JP7435459B2 - Condition monitoring device and condition monitoring method - Google Patents

Description

The present disclosure relates to a condition monitoring device that monitors the condition of a resident.

Techniques for monitoring residents are known. For example, Japanese Unexamined Patent Publication No. 2017-174012 (Patent Document 1) proposes a monitoring system that monitors the condition of elderly people and the like using IT (Information Technology). If a problem arises with a subject, a caregiver, nurse, etc. can immediately provide assistance. An information processing device has been disclosed that displays the condition of a subject on a screen in real time, and displays the condition of a subject in which an unusual phenomenon, that is, an event has occurred.

Furthermore, in Japanese Patent No. 5682504 (Patent Document 2), in a safety monitoring device that collects biological information of a subject and monitors the safety of the subject, microwaves are irradiated to the subject, and the Doppler A method is disclosed in which the body movements and breathing of a subject are detected from the shifted reflected waves, and the safety of the subject is monitored from the number of body movements and breathing rate within a predetermined period of time.

JP 2017-174012 Publication Patent No. 5682504

The above-mentioned document describes a method for monitoring the safety of a subject, in which an abnormal state of the subject is determined from a safety pattern based on a combination of body movement rate and breathing rate.

On the other hand, in the case of abnormalities associated with pneumonia or fever, there is a possibility that this safety pattern does not apply.

The present disclosure has been made in view of the above-mentioned background, and an objective in one aspect is to provide a condition monitoring device that can confirm the condition of a subject with high accuracy.

According to a certain embodiment, the condition monitoring device includes a detection unit that irradiates a subject with microwaves and detects a reflected wave reflected from the subject, and a detection unit that detects a reflected wave reflected from the subject based on the reflected wave detected by the detection unit. It includes an analysis section that detects breathing of the examiner and body movements other than breathing of the subject, and a determination section that determines that breathing is abnormal based on the detection result of the detection section.

Preferably, the analysis unit generates a spectrum signal based on the reflected wave detected by the detection unit, detects a frequency signal caused by the subject's breathing based on the spectrum signal, and detects a frequency signal of the subject that is higher than the frequency signal. Detects frequency signals caused by body movements other than breathing.

Preferably, the determining unit determines whether the number of breaths according to the frequency signal caused by breathing of the subject is equal to or higher than a predetermined number, and the power of the frequency signal caused by body movements other than breathing of the subject is less than a predetermined value. It is determined that the patient has a breathing abnormality.

In certain situations, it is possible to confirm the safety of a subject with high accuracy.
These and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the invention, taken in conjunction with the accompanying drawings.

1 is a diagram showing an example of the configuration of a monitoring system 100. FIG. 1 is a block diagram showing an overview of the configuration of a monitoring system 100. FIG. 3 is a block diagram showing the hardware configuration of a computer system 300 that functions as a cloud server 150. FIG. 1 is a diagram illustrating an example of a schematic device configuration of a monitoring system 100 using a sensor box 119. FIG. It is a figure explaining the sensor data in the test subject's normal state acquired by the sensor box 119 based on embodiment. It is a figure explaining the sensor data in the abnormal state of the test subject acquired by the sensor box 119 based on embodiment. It is a figure explaining spectrum data of sensor data when a subject is in a normal state based on an embodiment. It is a figure explaining spectrum data of sensor data when a subject is in an abnormal state based on an embodiment. It is a figure explaining sensor data in another abnormal state of a subject acquired by sensor box 119 based on an embodiment. FIG. 7 is a diagram illustrating spectrum data of sensor data when the subject is in another abnormal state based on the embodiment. It is a figure explaining the spectrum data of the sensor data in a normal state based on the modification of embodiment. It is a figure explaining the respiration rate in a normal state based on the modification of embodiment. FIG. 7 is a diagram illustrating spectrum data of sensor data in an abnormal state based on a modification of the embodiment. It is a figure explaining the respiration rate in the abnormal state based on the modification of embodiment. FIG. 7 is a diagram illustrating determination of an abnormal state based on a modification of the embodiment.

Hereinafter, embodiments of the technical idea according to the present disclosure will be described with reference to the drawings. In the following description, the same parts are given the same reference numerals. Their names and functions are also the same. Therefore, detailed descriptions thereof will not be repeated.

[Technical philosophy]
First, an overview of the technical idea disclosed in this specification will be explained. In one aspect, a respiratory signal is measured as biological information of a subject such as a resident of a facility, and the subject's daily condition can be accurately grasped. Measurements are performed without the subject being aware that they are being measured.

(Embodiment 1)
[Configuration of monitoring system (condition monitoring device)]
FIG. 1 is a diagram showing an example of the configuration of a monitoring system 100. The targets to be monitored are, for example, residents in each living room provided in the living room area 180 of the facility. In the monitoring system 100 of FIG. 1, living rooms 110 and 120 are provided in a living room area 180. A living room 110 is assigned to a resident 111. The living room 120 is assigned to a resident 121. In the example of FIG. 1, the number of living rooms included in the monitoring system 100 is two, but the number is not limited to this.

