Monitoring device, monitoring method, and program

Abstract

To enable appropriate notification of an abnormality of a person to be measured in consideration of a temporary body condition of the person to be measured, such as drinking or exercising.SOLUTION: A monitoring device 10 includes: a biological information acquisition unit 11 that acquires biological information on a person to be measured; an abnormality determination unit 16 that is based on the biological information, determines whether the person to be measured is in an abnormal condition; a notification unit 17 that when it is determined that the person to be measured is in the abnormal condition, notifies the fact accordingly; a condition determination unit 13 that determines whether the person to be measured is in a predetermined temporary body condition; and a notification restriction unit 15 that when it is determined that the person to be measured is in the temporary body condition, restricts notification made by the notification unit 17.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a monitoring device, a monitoring method, and a program, and in particular to a technique for determining a physical abnormality of a subject based on the subject's biological information. [Background technology]

[0002] There is known a system that detects biological information of a person to be measured, such as heart rate and respiration rate, while the person is asleep. For example, the following Patent Document 1 discloses an abnormality evaluation device that acquires the respiration rate of the person to be measured while asleep and compares the respiration rate with a reference respiration rate to determine whether the person to be measured is in an abnormal physical state. When the device determines that the person to be measured is in an abnormal state, it notifies the person or a caregiver of the abnormality. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6193650 Summary of the Invention [Problem to be solved by the invention]

[0004] After drinking alcohol or exercising, the heart rate and respiratory rate of the person being measured change significantly, albeit temporarily. Therefore, with the above-mentioned conventional technology, the person being measured after drinking alcohol or exercising may be judged to be in an abnormal state, and a notification of the abnormal state may be issued.

[0005] The present invention has been made in consideration of the above-mentioned problems, and its purpose is to provide a monitoring device, monitoring method, and program that can appropriately notify of abnormalities in a person being measured, taking into account the person's temporary physical condition, such as drinking or exercise. [Means for solving the problem]

[0006] (1) In order to solve the above problems, the monitoring device of the present invention includes a biometric information acquisition means for acquiring biometric information of the person being measured, an abnormality judgment means for judging whether or not the person being measured is in an abnormal state based on the biometric information, a notification means for notifying the person being measured of the abnormal state when it is judged that the person being measured is in an abnormal state, a state judgment means for judging whether or not the person being measured is in a predetermined temporary physical state, and a notification restriction means for restricting the notification by the notification means when it is judged that the person being measured is in the temporary physical state.

[0007] (2) In the monitoring device described in (1) above, the notification limiting means may change the judgment criteria in the judgment means when it is judged that the person being measured is in the temporary physical condition.

[0008] (3) The monitoring device according to (2) above may further include an influence level determination means for determining an influence level of the temporary physical condition of the person being measured. The notification limiting means may change a determination criterion in the determination means according to the influence level.

[0009] (4) In the monitoring device described in any of (1) to (3) above, the notification restriction means may be configured to, when it is determined that the person being measured is in the temporary physical state, not to issue a notification by the notification means until it is determined that the person being measured is not in the temporary physical state.

[0010] (5) In the monitoring device described in any one of (1) to (4) above, the condition determining means may determine whether or not the person being measured is in the temporary physical condition based on the biological information.

[0011] (6) In the monitoring device described in (5) above, the state determination means may include a machine learning model trained using the biometric information of a human being in the temporary physical state.

[0012] (7) In the monitoring device described in any one of (1) to (6) above, the temporary physical state may be a state after drinking alcohol or a state after exercise.

[0013] (8) Furthermore, the monitoring method of the present invention includes a bio-information acquisition step of acquiring bio-information of the person being measured, an abnormality judgment step of determining whether or not the person being measured is in an abnormal state based on the bio-information, a notification step of notifying the person being measured of the abnormal state if it is determined that the person being measured is in an abnormal state, a condition judgment step of determining whether or not the person being measured is in a predetermined temporary physical state, and a notification restriction step of restricting the notification in the notification step if it is determined that the person being measured is in the temporary physical state.

