) determines that the user has atrial fibrillation.

[0144] [Composition 5]

[0145] According to the blood pressure meter (100) described in any one of structures 1 to 4, when the data group of the pulse wave interval is clustered into multiple clusters, when the second indicator value representing the discrete size of the data group belonging to the multiple clusters is greater than or equal to a specified value, the determination unit (250) determines that the user has atrial fibrillation.

[0146] [Composition 6]

[0147] The blood pressure meter (100) according to configuration 5, wherein when the second index value is smaller than the predetermined value, the determination unit (250) determines that the user has suffered from an arrhythmia other than atrial fibrillation.

[0148] The embodiments disclosed this time should be considered in all respects as illustrative and non-restrictive. The scope of the present invention is indicated by the claims rather than the above description, and is intended to include all modifications within the meaning and scope equivalent to the claims.

[0149] Description of Reference Numerals

[0150] 10: Main body; 20: Cuff; 22: Fluid bag; 30: Air system component; 31: Pressure sensor; 32: Pump; 33: Valve; 50: Display; 51: Memory; 52: Operation unit; 52A: Measurement switch; 53: Communication interface; 54: Power supply unit; 100: Sphygmomanometer; 110: Processor; 210: Blood pressure measurement unit; 220: Pulse wave number measurement unit; 230: Interval calculation unit; 240: Clustering unit; 250: Judgment unit; 260: Output control unit; 310: A / D conversion circuit; 320: Pump drive circuit; 330: Valve drive circuit.

Claims

1. A sphygmomanometer, comprising: a blood pressure measuring unit that measures the user's blood pressure based on a pulse wave signal superimposed on a cuff pressure signal detected during the process of increasing or decreasing the cuff pressure, the cuff pressure indicating the internal pressure of a cuff worn on a measured part of the user; a pulse wave rate measuring unit for measuring the pulse wave rate of the user based on the pulse wave signal; an interval calculation unit that calculates a data set of pulse wave intervals based on the pulse wave signal; a clustering unit that clusters the data set of the pulse wave interval into one or more clusters using a threshold value; and a determination unit that determines whether the user has atrial fibrillation based on an index value indicating the size of the discreteness of the data group belonging to the cluster, The clustering unit sets the threshold value based on the pulse wave number.

2. The sphygmomanometer according to claim 1, wherein: The clustering unit sets the threshold value to be larger as the pulse wave number is smaller.

3. The sphygmomanometer according to claim 1 or 2, wherein: The threshold value is set to be less than or equal to the average value of the data group of the pulse wave interval.

4. The sphygmomanometer according to claim 1 or 2, wherein: When the data groups of the pulse wave intervals are clustered into one cluster, the determination unit determines that the user has atrial fibrillation if a first index value indicating the magnitude of dispersion of the data groups belonging to the one cluster is greater than or equal to a predetermined value.

5. The sphygmomanometer according to claim 1 or 2, wherein: When the data group of the pulse wave interval is clustered into a plurality of clusters, the determination unit determines that the user has atrial fibrillation if a second index value indicating the size of dispersion of the data groups belonging to the plurality of clusters is greater than or equal to a predetermined value.

6. The sphygmomanometer according to claim 5, wherein: When the second index value is smaller than the predetermined value, the determination unit determines that the user has suffered from an arrhythmia other than atrial fibrillation.

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