Monitoring device, monitoring method, and program

Abstract

To early detect a sign of hypotension.SOLUTION: In a monitoring method, a computer executes acquiring pulse wave data of a patient measured by a wearable device, calculating an estimate value of a heart rate and an estimate value of a blood pressure on the basis of acquired pulse wave data, and detecting a decrease in the blood pressure generated after an increase in the heart rate on the basis of the calculated estimate value of the heart rate and the calculated estimate value of the blood pressure.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a monitoring device, a monitoring method, and a program.

Background Art

[0002] In hemodialysis patients, blood pressure may fluctuate due to effects such as ultrafiltration during the dialysis operation. Conventionally, during dialysis, in addition to regularly monitoring blood pressure, blood pressure has been measured and hypotension has been confirmed when the patient's complaints and variations are confirmed.

[0003] Also, a blood pressure monitoring device has been proposed that includes a pulse wave detection unit that detects a subject's pulse wave based on a sensing signal of a reflective optical sensor, and a blood pressure decrease detection unit that detects, based on a change in the pulse wave signal detected by the pulse wave detection unit, a rapid blood pressure decrease caused by a rise in heart rate due to abnormal return of blood to the body during the blood circulation process and a gradual blood pressure decrease associated with peripheral vasodilation by the temporal change of the pulse wave (Patent Document 1).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in time-series monitoring, it is impossible to predict whether the blood pressure will stabilize in the future or whether hypotension will occur and the blood pressure will change suddenly. Therefore, an object of the present technology is to provide a technique for early detection of precursors of hypotension.

Means for Solving the Problems

[0006] In order to solve the above problems, the following means are employed. Acquiring the patient's pulse wave data measured by a wearable device, calculating an estimated heart rate and an estimated blood pressure based on the acquired pulse wave data; Detecting a decrease in blood pressure that occurs after an increase in heart rate based on the calculated estimated heart rate and estimated blood pressure; A monitoring device comprising a processor that executes the above. [Effects of the Invention]

[0007] The disclosed technology can provide a technology for early detection of signs of hypotension. [Brief explanation of the drawings]

[0008]

Figure 1

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Figure 5

[0009] Hereinafter, embodiments will be described with reference to the drawings. The configurations of the embodiments are examples, and the configurations of the invention are not limited to the specific configurations of the disclosed embodiments. A specific configuration may be appropriately adopted depending on the situation.

[0010] [Embodiment] FIG. 1 is a diagram showing an example of a system configuration. The system 10 in FIG. 1 is a system for remotely monitoring vital data of a patient, and includes a monitoring device 1, a wearable device (WD) 2, a patient terminal 3, and a monitor terminal 4. These components are The elements are communicatively connected via a network 5 .

[0011] The monitoring device 1 is a computer that predicts the heart rate and blood pressure based on the patient's pulse wave measured by the WD 2. If an acute drop in blood pressure is predicted, the monitoring device 1 notifies at least the monitor terminal 4. It is preferable that the notification is also sent to the patient terminal 3.

[0012] The WD2 is, for example, a smart watch or smart band worn by a patient undergoing dialysis, and measures the patient's pulse wave and transmits the pulse wave data to another device. The pulse wave data is a signal output by a pulse wave sensor that indicates changes in the pulse wave over time. Note that the device may be worn somewhere other than on the arm, such as a headband, as long as it can measure the pulse wave. In this embodiment, the WD2 wirelessly communicates with the patient terminal 3 using a communication method such as Bluetooth (registered trademark), and transmits the pulse wave data to the patient terminal 3.

[0013] The patient terminal 3 is a computer such as a smartphone carried by the patient, and transmits pulse wave data to the monitoring device 1 via the network 5. The WD 2 may also transmit pulse wave data directly to the monitoring device 1 via the network 5.

[0014] The monitor terminal 4 is a computer such as a smartphone carried by a medical professional such as a doctor or nurse, and receives a notification from the monitoring device 1 regarding a drop in the patient's blood pressure.

