Sphygmomanometer

Abstract

To provide a sphygmomanometer capable of accurately determining presence or absence of atrial fibrillation while reducing a burden on a user when measuring blood pressure.SOLUTION: A sphygmomanometer includes: a blood pressure measuring part for measuring blood pressure of a user on the basis of a pulse wave signal superposed on a cuff pressure signal detected in the process of pressurizing or depressurizing cuff pressure indicating inner pressure of the cuff mounted on a measurement site of the user; a pulse wave number measuring part for measuring the pulse wave number of the user on the basis of the pulse wave signal; an interval calculation part for calculating a data group of pulse wave intervals on the basis of the pulse wave signal; a clustering part for clustering the data group of pulse wave intervals to one or more cluster using a threshold; and determination part for determining whether or not atrial fibrillation has occurred in the user on the basis of an index value showing the size of variations in the data group belonging to the cluster. The clustering part sets a threshold on the basis of the pulse wave number.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to a blood pressure monitor, and more particularly to a blood pressure monitor having a function of determining atrial fibrillation. [Background technology]

[0002] Early detection of atrial fibrillation, which can cause heart disease, is desirable. Conventionally, a technology has been proposed that estimates atrial fibrillation from pulse wave information acquired by a blood pressure monitor. Specifically, blood pressure is measured multiple times during one measurement session using a blood pressure monitor, and the pulse wave interval, which is the interval between pulse wave signals acquired during each blood pressure measurement, is acquired, and atrial fibrillation is detected based on the pulse wave interval.

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

[0004] [Patent Document 1] US Patent Application Publication No. 2016 / 0228017 Summary of the Invention [Problem to be solved by the invention]

[0005] 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 rate, etc. must be repeated consecutively multiple times (e.g., three times) in one measurement opportunity. This increases the time required for measurement, and places a burden on the user, such as by making the user feel restricted by the pressure on the measurement site caused by the cuff.

[0006] In one aspect, the present disclosure provides a blood pressure monitor that is capable of accurately determining the presence or absence of atrial fibrillation while reducing the burden on a user during blood pressure measurement. [Means for solving the problem]

[0007] In one example of the present disclosure, a blood pressure monitor includes a blood pressure measuring unit that measures the blood pressure of a user based on a pulse wave signal superimposed on a cuff pressure signal detected during a process of increasing or decreasing a cuff pressure indicating an internal pressure of a cuff attached to a measurement site of a user, a pulse wave number measuring unit that measures the pulse wave number of the user 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 determining unit that determines whether atrial fibrillation has occurred in the user based on an index value indicating the magnitude of variation of the data group belonging to the cluster. The clustering unit sets the threshold value based on the pulse wave number.

[0008] According to the above configuration, the presence or absence of atrial fibrillation can be accurately determined while reducing the burden on the user during blood pressure measurement.

[0009] In another example of the present disclosure, the clustering unit increases the threshold value as the pulse wave number decreases.

[0010] According to the above configuration, the threshold value is appropriately set according to the pulse wave rate, so that an appropriate atrial fibrillation determination can be performed for each user.

[0011] In another example of the present disclosure, the threshold is set to be equal to or less than the average value of the pulse wave interval data group.

[0012] According to the above configuration, it is possible to reduce the possibility of erroneously determining an arrhythmia other than atrial fibrillation (for example, an extrasystole) as atrial fibrillation.

[0013] In another example of the present disclosure, when a group of pulse wave interval data is clustered into one cluster, a determination unit determines that atrial fibrillation has occurred in the user if a first index value indicating the magnitude of variation in the group of data belonging to one cluster is equal to or greater than a predetermined value.

[0014] According to the above configuration, the atrial re-determination can be performed with higher accuracy.

[0015] In another example of the present disclosure, when a group of pulse wave interval data is clustered into multiple clusters, a determination unit determines that atrial fibrillation has occurred in the user if a second index value indicating the degree of variation in the data groups belonging to the multiple clusters is equal to or greater than a predetermined value.

[0016] According to the above configuration, the atrial re-determination can be performed with higher accuracy.

[0017] In another example of the present disclosure, the determining unit determines that the user has developed arrhythmia other than atrial fibrillation when the second index value is less than a predetermined value.

[0018] According to the above configuration, it is possible to determine whether or not arrhythmia other than atrial fibrillation has occurred. Effect of the Invention

[0019] According to the present disclosure, the presence or absence of atrial fibrillation can be accurately determined while reducing the burden on the user during blood pressure measurement. [Brief description of the drawings]

[0020] [Figure 1] FIG. 1 is a diagram showing a blood pressure monitor according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram illustrating an example of a hardware configuration of a sphygmomanometer. [Diagram 3] FIG. 2 is a block diagram showing the functional configuration of the sphygmomanometer. [Figure 4] FIG. 11 is a diagram showing an example of a data group of pulse wave intervals. [Diagram 5]FIG. 1 is a diagram for explaining a clustering method. [Figure 6] FIG. 13 is a diagram showing a clustering result. [Figure 7] FIG. 13 is a diagram for explaining a method for setting a threshold value. [Figure 8] FIG. 13 is a diagram for explaining an upper limit value of a threshold value. [Figure 9] 10 is a flowchart illustrating a process executed by the sphygmomanometer. [Figure 10] 10 is a flowchart showing an example of a blood pressure measurement process of the sphygmomanometer. [Figure 11] 10 is a flowchart showing another example of the blood pressure measurement process of the sphygmomanometer. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the following description, the same components are denoted by the same reference numerals. Their names and functions are also the same. Therefore, detailed description thereof will not be repeated.