In the monitoring system 100, sensor boxes 119 installed in living rooms 110 and 120, a management server 200 installed in a management center 130, and an access point 140 are connected via a network 190. Network 190 may include both an intranet and the Internet.

In the monitoring system 100, a mobile terminal 143 carried by a caregiver 141 and a portable terminal 144 carried by a caregiver 142 can be connected to a network 190 via an access point 140. Further, sensor box 119, management server 200, and access point 140 can communicate with cloud server 150 via network 190.

Living rooms 110 and 120 each include a chest of drawers 112, a bed 113, and a toilet 114 as facilities. A door sensor 118 is installed on the door of the living room 110 to detect whether the door is opened or closed. A toilet sensor 116 is installed on the door of the toilet 114 to detect whether the toilet 114 is opened or closed. An odor sensor 117 is installed on the bed 113 to detect the odor of each resident 111, 121. In the rooms 110 and 120, each resident 111 and 121 can operate the care call handset 115, respectively.

The sensor box 119 has built-in sensors for detecting the behavior of objects in the rooms 110 and 120. An example of a sensor is a Doppler sensor for detecting motion of an object. Another example is a camera. The sensor box 119 may include both a Doppler sensor and a camera as sensors.

Components of the monitoring system 100 will be described with reference to FIG. 2. FIG. 2 is a block diagram showing an overview of the configuration of the monitoring system 100.

[Sensor box 119]
The sensor box 119 includes a control device 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, a communication interface 104, a camera 105, a Doppler sensor 106, a wireless communication device 107, and a storage device. 108.

Control device 101 controls sensor box 119. Control device 101 is configured, for example, by at least one integrated circuit. The integrated circuit is, for example, at least one CPU (Central Processing Unit), MPU (Micro Processing Unit) or other processor, at least one ASIC (Application Specific Integrated Circuit), at least one FPGA (Field Programmable Gate Array), or any of these. It is composed of a combination of

An antenna (not shown) or the like is connected to the communication interface 104. The sensor box 119 exchanges data with an external communication device via the antenna. External communication devices include, for example, management server 200, mobile terminals 143, 144 and other terminals, access point 140, cloud server 150, and other communication terminals.

Camera 105, in one implementation, is a near-infrared camera. The near-infrared camera includes an IR (Infrared) projector that projects near-infrared light. By using a near-infrared camera, images representing the interiors of living rooms 110 and 120 can be captured even at night. In other implementations, camera 105 is a surveillance camera that receives only visible light. In still other implementations, the camera 105 may be a 3D sensor or a thermography camera. Sensor box 119 and camera 105 may be configured as one body or may be configured as separate bodies.

The Doppler sensor 106 is, for example, a microwave Doppler sensor, and detects the behavior (motion) of objects in the rooms 110 and 120 by emitting and receiving radio waves. Thereby, the biometric information of the residents 111 and 121 in the rooms 110 and 120 can be detected. In one example, the Doppler sensor 106 emits microwaves in the 24 GHz band toward the beds 113 of the rooms 110 and 120, and receives reflected waves reflected by the occupants 111 and 121. The reflected waves undergo a Doppler shift due to the actions of the residents 111 and 121. The Doppler sensor 106 can detect the breathing state and heart rate of the residents 111, 121 from the reflected waves.

The wireless communication device 107 receives signals from the care call handset 240, the door sensor 118, the toilet sensor 116, and the odor sensor 117, and transmits the signals to the control device 101. For example, the care call handset 240 includes a care call button 241. When the button is operated, care call handset 240 transmits a signal to wireless communication device 107 indicating that the button has been operated. Door sensor 118, toilet sensor 116, and odor sensor 117 transmit their detection results to wireless communication device 107.

The storage device 108 is, for example, a fixed storage device such as a flash memory or a hard disk, or a recording medium such as an external storage device. The storage device 108 stores programs executed by the control device 101 and various data used to execute the programs. The various data may include behavior information of the residents 111 and 121.

At least one of the above programs and data may be stored in a storage device other than the storage device 108, as long as the storage device is accessible by the control device 101 (for example, the storage area of the control device 101 (such as a cache memory), the ROM 102, It may be stored in the RAM 103 or external devices (for example, the management server 200, the mobile terminals 143, 144, etc.).

[Mobile terminals 143, 144]
The mobile terminals 143 and 144 include a control device 221 , a ROM 222 , a RAM 223 , a communication interface 224 , a display 226 , a storage device 228 , and an input device 229 . In one aspect, the mobile terminals 143 and 144 are realized as, for example, a smartphone, a tablet terminal, a wristwatch type terminal, or other wearable device.