[0014] (9) The program according to the present invention is a program for causing a computer to function as a bioinformation acquiring means for calculating bioinformation of a subject, an abnormality determining means for determining whether or not the subject is in an abnormal state based on the bioinformation, a notification means for notifying the subject when it is determined that the subject is in an abnormal state, a condition determining means for determining whether or not the subject is in a predetermined temporary physical condition, and a notification limiting means for limiting the notification by the notification means when it is determined that the subject is in the temporary physical condition. This program may be stored in a computer-readable information storage medium such as a semiconductor memory or an optical magnetic disk. Effect of the Invention

[0015] According to the present invention, abnormalities in a person to be measured can be appropriately notified based on the temporary physical condition of the person to be measured, such as drinking alcohol or exercise. [Brief description of the drawings]

[0016] [Figure 1] 1 is an overall configuration diagram of a monitoring system according to an embodiment of the present invention. [Diagram 2] 1 is a functional block diagram of a monitoring device according to an embodiment of the present invention. [Diagram 3] FIG. 11 is a flow diagram showing an example of the operation of the monitoring device. [Figure 4] FIG. 11 is a flow diagram showing a modified operation example of the monitoring device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

[0018] FIG. 1 is an overall configuration diagram of a monitoring system according to an embodiment of the present invention. The monitoring system 1 shown in the figure is mainly composed of a bed 40 installed in a house. A speaker microphone 43 and a Doppler sensor 45 are attached to the headboard of the bed 40. The Doppler sensor 45 irradiates microwaves toward the chest of the person to be measured who is sleeping on the bed 40 and receives the reflected waves. A Doppler signal indicating the movement of the chest caused by the heartbeat and breathing is generated from the reflected waves, and the Doppler data obtained by digitizing this Doppler signal is output. The speaker microphone 43 is also installed so as to face the person to be measured who is sleeping on the bed 40. A weight scale 41 is attached to the floor board of the bed 40, etc., and measures the weight of the person to be measured, bedding, etc. The weight scale 41, the speaker microphone 43, and the Doppler sensor 45 are connected to a monitoring device 10 installed in the same house.

[0019] The monitoring device 10 acquires biometric information (here, heart rate and pulse rate) of the person being measured (not shown) sleeping in bed 40 based on Doppler data measured by the Doppler sensor 45, and detects abnormalities in the person being measured based on this biometric information. When an abnormality is detected, a call message such as "An abnormality has been detected. Are you OK?" is output from the speaker unit of the speaker microphone 43. If the person being measured does not respond to this with a message such as "I'm OK" into the microphone unit of the speaker microphone 43, the monitoring device 10 transmits a message of abnormality to the monitoring server 20 connected via a communication network 30 such as the Internet. Here, the monitoring server 20 is a computer installed in a remote monitoring center. When the monitoring server 20 receives the message of abnormality, the staff of the monitoring center calls the person being measured again from the speaker unit of the speaker microphone 43, and requests the dispatch of a medical professional such as a doctor or an ambulance to the house if necessary.

[0020] FIG. 2 is a functional block diagram of a monitoring device 10 according to an embodiment of the present invention. As shown in the figure, the monitoring device 10 functionally includes a biological information acquisition unit 11, an admission determination unit 12, a state determination unit 13, an influence level determination unit 14, a notification restriction unit 15, an abnormality determination unit 16, and a notification unit 17. The monitoring device 10 includes a general-purpose computer including a CPU and a memory, and each function shown in FIG. 2 is realized by executing a program according to an embodiment of the present invention in this computer. This program may be supplied to the computer from a computer-readable information storage medium such as a semiconductor memory, or may be supplied to the computer by being downloaded from another computer via a communication network 30 such as the Internet.