[0022] [Example of application] An application example of the present invention will be described with reference to Fig. 1. Fig. 1 is a diagram showing a blood pressure monitor 100 according to the present embodiment.

[0023] With reference to Fig. 1, blood pressure monitor 100 is an upper arm type blood pressure monitor that measures the blood pressure of a subject who is a user. Blood pressure monitor 100 has a main body and a cuff (arm band) as main components. Note that blood pressure monitor 100 may be a wrist type blood pressure monitor in which the main body and the cuff (arm band) are integrated. Hereinafter, the processing contents will be described with reference to Fig. 1.

[0024] In Fig. 1, a situation is assumed in which a user measures his / her own blood pressure using a blood pressure monitor 100. The blood pressure monitor 100 starts blood pressure measurement according to a blood pressure measurement instruction from the user (corresponding to (1) in Fig. 1). Specifically, the blood pressure monitor 100 extracts a pulse wave signal (fluctuation component) superimposed on a cuff pressure indicating the internal pressure of a cuff attached to a measurement site (e.g., an arm) of the user, and calculates a blood pressure value by an oscillometric method based on the pulse wave signal. For example, the blood pressure monitor 100 performs blood pressure measurement using a pressurization measurement method in which blood pressure is measured during a cuff pressure pressurization process, or a depressurization measurement method in which blood pressure is measured during a depressurization process after the cuff pressure pressurization process.

[0025] The sphygmomanometer 100 measures (counts) the pulse wave number (corresponding to (2) in FIG. 1) based on the pulse wave signal obtained during blood pressure measurement (obtained during the pressurization process in the case of the pressurization measurement method, or during the depressurization process in the case of the depressurization measurement method), and calculates a data set of the pulse wave interval (corresponding to (3) in FIG. 1). Typically, the pulse wave interval is the peak-to-peak interval of the pulse wave (or the bottom-to-bottom interval, which is equivalent thereto).

[0026] 1, when pulse wave signal Pa is obtained, a data set of pulse wave intervals ta1-ta5 is calculated. Similarly, when pulse wave signal Pb is obtained, a data set of pulse wave intervals tb1-tb5 is calculated, and when pulse wave signal Pc is obtained, a data set of pulse wave intervals tc1-tc5 is calculated.

[0027] Pulse wave signal Pa is an example of a pulse wave signal indicative of atrial fibrillation. Pulse wave intervals ta1-ta5 in pulse wave signal Pa vary irregularly overall, with pulse waves occurring randomly. Pulse wave signal Pb is an example of a pulse wave signal indicative of normal sinus rhythm. Pulse wave intervals tb1-tb5 in pulse wave signal Pb are generally the same, with pulse waves occurring regularly. Pulse wave signal Pc is an example of a pulse wave signal indicative of an arrhythmia other than atrial fibrillation (e.g., premature contraction). Pulse wave intervals tc1-tc3 and tc5 in pulse wave signal Pc are generally the same, with the exception of pulse wave interval tc4, which has a different magnitude and is partially missing a pulse wave.

[0028] In this embodiment, attention is focused on the fact that the pulse wave intervals in a pulse wave signal indicating atrial fibrillation vary irregularly overall, and the presence or absence of atrial fibrillation is determined using an index value also called Cstd (Clustered Standard Deviation), which is an example of an index value indicating the magnitude of variation (hereinafter also called a "variation index value").

[0029] The sphygmomanometer 100 clusters the calculated pulse interval data group using a threshold Th to generate one or more clusters (corresponding to (4) in FIG. 1). For example, the sphygmomanometer 100 clusters the pulse interval data group by comparing the difference between each pulse interval included in the pulse interval data group with the threshold Th.

[0030] For example, the data group of pulse wave intervals ta1 to ta5 is classified into one cluster with large variation between the data. The data group of pulse wave intervals tb1 to tb5 is classified into one cluster with small variation between the data. The data group of pulse wave intervals tc1 to tc5 is classified into a cluster including pulse wave intervals tc1 to tc3 and tc5, which has small variation between the data, and a cluster including pulse wave interval tc4.

[0031] The sphygmomanometer 100 determines the presence or absence of atrial fibrillation based on the variation index value of the data group belonging to the cluster (corresponding to (5) in FIG. 1). In the data group of pulse wave intervals ta1 to ta5 corresponding to atrial fibrillation, the variation between each piece of data is large, so the variation 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 premature contractions, the variation between each piece of data belonging to the cluster is small, so the variation index value of the data group is small. Using this, the sphygmomanometer 100 determines that atrial fibrillation has occurred when the variation index value of the data group belonging to the cluster is equal to or greater than a predetermined value.

[0032] Then, the blood pressure monitor 100 displays the measured blood pressure value and the atrial fibrillation determination result on the display (corresponding to (6) in FIG. 1).