[0015] The network 5 includes, for example, an IP (Internet Protocol) network. Devices connected to the network 5 can communicate based on a predetermined communication protocol. Part of the network 5 may be a telephone network (fixed telephone network or mobile communication network), an ad hoc network, an intranet, a VPN (Virtual Private Network), a LA N (Local Area Network), Wireless LAN, WAN (Wide Area Network) ) It may also be the Internet.

[0016] In addition, in FIG. 1, one WD2, one patient terminal 3, and one monitor terminal 4 are shown respectively. However, the system 10 may include a plurality of at least any one of WD2, the patient terminal 3, and the monitor terminal 4. When a plurality of WD2 are included, the monitoring device 1 identifies the WD2 based on the identification information and performs predictions such as blood pressure for each patient wearing the WD2. When a plurality of monitor terminals 4 are included, the monitoring device 1 notifies the appropriate monitor terminal 4 according to the patient in charge of the user of the monitor terminal 4, the time zone where the user works, etc.

[0017] FIG. 2 is a diagram showing an example of the device configuration. The monitoring device 1 is a computer such as a server. The monitoring device 1 includes a processor 11, a storage device 12, and a communication interface (IF) 13. The processor 11 is an arithmetic processing device such as a CPU (Central Processing Unit), and performs each process according to the present embodiment by executing a program. The storage device 12 is, for example, a main storage device such as a RAM (Random Access Memory) or a ROM (Read Only Memory), and an auxiliary storage device (secondary storage device) such as an HDD (Hard-disk Drive), an SSD (Solid State Drive), or a flash memory. The main storage device temporarily stores the program read by the processor or secures the working area of the processor. The auxiliary storage device stores the program executed by the processor and the data transmitted and received between other devices. The communication IF 13 is, for example, a network adapter or a communication module that communicates by wire or wirelessly and performs data communication based on a predetermined protocol.

[0018] WD2 is a computer such as a smartwatch or a smartband. WD2 includes a processor 21, a storage device 22, a communication interface (IF) 23, and a pulse wave sensor 24. The processor 21, the storage device 22, and the communication IF 23 are generally similar to the processor 11, the storage device 12, and the communication IF 13, respectively. In this embodiment, the communication IF 23 is a communication module for performing ad-hoc communication with the patient terminal 3.

[0019] The pulse wave sensor 24 is, for example, an optical pulse wave sensor and outputs pulse wave data. When the patient wears and uses the pulse wave sensor 24, a reflection type pulse wave sensor is preferred. The reflection type pulse wave sensor includes, for example, a light emitting element such as an LED (Light Emitting Diode), and a light receiving element such as a photodiode or a phototransistor, and measures the reflected light in the living body. In the living body, the blood flow volume in the artery changes with the pulsation of the heart, and the amount of light absorption by hemoglobin in the blood changes, so that a pulse wave can be obtained from the reflected light. The pulse wave data is temporarily held in the storage device 22, for example. Further, the processor 21 transmits the pulse wave data held in the storage device 22 to the patient terminal 3 via the communication IF 23.

[0020] The patient terminal 3 is a computer such as a smartphone. The patient terminal 3 includes a processor 31, a storage device 32, a communication interface (IF) 33, and a user interface (UI) 34. The processor 31, the storage device 32, and the communication IF 33 are generally similar to the processor 11, the storage device 12, and the communication IF 13, respectively. In this embodiment, the communication IF 33 includes a communication module for performing ad-hoc communication with WD2 and a network adapter for communicating with the monitoring device 1 via the network 5. The UI 34 is, for example, a liquid crystal display provided with a touch panel and may include a speaker.

[0021] When the processor 31 receives the pulse wave data via the communication IF 33, it temporarily stores the data in the storage device 32, for example. The processor 31 also transmits the pulse wave data stored in the storage device 32 to the monitoring device 1 via the communication IF 33 and the network 5. When the monitoring device 1 notifies the corresponding patient that it has predicted an acute drop in blood pressure, the processor 31 of the patient terminal 3 receives the notification from the monitoring device 1 via the communication IF 33 and outputs information to the UI 34.