[0021] The biological information acquiring unit 11 acquires biological information of the subject based on the Doppler data detected by the Doppler sensor 45. Here, the heart rate and respiration rate are acquired as the biological information. For example, peaks corresponding to the heart rate and respiration rate are identified by Fourier analysis of the Doppler data, and the heart rate and respiration rate are acquired from the positions (frequencies) of these peaks.

[0022] The entry-to-bed determination unit 12 determines whether the person to be measured is sleeping in the bed 40 based on the weight detected by the weighing scale 41. For example, the weight of the person to be measured is stored in advance, and the person to be measured is determined to have entered bed at the timing when the weight detected by the weighing scale 41 increases by the weight of the person to be measured. The person to be measured is also determined to have left bed at the timing when the weight detected by the weighing scale 41 decreases by the weight stored in advance.

[0023] The state determination unit 13 determines whether the subject is in a predetermined temporary physical state. Here, the "predetermined temporary physical state" refers to a state after drinking alcohol and a state after exercise, and based on the Doppler data detected by the Doppler sensor 45, it is determined whether the subject is in a state after drinking alcohol (a state in which the influence of drinking alcohol remains), a state after exercise (a state in which the influence of exercise remains), a normal state, or another state. As an example, this determination can be made using a machine learning model. Specifically, a label indicating a state after drinking is assigned to Doppler data or its feature amount for a certain period (here, as an example, 5 minutes) of a person in a state after drinking alcohol, and learning data is created. In addition, a label indicating a state after exercise is assigned to Doppler data or its feature amount for a certain period of a person in a state after exercise, and learning data is created. Furthermore, a label indicating a normal state is assigned to Doppler data or its feature amount for a certain period of a person in a normal state (a state that is neither a state after drinking alcohol nor a state after exercise), and learning data is created. Then, a machine learning model that classifies the physical state from the Doppler data or its feature amount is trained using these learning data. In a state after drinking alcohol, the heart rate and breathing rate tend to be high and the intensity is also high. In addition, even after falling asleep, the heart rate and breathing rate tend to change little. In addition, the ratio of exhalation to inspiration in breathing tends to change. On the other hand, in a state after exercise, the heart rate and breathing rate tend to be high and the intensity is also high. In addition, after falling asleep, the heart rate and breathing rate tend to gradually decrease. In breathing, the ratio of exhalation to inspiration tends to fall within a certain range. By having a machine learning model learn such features, it is possible to determine whether the subject is in a state after drinking alcohol, a state after exercise, a normal state, or another state.

[0024] In this embodiment, the temporary physical state of the subject is determined by the machine learning model, but other methods may be used. For example, a sensor may be provided on the dining table or refrigerator, and the detection result may be used to determine whether the subject is in a state after drinking alcohol. A breath sensor may be provided to determine whether the subject is in a state after drinking alcohol based on the alcohol concentration contained in the breath. A video camera may be provided near the dining table in the house, and the contents of the video may be used to determine whether the subject has drunk alcohol. A video camera may be provided in the living room, and the contents of the video may be used to determine whether the subject has exercised in the house. The subject may input to the monitoring device 10 whether he or she has drunk alcohol or exercised.

[0025] The influence level determination unit 14 determines the influence level (the extent of the influence of alcohol) when the subject is in a post-alcohol state. Also, when the subject is in a post-exercise state, it determines the influence level (the extent of the influence of exercise). For example, the greater the influence of alcohol remains after drinking, the higher the subject's heart rate and respiration rate. Therefore, a range of heart rate and / or respiration rate is set for each influence level (for example, in three stages), and when the state determination unit 13 determines that the subject is in a post-alcohol state, the influence level determination unit 14 checks to which influence level range the subject's heart rate and respiration rate acquired by the biological information acquisition unit 11 belong, and thereby determines the influence level of alcohol.