[0033] According to the above application example, blood pressure measurement and atrial fibrillation determination are performed simultaneously in one measurement opportunity, and there is no need to perform multiple blood pressure measurements to determine atrial fibrillation. As a result, both blood pressure measurement and atrial fibrillation determination can be achieved while reducing the burden on the user, such as the user being repeatedly pressed on the measurement site during blood pressure measurement and the blood pressure measurement time being extended. Furthermore, by using a variability index value (e.g., Cstd), atrial fibrillation can be distinguished from arrhythmias other than atrial fibrillation, thereby improving the accuracy of atrial fibrillation determination.

[0034] [Configuration example] <Hardware configuration> Fig. 2 is a block diagram showing an example of a hardware configuration of the blood pressure monitor 100. Referring to Fig. 2, the blood pressure monitor 100 includes, as main components, a main body 10 and a cuff 20. 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.

[0035] The processor 110 is an arithmetic processing unit such as a CPU (Central Processing Unit) or an MPU (Multi Processing Unit). The processor 110 realizes each of the processes (steps) of the sphygmomanometer 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 in response to an operation signal from the operation unit 52. The processor 110 also calculates a blood pressure value using an algorithm for calculating blood pressure by the oscillometric method, and displays the calculated blood pressure value on the display 50.

[0036] The memory 51 is realized 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 used for controlling the sphygmomanometer 100, setting data for setting various functions of the sphygmomanometer 100, and data of blood pressure measurement results, a pulse wave number, a pulse wave interval, etc. The memory 51 is also used as a work memory, etc. when the program is executed.

[0037] The air system component 30 supplies or exhausts air through air piping to the fluid bag 22 contained in the cuff 20. The air system component 30 includes a pressure sensor 31 for detecting the pressure inside the fluid bag 22, and a pump 32 and a valve 33 as an inflation / deflation mechanism for inflating and deflating the fluid bag 22.

[0038] 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 piezo-resistance type 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. The pump 32 supplies air as a fluid to the fluid bag 22 through the air pipe to increase the cuff pressure. The valve 33 is opened and closed to control the cuff pressure by discharging air from the fluid bag 22 through the air pipe or by sealing air in the fluid bag 22.

[0039] The A / D conversion circuit 310 converts the output value of the pressure sensor 31 (for example, a voltage value corresponding to a change in electrical resistance due to the piezoresistance effect) from an analog signal to a digital signal and outputs it to the processor 110. The processor 110 acquires a signal representing the cuff pressure according to the output value of the A / D conversion circuit 310. The pump drive circuit 320 controls the drive of the pump 32 based on a control signal provided by the processor 110. The valve drive circuit 330 controls the opening and closing of the valve 33 based on a control signal provided by the processor 110.

[0040] The processor 110 performs blood pressure measurement using a pressurization measurement method in which the user's blood pressure is measured based on the pulse wave signal during a pressurization process in which the cuff pressure is increased, or a depressurization measurement method in which the user's blood pressure is measured based on the pulse wave signal during a depressurization process in which the cuff pressure is reduced after a pressurization process in which the cuff pressure is increased to a pressure greater than a specified pressure (e.g., the "estimated systolic blood pressure" described below).

[0041] For example, when a measurement is performed using the reduced pressure measurement method, the following operation is generally performed. A cuff is wrapped around the user's measurement site (wrist, arm, etc.) in advance, and when a measurement is performed, pump 32 and valve 33 are controlled to increase the cuff pressure higher than the estimated systolic blood pressure, and then the pressure is gradually reduced. During this reduction process, the cuff pressure is detected by pressure sensor 31, and the change in arterial volume occurring in the artery at the measurement site is extracted as a pulse wave signal. Based on the change in amplitude of the pulse wave signal (mainly the rise and fall) accompanying the change in cuff pressure at that time, the systolic blood pressure (maximum blood pressure) and diastolic blood pressure (minimum blood pressure) are calculated.

[0042] The display 50 displays various information including blood pressure measurement results and atrial fibrillation determination results based on control signals from the processor 110. The communication interface 53 exchanges various information with external devices. The power supply unit 54 supplies power to the processor 110 and each piece of hardware.

[0043] The operation unit 52 inputs an operation signal corresponding to an instruction from a user to the processor 110. For example, the operation unit 52 includes a measurement switch 52A for receiving an instruction from a user to start blood pressure measurement.

[0044] (Functional configuration) Fig. 3 is a block diagram showing a functional configuration of the sphygmomanometer 100. Referring to Fig. 3, the sphygmomanometer 100 includes, as main functional components, a blood pressure measurement unit 210, a pulse wave number measurement unit 220, an interval calculation unit 230, a clustering unit 240, a determination unit 250, and an output control unit 260. Each of these functions is realized, for example, by the processor 110 of the sphygmomanometer 100 executing a program stored in the memory 51. Note that some or all of these functions may be configured to be realized by hardware.

[0045] The blood pressure measurement unit 210 controls the cuff pressure according to a measurement start instruction (e.g., pressing the measurement switch 52A) from the user via the operation unit 52. Specifically, the blood pressure measurement unit 210 drives the pump 32 via the pump drive circuit 320, and controls the drive of the valve 33 via the valve drive circuit 330. The valve 33 is opened and closed to discharge or seal air in the fluid bag 22 to control the cuff pressure.

[0046] The blood pressure measurement unit 210 receives the cuff pressure signal detected by the pressure sensor 31 and extracts a pulse wave signal representing the pulse wave at the measurement site superimposed on the cuff pressure signal. That is, the blood pressure measurement unit 210 detects, from the cuff pressure signal, a pulse wave, which is a pressure component that is superimposed on the cuff pressure signal in synchronization with the beating of the user's heart.