[0022] The monitor terminal 4 is also a computer such as a smartphone. The configuration of the monitor terminal 4 is generally the same as that of the patient terminal 3, and includes a processor 41, a storage device 42, a communication interface (IF) 43, and a user interface (UI) 44. In this embodiment, the communication IF 43 is a network adapter for communicating with the monitoring device 1 via the network 5. The UI 34 is, for example, a liquid crystal display equipped with a touch panel and may include a speaker. When the monitoring device 1 predicts an acute drop in blood pressure, the processor 41 of the monitor terminal 4 receives the notification from the monitoring device 1 via the communication IF 43 and outputs information to the UI 44.

[0023] FIG. 3 is a process flow diagram showing an example of the processing executed by the system. For example, a dialysis patient wears the WD2 during dialysis to measure the pulse wave.

[0024] The pulse wave sensor 24 of the WD2 measures the patient's pulse wave and outputs pulse wave data (FIG. 3: S1). FIG. 4 is a diagram for explaining the estimation of blood pressure according to the embodiment. FIG. 4(A) is a graph showing an example of a pulse wave. In the graph of FIG. 4(A), the vertical axis represents the amplitude and the horizontal axis represents the passage of time. In S1, the pulse wave sensor 24 measures a pulse wave as shown in FIG. 4(A) and outputs the pulse wave data (PPG (Photoplethysmogram) signal) after A / D conversion. The process of S1 is continuously performed at a predetermined sampling period.

[0025] In addition, the processor 21 of WD2 transmits the pulse wave data measured by the pulse wave sensor 24 via the communication IF23 (Fig. 3: S2). The pulse wave data is transmitted to the monitoring device 1 via, for example, the patient terminal 3 and the network 5. However, in Fig. 3, the patient terminal 3 and the network 5 are omitted. In S2, for example, the pulse wave data output by the pulse wave sensor 24 within a predetermined period is transmitted collectively. Also, after S2, the process returns to S1 and the processor 21 repeats the process.

[0026] On the other hand, the processor 11 of the monitoring device 1 receives the pulse wave data via the communication IF13 and stores it in the storage device 12 (Fig. 3: S3). Also, the processor 11 calculates the moving average of the heart rate (Fig. 3: S4). In this step, preprocessing is performed on the pulse wave data to remove noise, and the moving average of the heart rate in the most recent predetermined period is calculated.

[0027] Fig. 4(B) is a graph showing an example of the smoothed pulse wave data. The raw PPG signal includes noise due to motion artifacts and the like. Therefore, smoothing is performed on the PPG signal by band-pass filter processing, automatic gain control, impulse response processing, etc., to obtain pulse wave data with noise removed. Note that at least a part of these preprocessings may be performed by WD2. In Fig. 4(B), the minimum value S with a low value is the starting point of the arterial fluctuation wave (aortic valve opening point). The maximum value P with a high value is the maximum left ventricular ejection point (systolic peak). The minimum value C with a high value is the notch part at the end of the systolic phase. Note that a tidal wave may be mixed in. The small maximum value D is the dicrotic wave (a frequency vibration wave generated from the blood applied to the aortic valve by the aortic blood pressure, diastolic peak). In S3, for example, based on the interval at which the maximum value P appears, the most recent heart rate can be estimated.

[0028] Also, the processor 11 estimates the blood pressure from the pulse wave data and calculates the moving average of the blood pressure (Fig. 3: S5). The systolic blood pressure (SBP) and the diastolic blood pressure (DBP) are, for example, based on the smoothed pulse wave data shown in Fig. 4(B). In this case, the diastolic time (Figure 4(B): DT) and the pulse transit time (the time delay from the systolic peak to the diastolic peak (Figure 4(B): T1)) can be detected and estimated using a regression equation created in advance by linear regression. Note that these time parameters decrease as blood pressure rises. Also, DT has a high correlation with systolic blood pressure, and T1 has a high correlation with diastolic blood pressure.