[0026] Furthermore, the greater the influence of exercise remains after exercise, the higher the heart rate and respiration rate of the person being measured. Therefore, a range of the heart rate and / or respiration rate may be set in advance for each influence level (for example, in three stages), and when the state determination unit 13 determines that the person being measured is in a post-exercise state, the influence level determination unit 14 may check to which influence level range the heart rate and respiration rate of the person being measured acquired by the biological information acquisition unit 11 belong, thereby determining the influence level of the exercise.

[0027] The abnormality determination unit 16 determines whether the subject is in an abnormal state based on the subject's heart rate and respiration rate acquired by the biological information acquisition unit 11. As an example, a plurality of numerical ranges for the heart rate are provided, and a risk value is set for each of the numerical ranges. Then, the risk value for the heart rate is determined by checking which numerical range the heart rate belongs to. Similarly, a plurality of numerical ranges for the respiration rate are provided, and a risk value is set for each of the numerical ranges. Then, the risk value for the respiration rate is determined by checking which numerical range the respiration rate belongs to. Then, the abnormality determination unit 16 calculates a total risk value by adding the risk value for the heart rate and the risk value for the respiration rate. If this total risk value is equal to or greater than a given threshold, the abnormality determination unit 16 determines that the subject is in an abnormal state. As the given threshold, a normal threshold used when the subject is in a normal state and a post-drinking threshold used when the subject is in a post-drinking state are provided. As described later, a plurality of post-drinking thresholds may be provided according to the degree to which the influence of drinking remains (influence level). In addition, when the subject is in a post-exercise state, it may be determined whether the subject is in an abnormal state, and in this case, a post-exercise threshold may be further prepared. A plurality of post-exercise thresholds may be prepared according to the degree to which the effects of exercise remain (influence level).

[0028] When it is determined that the subject is in an abnormal state, the notification unit 17 notifies the subject. Specifically, it outputs a voice message from the speaker unit of the speaker microphone 43. If there is no response from the subject to the message, it transmits a message to the monitoring server 20 via the communication network 30 to the monitoring server 20 that the subject is in an abnormal state.

[0029] The notification limiting unit 15 limits notification by the notification unit 17 when the subject is determined to be in a post-drinking state or a post-exercise state. For example, when the subject is in a post-drinking state, the abnormality determination unit 16 changes the determination criteria for the abnormality state. Specifically, the threshold value compared with the total risk value is changed to a post-drinking threshold value that is increased by a predetermined value from the normal threshold value. This reduces the number of cases where the total risk value exceeds the threshold value and is determined to be an abnormal state. In this way, notification by the notification unit 17 can be suppressed. At this time, the degree to which the threshold value is increased may be changed according to the influence level of alcohol. Specifically, the higher the influence level of alcohol, the larger the post-drinking threshold value may be used. In this way, the determination criteria can be set appropriately according to the influence level of alcohol. The notification limiting unit 15 may stop the abnormality determination by the abnormality determination unit 16 or the notification by the notification unit 17 until it is determined that the subject is not in a post-drinking state.

[0030] Similarly, when the subject is in a post-exercise state, the abnormality determination section 16 may change the criteria for determining an abnormality. Specifically, the threshold value compared with the overall risk value is changed to a post-exercise threshold value that is increased by a predetermined value from the normal threshold value. At this time, the degree to which the threshold value is increased may be changed according to the level of influence of exercise. Specifically, the higher the level of influence of exercise, the larger the post-exercise threshold value that is used. Alternatively, the notification limiting section 15 may stop the abnormality determination by the abnormality determination section 16 or stop the notification by the notification section 17 until it is determined that the subject is not in a post-exercise state.

[0031] FIG. 3 is a flow diagram showing an example of the operation of the monitoring device 10. As shown in the figure, in the monitoring device 10, the bed entry determination unit 12 first monitors whether the subject has entered the bed 40 (S101). If the subject has entered the bed, the biological information acquisition unit 11 then acquires Doppler data transmitted from the Doppler sensor 45 (S102). The monitoring device 10 repeats the processes of S101 and S102 until one minute has passed (S103), and when one minute has passed (S103), it next determines whether five minutes or more have passed since the subject entered the bed (S104). If five minutes or more have not passed, the abnormality determination unit 16 sets the normal threshold value as the determination criterion (S109).