[0047] The blood pressure measurement 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 measurement unit 210 measures the user's blood pressure by an increase measurement method or a decrease measurement method according to the oscillometric method. For example, when a decrease measurement method is adopted in which a pulse wave is detected when the fluid bag 22 is decreased in pressure, the blood pressure measurement unit 210 calculates a systolic blood pressure based on the cuff pressure when the amplitude of the pulse wave signal suddenly increases (at the rising edge) and a diastolic blood pressure based on the cuff pressure when the amplitude suddenly decreases (at the falling edge). The blood pressure measurement unit 210 may also adopt a so-called increase measurement method in which a pulse wave is detected when the fluid bag 22 is increased in pressure.

[0048] The pulse wave number measuring unit 220 measures the pulse wave number N of the user based on a pulse wave signal obtained when blood pressure is measured by the blood pressure measuring unit 210. Specifically, the pulse wave number measuring unit 220 measures the pulse wave number N based on a pulse wave signal during the process of increasing the cuff pressure when blood pressure measurement is performed by the pressurization measurement method. The pulse wave number measuring unit 220 measures the pulse wave number N based on a pulse wave signal during the process of decreasing the cuff pressure when blood pressure measurement is performed by the pressurization measurement method.

[0049] The interval calculation unit 230 calculates a data set of the pulse wave interval based on the pulse wave signal. Specifically, when blood pressure measurement is performed using the pressurization measurement method, the interval calculation unit 230 calculates a data set of the pulse wave interval indicated by the pulse wave signal based on the pulse wave signal during the process of pressurizing the cuff pressure. When blood pressure measurement is performed using the depressurization measurement method, the interval calculation unit 230 calculates a data set of the pulse wave interval indicated by the pulse wave signal based on the pulse wave signal during the process of depressurizing the cuff pressure. For example, when the pulse wave signal Pa in FIG. 1 is obtained, the data set of the pulse wave interval is pulse wave intervals ta1 to ta5.

[0050] The clustering unit 240 uses the threshold value Th to cluster the data group of pulse wave intervals into one or more clusters. Specifically, the clustering unit 240 sorts the data group of pulse wave intervals in ascending or descending order, and compares the difference between each data (pulse wave interval) and the threshold value Th to cluster the data group of pulse wave intervals and generate one or more clusters.

[0051] The clustering unit 240 also sets the threshold value Th based on the pulse wave number N. Specifically, the clustering unit 240 increases the threshold value Th as the pulse wave number N decreases. However, the threshold value Th is set to be equal to or less than the average value of the data group of pulse wave intervals. The clustering method for the data group of pulse wave intervals will be described in detail later.

[0052] The determination unit 250 receives input of cluster information from the clustering unit 240. The cluster information includes the number of clusters, information indicating a data group belonging to each cluster, etc. The determination unit 250 calculates a dispersion index value of a data group belonging to a cluster based on the cluster information, and determines whether or not atrial fibrillation has occurred in the user based on the dispersion index value.

[0053] In one aspect, when a data group of pulse wave intervals is clustered into one cluster, the determination unit 250 determines that atrial fibrillation has occurred in the user if the variability index value of the data group belonging to the one cluster is equal to or greater than a predetermined value.

[0054] When the number of clusters is one, the standard deviation, variance, mean absolute deviation, or median absolute deviation is used as the variation index value. Specifically, the determination unit 250 calculates the standard deviation, variance, mean absolute deviation, or median absolute deviation of the data group belonging to the one cluster as the variation index value.

[0055] In another aspect, when the pulse wave interval data group is clustered into a plurality of clusters, the determination unit 250 determines that the user has atrial fibrillation if the variation index value of the data group belonging to the plurality of clusters is equal to or greater than a predetermined value. Furthermore, the determination unit 250 determines that the user has an arrhythmia other than atrial fibrillation if the variation index value is less than the predetermined value.

[0056] When there are multiple clusters, any one of Cstd, "Clustered Variance (for convenience, also referred to as "CVar")", "Clustered Absolute Deviation (for convenience, also referred to as "CAD")", the average of standard deviations, the average of variances, the average of mean absolute deviations, and the average of median absolute deviations is used as the variation index value for a data group belonging to multiple clusters. Specifically, the determination unit 250 calculates any one of Cstd, CVar, CAD, the average of standard deviations, the average of variances, the average of mean absolute deviations, and the average of median absolute deviations as the variation index value for a data group belonging to multiple clusters.

[0057] It is assumed that Cstd is used as the variation index value. In this case, the determination unit 250 calculates the sum of squared deviations of the data groups belonging to each cluster, and calculates Cstd as the square root of the sum of the squared deviations divided by the total number of pulse wave interval data. 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 a cluster is x av Let the number of data in the data group be n, and the data value included in the data group be x i (where i = 1 to n), the sum of squared deviations of the data group is S k (where k = 1 to m). In this case, Cstd is calculated using the following formulas (1) and (2).

[0058]

number

[0059] Assume that CVar is used as the variation index value. In this case, the determination unit 250 calculates the sum of squared deviations of the data groups belonging to each cluster, and divides the sum of the squared deviations by the total number of data of the pulse wave intervals to calculate Cvar. More specifically, Cvar is calculated using formula (1) and the following formula (3).