[0029] In S5, the moving averages of blood pressure in two periods with different lengths are calculated. That is, the moving average of blood pressure is calculated for a relatively long first period and a second period shorter than the first period.

[0030] Also, the processor 11 determines whether a downward trend in blood pressure has occurred after the heart rate has increased (Figure 3: S6). In this step, the processor 11 determines, for example, whether a downward trend in blood pressure has occurred within a predetermined period after the moving average of the heart rate has risen above a predetermined heart rate threshold. The downward trend in blood pressure is detected based on the difference between the two moving averages calculated in S5. That is, when the moving average of blood pressure in the second period is smaller than the moving average of blood pressure in the first period by a value greater than or equal to a predetermined blood pressure threshold, the processor 11 determines that a downward trend in blood pressure has occurred.

[0031] Figure 5 is a diagram showing an example of fluctuations in heart rate and blood pressure. The graph in Figure 5(A) has the heart rate or blood pressure on the vertical axis and the elapsed time on the horizontal axis. Also, the thick solid line is the heart rate, the thick dashed line is the SBP, the thin dashed line is the DBP, and the thin solid line is the mean blood pressure (MBP). The graph in Figure 5(A) represents the heart rate and blood pressure estimated from the pulse wave data.

[0032] In S6, a determination is made based on the moving average of blood pressure in the first period and the moving average of blood pressure in the second period. In the graph of FIG. 5(B), the vertical axis represents the moving average of blood pressure, and the horizontal axis represents the elapsed time. Also, MA1 is the moving average of blood pressure in a relatively long first period. MA2 is the moving average of blood pressure in a second period shorter than the first period. For example, the first period is 60 minutes and the second period is 15 minutes, but it is not limited to this example. When the decrease in blood pressure starts, the most recent short-term moving average starts to decrease earlier than the most recent long-term moving average. In FIG. 5(B), the broken line indicating MA2 changes so as to cross downward with respect to the broken line indicating MA1. In the present embodiment, by comparing the moving average of blood pressure in the first period with the moving average of blood pressure in the second period, it is possible to detect an early tendency of future blood pressure decrease.

[0033] Also, by detecting a decrease in blood pressure that occurs after an increase in heart rate, the detection accuracy of hypotension can be improved. Generally, when a decrease in blood pressure due to hypotension occurs, first the heart rate increases to compensate for this, and then a rapid decrease in blood pressure appears when it cannot be compensated for. In S6, by detecting that a tendency for a decrease in blood pressure has occurred after an increase in heart rate, it is possible to detect a precursor of hypotension accurately at an early stage. For example, in FIG. 5(B), a precursor of a rapid decrease in blood pressure occurring in the portion indicated by the ellipse can be detected at the time indicated by the arrow.

[0034] In S6, when it is determined that a tendency for a decrease in blood pressure has occurred after an increase in heart rate (S6: YES), the processor 11 notifies another device of a blood pressure decrease warning via the communication IF13 (FIG. 3: S7). The notification is performed, for example, to the monitor terminal 4. Also, the notification may be further performed to the patient terminal 3.

[0035] In S6, when it is determined that a tendency for a decrease in blood pressure has not occurred after an increase in heart rate (S6: NO), or after S7, the process returns to S3 and the processor 11 repeats the process. The monitoring process as described above is continuously performed for a predetermined period, for example, during the dialysis of a patient.

[0036] Note that the process flow diagram in FIG. 3 is schematic, and the transmission of the heart rate from WD1 in S2, the calculation of the heart rate in S4, the calculation of the blood pressure in S5, and the determination in S6 may be repeatedly executed at different frequencies. Also, within the scope not departing from the gist of the present disclosure, the order may be changed or executed in parallel.