[0032] If it is determined in S104 that 5 minutes or more have passed since the subject went to bed, the state determination unit 13 determines the state of the subject, and the influence level determination unit 14 determines the influence level of drinking or the like (S105). Specifically, the state determination unit 13 inputs Doppler data for the most recent 5 minutes into a machine learning model to determine whether the subject is in a state after drinking or exercising. As a result, if it is determined that the subject is in a normal state (S106), the abnormality determination unit 16 sets a normal threshold as the determination criterion (S109). Also, if it is determined that the subject is in a state after drinking (S107), the abnormality determination unit 16 sets a post-drinking threshold according to the influence level of drinking as the determination criterion (S109). Also, if it is determined that the subject is in a state after exercising (S108), the notification unit 17 outputs a voice from the speaker unit of the speaker microphone 43 to the effect that the abnormality determination is temporarily halted (suspended) (S112), and returns to S101. Furthermore, if it is determined that the person being measured is not in a post-exercise state (S108), the notification unit 17 outputs a voice from the speaker unit of the speaker microphone 43 indicating that the abnormality determination is to be stopped (S111), and transmits a message to that effect to the watching server 20.

[0033] Thereafter, the abnormality determination unit 16 calculates a total risk value based on the heart rate and respiratory rate acquired by the biological information acquisition unit 11 (S113). Then, the abnormality determination unit 16 performs abnormality determination by comparing the total risk value with the threshold value set in S109 or S110 (S114).

[0034] When the abnormality determination unit 16 determines that the most recent five abnormality determinations have been consecutively abnormal (S115), the notification unit 17 issues a call through the speaker unit of the speaker microphone 43 (S116). If the measurement subject's response to this call is picked up by the microphone unit of the speaker microphone 43 (S117), the process returns to S101. If the measurement subject's response is not picked up (S117), the notification unit 17 transmits a message to the monitoring server 20 indicating that an abnormality has occurred in the measurement subject (S118), and the process returns to S101.

[0035] Also, in S115, if the abnormality determination unit 16 determines that there is no abnormal state in the most recent five consecutive abnormality determinations, the process returns to S101. Then, after one minute has elapsed, the state determination unit 13 again determines the state of the subject based on the Doppler data for the most recent five minutes, and the influence level determination unit 14 determines the influence level of drinking, etc. (S105). If the monitoring device 10 judges that the subject has changed from the post-drinking state (S107) to a normal state (S106), it sets a normal threshold as the judgment criterion (S109) and continues the subsequent processes.

[0036] According to the monitoring system 1 described above, the heart rate and respiratory rate of the person being measured after going to bed or while asleep can be obtained based on the Doppler data acquired by the Doppler sensor 45, and a total risk value is calculated from these values. The total risk value is compared with a given threshold, and if it is equal to or greater than the threshold, it is determined that an abnormality has occurred. The notification unit 17 notifies the person being measured and the staff of the monitoring center of this fact. In this embodiment, it is determined from the Doppler data whether the person being measured is in a temporary physical state due to drinking or exercise, and the notification by the notification unit 17 is limited based on this. This makes it possible to prevent excessive notifications from being made to the person being measured and the staff of the monitoring center.

[0037] The present invention is not limited to the above-described embodiment, and various modifications are possible. Such modifications also fall within the technical scope of the present invention.