[0060]

number

[0061] Assume that CAD is used as the variation index value. In this case, the determination unit 250 calculates the sum of absolute deviations of the data groups belonging to each cluster, and calculates the CAD by dividing the sum of the absolute deviations by the total number of data of the pulse wave intervals. More specifically, the sum of absolute deviations of the data groups in the cluster is expressed as T k (where k = 1 to m), the CAD is calculated using the following formulas (4) and (5). Note that other variables (e.g., x av etc.) are the same as the variables used in equation (1).

[0062]

number

[0063] 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 used as the variation 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 sum of each standard deviation by the number of clusters m as the "average value of 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 sum of each variance by the number of clusters m as the "average value of variance."

[0064] The determination unit 250 calculates the mean absolute deviation (the sum of absolute deviations divided by the number of data n) of the data groups belonging to each cluster, and calculates the sum of the mean absolute deviations by the number of clusters m as the "average of mean absolute deviations." The determination unit 250 calculates the median absolute deviation of the data groups belonging to each cluster, and calculates the sum of the median absolute deviations by the number of clusters m as the "average of median absolute deviations." Details of the atrial fibrillation determination method will be described later.

[0065] The output control unit 260 displays the measurement results (e.g., systolic blood pressure and diastolic blood pressure values) of the blood pressure measurement unit 210 and the determination results (e.g., the determination result of the presence or absence of atrial fibrillation) of the determination unit 250 on the display 50. The output control unit 260 may transmit the measurement results and the determination results to an external device via the communication interface 53, or may be configured to output the results as audio via a speaker (not shown).

[0066] (Clustering and atrial fibrillation determination) Fig. 4 is a diagram showing an example of a data group of pulse wave intervals. Specifically, Fig. 4(a) is an example of a data group of pulse wave intervals in a pulse wave signal indicating atrial fibrillation. Fig. 4(b) is an example of a data group of pulse wave intervals in a pulse wave signal indicating normal sinus rhythm. Fig. 4(c) is an example of a data group of pulse wave intervals in a pulse wave signal indicating premature contraction. The vertical axis of Fig. 4(a) to Fig. 4(c) shows the normalized value of the pulse wave interval, and the horizontal axis shows the order of the pulses that occurred.

[0067] 4 is a normalized value obtained by dividing each pulse interval included in the pulse interval data group by the average value of the pulse intervals. Therefore, when the pulse interval T is equal to the average value, the normalized value of the pulse interval T is "1".

[0068] 4(a), the pulse wave interval data group varies irregularly between approximately 0.6 and 1.5, which shows the same tendency as the pulse wave interval data groups ta1 to ta5 of pulse wave signal Pa in FIG.

[0069] 4(b), there is no variation in the data group of pulse wave intervals, with each piece of data lying around 1.0. This is a similar trend to the data groups tb1-tb5 of pulse wave intervals in pulse wave signal Pb in FIG.

[0070] 4(c), some of the data in the pulse wave interval data group varies. Specifically, most of the data is near 1.0, but some of the data (e.g., the 2nd, 3rd, 15th, 16th, 22nd, and 23rd data) have slightly different values. This is the same tendency as the data groups tc1 to tc5 of the pulse wave interval in the pulse wave signal Pc in FIG. 1.

[0071] The sphygmomanometer 100 (clustering unit 240) generates one or more clusters by clustering the data group of the pulse wave intervals shown in Fig. 4. First, the clustering method will be described with reference to Fig. 5.

[0072] Fig. 5 is a diagram for explaining the clustering method. With reference to Fig. 5, a situation is assumed in which data groups D1 to D15 are clustered. Data groups D1 to D15 are obtained by rearranging data groups of pulse wave intervals in a pulse wave signal in descending order. That is, data D1 is the largest and data D15 is the smallest.

[0073] Clustering is performed by comparing the difference between the data before and after each data with a threshold value Th. For example, the sphygmomanometer 100 (for example, the clustering unit 240) determines whether the difference between the data D1 and the data D2 following (adjacent to) the data D1 is equal to or greater than the threshold value Th. Since the difference is equal to or greater than the threshold value Th, the data D1 is classified into a different cluster from the data D2. In the example of FIG. 5, the data D1 belongs to the cluster C1.

[0074] Similarly, the clustering unit 240 classifies the data D2 and D3 into the same cluster because the difference between the data D2 and D3 is less than the threshold Th. Next, the clustering unit 240 classifies the data D3 into a different cluster from the data D4 because the difference between the data D3 and D4 is equal to or greater than the threshold Th. Therefore, in the example of FIG. 5, the data D2 and D3 belong to the cluster C2.

[0075] By repeating 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. In the example of Fig. 5, 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.

[0076] Fig. 6 is a diagram showing the clustering results. Specifically, it shows the results of clustering each of the data groups of pulse wave intervals shown in Figs. 4(a) to 4(c) using a threshold value Th. By the clustering method described in Fig. 5, the data group of pulse wave intervals related to atrial fibrillation shown in Fig. 4(a) is clustered into one cluster X1. The data group of pulse wave intervals related to normal sinus rhythm shown in Fig. 4(b) is clustered into one cluster Y1. The data group of pulse wave intervals related to premature contractions shown in Fig. 4(c) is clustered into three clusters Z1 to Z3.