[0037] (Effect of the Embodiment) According to the comparison of the moving average in S6, it is possible to detect a downward trend in blood pressure based on the estimated blood pressure value, enabling early warning. Also, since a highly accurate determination can be made early, it is beneficial for realizing telemedicine and reducing the burden on medical staff.

[0038] Also, in S7, if a notification is also sent to the patient terminal 3, the patient can grasp their own condition from the change in their physical condition, leading to an improvement in the quality of medical care. That is, generally, even if a patient feels some subjective symptoms but does not understand the relationship with their own risk, by sharing the detected information with the patient as well, the patient can also learn the relationship between the subjective symptoms, pulse, blood pressure, and their own risk.

[0039] (Others)[[ID=IS]] The embodiments have been described above, but the present disclosure is not limited to these, and various changes based on the knowledge of those skilled in the art are possible as long as they do not depart from the gist of the claims. For example, at least a part of the functions of the monitoring device 1 may be realized by being distributed among a plurality of devices, or a plurality of devices may provide the same function in parallel.

[0040] Also, the present technology includes a method or computer program for executing the above-described processing, and a computer-readable recording medium on which the program is recorded. By causing a computer to execute the program recorded on the recording medium, the above-described processing becomes possible.

[0041] Here, a computer-readable recording medium refers to a recording medium that accumulates information such as data and programs by electrical, magnetic, optical, mechanical, or chemical actions and can be read by a computer. Examples of removable recording media of this kind from a computer include flexible disks, magneto-optical disks, optical disks, magnetic tapes, memory cards, etc. Also, examples of recording media fixed to a computer include HDDs, SSDs, ROMs, etc.

Explanation of Symbols

[0042] 10: System 1: Monitoring device, 11: Processor, 12: Storage device, 13: Communication interface 2: Wearable device (WD), 21: Processor, 22: Storage device, 23: Communication interface (IF), 24: Pulse sensor 3: Patient terminal, 31: Processor, 32: Storage device, 33: Communication interface (IF), 34: User interface (UI) 4: Monitor terminal, 41: Processor, 42: Storage device, 43: Communication interface (IF), 44: User interface (UI) 5: Network

Claims

1. Obtaining the patient's pulse wave data measured by a wearable device; Calculating an estimated heart rate value and an estimated blood pressure value based on the obtained pulse wave data; Detecting a decrease in blood pressure that occurs after an increase in heart rate based on the calculated estimated heart rate value and estimated blood pressure value; A monitoring device comprising a processor that executes the above.

2. The processor detects a decrease in blood pressure that occurs after an increase in heart rate using a moving average of the estimated heart rate value and a moving average of the estimated blood pressure value. The monitoring device according to Claim 1.

3. The processor determines that a decrease in blood pressure that occurs after an increase in heart rate is detected when, within a predetermined period after the moving average of the estimated heart rate value increases by a first threshold value or more, the moving average of the estimated blood pressure value in a most recent second period shorter than the first period is smaller by a second threshold value or more than the moving average of the estimated blood pressure value in the most recent first period. The monitoring device according to Claim 2.

4. When the processor detects a decrease in blood pressure that occurs after an increase in heart rate, it notifies a warning to the terminal possessed by the patient and the terminal possessed by medical staff. The monitoring device according to any one of Claims 1 to 3.

5. Obtaining the patient's pulse wave data measured by a wearable device; Calculating an estimated heart rate value and an estimated blood pressure value based on the obtained pulse wave data; Detecting a decrease in blood pressure that occurs after an increase in heart rate based on the calculated estimated heart rate value and estimated blood pressure value; A monitoring method executed by a computer.

6. Obtaining the patient's pulse wave data measured by a wearable device; Calculating an estimated heart rate value and an estimated blood pressure value based on the obtained pulse wave data; Detecting a decrease in blood pressure that occurs after an increase in heart rate based on the calculated estimated heart rate value and estimated blood pressure value; A program for causing a computer to execute the above.

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