[0038] For example, in the operation example of FIG. 3, the state of drinking, etc., was not judged until 5 minutes or more had passed after going to bed, but the state of drinking, etc. may be judged after 1 minute has passed after going to bed. FIG. 4 is a flow diagram showing the operation of the monitoring device in this case. As shown in the figure, after 1 minute has passed after going to bed, the state judgment unit 13 judges the state of the person being measured, and the influence level judgment unit 14 judges the influence level of drinking, etc. (S105a). At this time, if it is less than 5 minutes after going to bed, the state judgment unit 13 judges the state of the person being measured based on the Doppler data for the previous 1 minute, for example, by a first machine learning model. Also, if 5 minutes or more have passed after going to bed, the state of the person being measured is judged based on the Doppler data for the previous 5 minutes, for example, by a second machine learning model. When creating the first machine learning model, a label indicating a state after drinking, etc. is assigned to the 1-minute Doppler data or its feature amount of a person in each of the states after drinking, after exercise, and normal, and learning data is created. Then, a first machine learning model that classifies the physical condition from one minute of Doppler data or its feature values ​​is trained using the learning data thus created. Similarly, when creating a second machine learning model, a label indicating the state after drinking is added to five minutes of Doppler data or its feature values ​​of a person in each of the states after drinking, after exercise, and normal, to create learning data. Then, a second machine learning model that classifies the physical condition from five minutes of Doppler data or its feature values ​​is trained using the learning data thus created. According to this modification, an abnormality can be appropriately determined based on the temporary physical condition of the person being measured one minute after going to bed. [Explanation of symbols]

[0039] 1 monitoring system, 10 monitoring device, 11 vital information acquisition unit, 12 bed admission determination unit, 13 status determination unit, 14 impact level determination unit, 15 notification restriction unit, 16 abnormality determination unit, 17 notification unit, 20 monitoring center server, 30 communication network, 40 bed, 41 weighing scale, 43 speaker microphone, 45 Doppler sensor.

Claims

1. A biological information acquiring means for acquiring biological information of a subject; an abnormality determination means for determining whether the subject is in an abnormal state based on the biological information; a notification means for notifying the subject when the subject is determined to be in an abnormal state; A state determination means for determining whether the subject is in a predetermined temporary physical state; a notification limiting means for limiting notification by the notification means when the subject is determined to be in the temporary physical condition; A monitoring device comprising:

2. The monitoring device according to claim 1, The notification limiting means changes the determination criterion in the determining means when the subject is determined to be in the temporary physical condition. A monitoring device characterized by the above.

3. The monitoring device according to claim 2, an influence level determining means for determining an influence level of the temporary physical condition of the subject; The notification limiting means changes a determination criterion in the determining means in accordance with the impact level. A monitoring device characterized by the above.

4. The monitoring device according to claim 1, When it is determined that the subject is in the temporary physical condition, the notification limiting means does not issue a notification by the notification means until it is determined that the subject is not in the temporary physical condition. A monitoring device characterized by the above.

5. The monitoring device according to claim 1, the condition determining means determines whether the subject is in the temporary physical condition based on the biological information. A monitoring device characterized by the above.

6. The monitoring device according to claim 5, The state determination means includes a machine learning model trained using the biometric information of a human being in the temporary physical state. A monitoring device characterized by the above.

7. The monitoring device according to claim 6, The temporary physical state is a state after drinking alcohol or a state after exercise; A monitoring device characterized by the above.

8. A biological information acquiring step of acquiring biological information of a subject; an abnormality determination step of determining whether or not the subject is in an abnormal state based on the biological information; a notification step of notifying the subject that the subject is in an abnormal state when the subject is determined to be in an abnormal state; a state determination step of determining whether the subject is in a predetermined temporary physical state; a notification limiting step of limiting notification in the notification step when the subject is determined to be in the temporary physical condition; A monitoring method comprising:

9. A biological information acquiring means for calculating biological information of a subject; an abnormality determination means for determining whether the subject is in an abnormal state based on the biological information; a notification means for notifying the subject when the subject is determined to be in an abnormal state; A state determination means for determining whether the subject is in a predetermined temporary physical state; and a notification limiting means for limiting notification by the notification means when the subject is determined to be in the temporary physical condition; A program that makes a computer function as a

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