[0077] A data group of pulse wave intervals related to atrial fibrillation is clustered into one cluster X1, and therefore, one of four index values ​​(i.e., standard deviation, variance, mean absolute deviation, and median absolute deviation) is used as the variation index value Sdx of the data group. As shown in FIG. 6, the data group belonging to cluster X1 has a large variation, and therefore, the variation index value Sdx of the data group is large. Similarly, a data group of pulse wave intervals related to normal sinus rhythm is clustered into one cluster Y1, and therefore, one of the above four index values ​​is used as the variation index value Sdy of the data group. However, it is assumed that the same type of index value is used for the variation index values ​​Sdx and Sdy. As shown in FIG. 6, the data group belonging to cluster Y1 has a small variation, and therefore, the variation index value Sdy of the data group is small.

[0078] The data group of pulse wave intervals corresponding to the extrasystoles is clustered into three clusters Z1 to Z3, and the variation index value Sdz of the data group is one of Cstd, CVar, CAD, the average of standard deviations, the average of variances, the average of mean absolute deviations, and the average of median absolute deviations. As shown in Fig. 6, the data group belonging to each of the clusters Z1 to Z3 has a small variation. Therefore, the variation index value Sdz of the data group of pulse wave intervals corresponding to the extrasystoles is small.

[0079] For this reason, when atrial fibrillation occurs, the variation index value calculated by the above method becomes large. Therefore, the sphygmomanometer 100 (determination unit 250) calculates the variation index value of the data group belonging to the clustered cluster, and when the variation index value is larger than a predetermined value, determines that atrial fibrillation has occurred.

[0080] When the data group of pulse wave intervals is clustered into multiple clusters, the sphygmomanometer 100 (determination unit 250) determines that atrial fibrillation has occurred when the dispersion index value of the data group belonging to multiple clusters is equal to or greater than a predetermined value. This is because, although multiple clusters are generated, the dispersion of the data group belonging to each cluster is large, and the data group of pulse wave intervals is considered to be irregularly dispersed overall (i.e., the dispersion index value is large).

[0081] On the other hand, when the dispersion index values ​​of the data groups belonging to a plurality of clusters are less than the predetermined value, the sphygmomanometer 100 (determination unit 250) determines that an arrhythmia other than atrial fibrillation (eg, premature contraction) has occurred.

[0082] Furthermore, when the data group of pulse wave intervals is clustered into one cluster and the variation index value of the data group belonging to the cluster is less than a predetermined value, the sphygmomanometer 100 (determination unit 250) may determine that the user's pulse is normal (e.g., exhibits normal sinus rhythm).

[0083] In order to appropriately determine the presence or absence of atrial fibrillation as described above, it is necessary to perform clustering using an appropriate threshold value Th. A method for setting the threshold value Th will be described below.

[0084] Fig. 7 is a diagram for explaining a method for setting a threshold value. Fig. 7(a) and Fig. 7(b) each show a result of clustering a group of pulse wave interval data related to atrial fibrillation using a threshold value Th. However, Fig. 7(a) shows a clustering result when the pulse wave number is high, and Fig. 7(b) shows a clustering result when the pulse wave number is low.

[0085] In Fig. 7(a), one cluster Ca is generated, and the data group of pulse wave intervals belonging to cluster Ca varies widely, so the variation index value (e.g., standard deviation, variance, mean absolute deviation, or median absolute deviation) of the data group is large, and therefore it is correctly determined that atrial fibrillation has occurred.

[0086] On the other hand, in Fig. 7(b), three clusters Cb1 to Cb3 are generated, and the variation of the data groups of pulse wave intervals belonging to each of the clusters Cb1 to Cb3 is small. Therefore, the variation index values ​​(e.g., Cstd, CVar, CAD, average standard deviation, average variance, average mean absolute deviation, or average median absolute deviation) of the data groups in the multiple clusters Cb1 to Cb3 are also small. As a result, it is erroneously determined that an arrhythmia other than atrial fibrillation has occurred.

[0087] In order to prevent the above-mentioned erroneous determination, the sphygmomanometer 100 (clustering unit 240) changes the threshold value Th according to the pulse wave number. Specifically, the clustering unit 240 increases the threshold value Th as the pulse wave number decreases. With this configuration, as shown in FIG. 7(b), when the pulse wave number is low, the threshold value Th increases, so the clustering unit 240 generates one cluster Cb instead of generating three clusters Cb1 to Cb3. The data group of pulse wave intervals belonging to cluster Cb varies greatly, so the variation index value of the data group increases. As a result, it is correctly determined that atrial fibrillation has occurred.

[0088] Using FIG. 8, the upper limit of the threshold value Th can be considered as follows.

[0089] FIG. 8 is a diagram for explaining the upper limit of the threshold. Referring to FIG. 8, an example is shown in which one pulse is missing in the pulse wave signal Pd. As described above, if the pulse wave interval is the same as the average value of the data group of pulse wave intervals, the normalized value of the pulse wave interval is "1". In the example of FIG. 8, the pulse wave intervals Ta and Tc are "1". Next, when one pulse is missed, 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 coincides with the average value of the data group of pulse wave intervals.

[0090] The phenomenon of missing a pulse is often seen in arrhythmias other than atrial fibrillation (for example, premature ventricular contractions). Therefore, if the threshold Th is set to "1" or more, the data group related to the premature ventricular contractions may be clustered into a single cluster rather than multiple clusters. In this case, arrhythmias other than atrial fibrillation may be erroneously determined to be "atrial fibrillation". Therefore, the upper limit of the threshold Th is set to the average value of the data group of pulse wave intervals.

[0091] (Processing Procedure) Fig. 9 is a flowchart for explaining a process procedure executed by blood pressure monitor 100. With reference to Fig. 9, at the start of this process, cuff 20 is attached to a measurement site of the user.

[0092] 9, processor 110 of sphygmomanometer 100 receives an operation signal based on a user operation of measurement switch 52A from operation unit 52 (step S10). Processor 110 starts a blood pressure measurement process (step S20) in response to the operation signal. In the blood pressure measurement process, a data set of a blood pressure value, a pulse wave number N, and a pulse wave interval is calculated based on the pulse wave signal. The blood pressure measurement process will be described in detail later.

[0093] The processor 110 executes an atrial fibrillation determination process based on the data group of the pulse wave rate N and the pulse wave interval (step S30). Specifically, the processor 110 sets a threshold Th used for clustering based on the pulse wave rate N, and clusters the data group of the pulse wave interval into one or more clusters using the threshold Th. Then, the processor 110 determines whether or not atrial fibrillation has occurred based on the dispersion index value of the data group belonging to the cluster.

[0094] The processor 110 displays the blood pressure measurement results (eg, systolic blood pressure and diastolic blood pressure) and the results of the atrial fibrillation determination process on the display 50 (step S40).

[0095] Fig. 10 is a flowchart showing an example of a blood pressure measurement process of the sphygmomanometer 100. The blood pressure measurement process shown in Fig. 10 (corresponding to step S20 in Fig. 9) is a process for measuring blood pressure by a pressurization measurement method.

[0096] 10, the processor 110 of the sphygmomanometer 100 initializes the pressure sensor 31 (step S102). Specifically, the processor 110 initializes the processing memory area, turns off (stops) the pump 32, and adjusts the pressure sensor 31 to 0 mmHg (sets the atmospheric pressure to 0 mmHg) with the valve 33 open.

[0097] Next, the processor 110 closes the valve 33 via the valve drive circuit 330 (step S104), and turns on the pump 32 via the pump drive circuit 320 to start pressurizing 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 inside 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. This starts the pressurization process.

[0098] 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 diastolic blood pressure based on the pulse wave signal, and determines whether the blood pressure calculation is complete (step S108).

[0099] If the blood pressure calculation cannot be completed due to insufficient data (NO in step S108), the processor 110 repeats the processes of steps S106 and S108 unless the cuff pressure reaches a predetermined upper limit pressure (e.g., 300 mmHg). If the blood pressure calculation is completed (YES in step S108), the processor 110 stops the pump 32 (i.e., stops the pressurization process) (step S110) and opens the valve 33 (step S112), thereby performing control to exhaust the air in the cuff 20.

[0100] 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 pressurization process (step S114). Processor 110 stores the calculated data set of the pulse wave number N and the pulse wave interval in memory 51.

[0101] Fig. 11 is a flowchart showing another example of the blood pressure measurement process of the sphygmomanometer 100. The blood pressure measurement process shown in Fig. 11 (corresponding to step S20 in Fig. 9) is a process for measuring blood pressure by a reduced pressure measurement method.

[0102] 11, the processes in steps S122 to S126 are similar to those in steps S102 to S106 in FIG. 10, respectively, and therefore will not be described in detail.

[0103] Processor 110 estimates the systolic blood pressure based on the pulse wave signal obtained during inflation (step S128). Processor 110 determines whether the cuff pressure reaches or exceeds pressure P (step S130). Typically, pressure P is set to a value that is a fixed value (e.g., 40 mmHg) higher than the estimated systolic blood pressure value.

[0104] If the cuff pressure is less than pressure P (NO in step S130), the processor 110 returns to step S126. If the cuff pressure is equal to or greater than pressure P (YES in step S130), the processor 110 stops the pump 32 (step S132) and controls the valve 33 to gradually open (step S134). This causes a transition from the pressurization process to the depressurization process (i.e., the depressurization process starts), and the cuff pressure is gradually depressurized.

[0105] During this decompression process, processor 110 extracts a pulse wave signal from the cuff pressure signal detected by pressure sensor 31, attempts to calculate systolic and diastolic blood pressures based on the pulse wave signal, and determines whether blood pressure calculation is complete (step S136). If blood pressure calculation is not complete (NO in step S136), processor 110 repeats the processes of steps S134 and S136. If blood pressure calculation is complete (YES in step S136), processor 110 fully opens valve 33 (step S138) to perform control to rapidly exhaust air from within cuff 20.

[0106] Processor 110 calculates a data set of pulse wave number N and pulse wave interval based on the pulse wave signal obtained during the depressurization process (step S140). Processor 110 stores the calculated data set of pulse wave number N and pulse wave interval in memory 51.

[0107] <Other embodiments> (1) In the above-described embodiment, a program for causing a computer to function and execute the control as described in the above-described flowchart can also be provided. Such a program can be provided as a program product by being recorded on a non-transitory computer-readable recording medium such as a flexible disk, a CD-ROM (Compact Disk Read Only Memory), a secondary storage device, a main storage device, or a memory card that is attached to the computer. Alternatively, the program can be provided by being recorded on a recording medium such as a hard disk built into the computer. The program can also be provided by downloading via a network.

[0108] (2) The configurations exemplified as the above-mentioned embodiments are merely examples of the configurations of the present invention, and may be combined with other known technologies, or may be modified, such as by omitting some parts, without departing from the scope of the present invention. In addition, the above-mentioned embodiments may be implemented by appropriately adopting the processes and configurations described in other embodiments.

[0109] [Note] As described above, the present embodiment includes the following disclosure.

[0110] [Configuration 1] A blood pressure monitor (100) comprising: a blood pressure measurement unit (210) that measures the blood pressure of a user based on a pulse wave signal superimposed on a cuff pressure signal detected during a process of increasing or decreasing a cuff pressure indicating an internal pressure of a cuff (20) attached to a measurement site of the user; a pulse wave number measurement unit (220) that measures the pulse wave number of the user based on the pulse wave signal; an interval calculation unit (230) that calculates a data group of pulse wave intervals based on the pulse wave signal; a clustering unit (240) that clusters the data group of pulse wave intervals into one or more clusters using a threshold value; and a determination unit (250) that determines whether atrial fibrillation has occurred in the user based on an index value indicating a magnitude of variation in the data group belonging to the cluster, wherein the clustering unit sets the threshold value based on the pulse wave number.

[0111] [Configuration 2] The blood pressure monitor (100) according to configuration 1, wherein the clustering unit (240) sets the threshold value to a larger value as the pulse wave number decreases.

[0112] [Configuration 3] The blood pressure monitor (100) according to configuration 1 or 2, wherein the threshold value is set to be equal to or lower than an average value of a group of data on the pulse wave interval.

[0113] [Configuration 4] The blood pressure monitor (100) according to any one of configurations 1 to 3, wherein when the pulse wave interval data group is clustered into one cluster, the determination unit (250) determines that atrial fibrillation has occurred in the user if a first index value indicating the magnitude of variation in the data group belonging to the one cluster is equal to or greater than a predetermined value.

[0114] [Configuration 5] The blood pressure monitor (100) according to any one of configurations 1 to 4, wherein when the pulse wave interval data group is clustered into a plurality of clusters, the determination unit (250) determines that atrial fibrillation has occurred in the user if a second index value indicating the magnitude of variation in the data groups belonging to the plurality of clusters is equal to or greater than a predetermined value.

[0115] [Configuration 6] The blood pressure monitor according to configuration 5, wherein the determination unit determines that the user has developed arrhythmia other than atrial fibrillation when the second index value is less than the predetermined value.

[0116] The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present invention is defined by the claims, not the above description, and is intended to include all modifications within the scope and meaning equivalent to the claims. [Explanation of symbols]

[0117] 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 rate 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 blood pressure measurement unit that measures the blood pressure of the user based on a pulse wave signal superimposed on a cuff pressure signal detected during a process of increasing or decreasing a cuff pressure indicating an internal pressure of a cuff attached to a measurement site of the user; a pulse wave rate measuring unit that measures the pulse wave rate of the user based on the pulse wave signal; an interval calculation unit that calculates a data group of pulse wave intervals based on the pulse wave signal; a clustering unit that clusters the group of pulse wave interval data into one or more clusters using a threshold value; a determination unit that determines whether atrial fibrillation has occurred in the user based on an index value that indicates a magnitude of variation in a data group that belongs to the cluster, the clustering unit sets the threshold value based on the pulse wave rate; When the pulse wave interval data group is clustered into a plurality of clusters, the determination unit determines that atrial fibrillation has occurred in the user if a second index value indicating the magnitude of variation in the data groups belonging to the plurality of clusters is equal to or greater than a predetermined value.

2. The blood pressure monitor according to claim 1 , wherein the clustering unit increases the threshold value as the pulse wave number decreases.

3. The blood pressure monitor according to claim 1 , wherein the threshold value is set to be equal to or less than an average value of the group of pulse wave interval data.

4. 3. The blood pressure monitor according to claim 1, wherein when the pulse wave interval data group is clustered into one cluster, the determination unit determines that atrial fibrillation has occurred in the user if a first index value indicating a magnitude of variation in the data group belonging to the one cluster is equal to or greater than a predetermined value.

5. The blood pressure monitor according to claim 1 , wherein the determination unit determines that the user has developed arrhythmia other than atrial fibrillation when the second index value is less than the predetermined value.

6. A blood pressure measurement unit that measures the blood pressure of the user based on a pulse wave signal superimposed on a cuff pressure signal detected during the process of increasing or decreasing cuff pressure, which indicates the internal pressure of a cuff attached to a measurement site of the user; and a pulse wave rate measuring unit that measures the pulse wave rate of the user based on the pulse wave signal; an interval calculation unit that calculates a data group of pulse wave intervals based on the pulse wave signal; a clustering unit that sorts the group of pulse interval data in ascending or descending order and compares the difference between two adjacent pulse intervals in the sorted group of pulse interval data with a threshold, thereby clustering the group of pulse interval data into one or more clusters; a determination unit that determines whether atrial fibrillation has occurred in the user based on an index value that indicates a magnitude of variation in a data group that belongs to the cluster, The clustering unit sets the threshold value based on the pulse wave rate.

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