Control device 221 controls mobile terminals 143 and 144. The control device 221 is constituted by, for example, at least one integrated circuit. The integrated circuit is configured, for example, by at least one CPU, at least one ASIC, at least one FPGA, or a combination thereof.

An antenna (not shown) or the like is connected to the communication interface 224. The mobile terminals 143 and 144 exchange data with external communication devices via the antenna and access point 140. External communication devices include, for example, the sensor box 119 and the management server 200.

The display 226 is realized by, for example, a liquid crystal display, an organic EL (Electro Luminescence) display, or the like. Input device 229 is realized, for example, by a touch sensor provided on display 226. The touch sensor receives a touch operation on the mobile terminals 143, 144, and outputs a signal corresponding to the touch operation to the control device 221.

The storage device 228 is realized by, for example, a flash memory, a hard disk or other fixed storage device, or a removable data recording medium.

[Management server 200]
Management server 200 includes an analysis section 202 and a determination section 204.

The analysis unit 202 and the determination unit 204 are realized by the CPU executing programs stored in memory. The analysis unit 202 reads sensor data stored in the hard disk 5 of the cloud server 150 and obtains spectrum data of the respiratory signal.

The determination unit 204 determines the condition of the subject based on the spectrum data of the respiratory signal.

[Cloud server configuration]
The configuration of cloud server 150 will be described with reference to FIG. 3. FIG. 3 is a block diagram showing the hardware configuration of computer system 300 functioning as cloud server 150.

The computer system 300 includes, as main components, a CPU 1 that executes a program, a mouse 2 and a keyboard 3 that receive instructions from a user of the computer system 300, and data generated by executing a program by the CPU 1 or a mouse 2. Alternatively, a RAM 4 that volatilely stores data input via the keyboard 3, a hard disk 5 that stores data nonvolatilely, an optical disk drive 6, a communication interface (I/F) 7, and a monitor 8. include. Each component is connected to each other by a data bus. The optical disk drive device 6 is loaded with a CD-ROM 9 and other optical disks.

Processing in the computer system 300 is realized by each piece of hardware and software executed by the CPU 1. Such software may be stored in the hard disk 5 in advance. Further, the software may be stored on a CD-ROM 9 or other recording medium and distributed as a computer program. Alternatively, the software may be provided as a downloadable application program by an information provider connected to the Internet. Such software is read from the recording medium by the optical disk drive device 6 or other reading device, or is downloaded via the communication interface 7, and then temporarily stored in the hard disk 5. The software is read from the hard disk 5 by the CPU 1 and stored in the RAM 4 in the form of an executable program. CPU1 executes the program.

Each of the components constituting the computer system 300 shown in FIG. 3 is common. Therefore, it can be said that one of the essential parts of the technical idea according to the present disclosure is software stored in the RAM 4, hard disk 5, CD-ROM 9, and other recording media, or software that can be downloaded via a network. The storage medium may include a non-transitory computer readable data storage medium. Note that since the operation of each piece of hardware in the computer system 300 is well known, detailed explanation will not be repeated.

Note that the recording medium is not limited to CD-ROM, FD (Flexible Disk), hard disk, but also magnetic tape, cassette tape, optical disk (MO (Magnetic Optical Disc) / MD (Mini Disc) / DVD (Digital Versatile Disc)). , IC (Integrated Circuit) cards (including memory cards), optical cards, mask ROM, EPROM (Electronically Programmable Read-Only Memory), EEPROM (Electronically Erasable Programmable Read-Only Memory), flash ROM, and other semiconductor memories. It may also be a medium that carries a program.

The program here includes not only programs that can be directly executed by the CPU, but also programs in source program format, compressed programs, encrypted programs, and the like.

[Device configuration of monitoring system 100]
With reference to FIG. 4, monitoring using the monitoring system 100 will be described. FIG. 4 is a diagram showing an example of a schematic device configuration of the monitoring system 100 using the sensor box 119.

The monitoring system 100 is used to watch over the residents 111, 121 and other residents who are the persons to be watched (monitored persons). As shown in FIG. 4, a sensor box 119 is attached to the ceiling of the living room 110. Sensor boxes 119 are similarly installed in other living rooms.

Range 410 represents the detection range by sensor box 119. If the sensor box 119 has a Doppler sensor as described above, the Doppler sensor detects human behavior occurring within the range 410. If the sensor box 119 has a camera as a sensor, the camera takes an image within the range 410.

The sensor box 119 is installed, for example, in a nursing care facility, a medical facility, a home, or the like. In the example of FIG. 4, the sensor box 119 is attached to the ceiling and photographs the resident 111 and the bed 113 from the ceiling. The mounting location of the sensor box 119 is not limited to the ceiling, but may be mounted on the side wall of the living room 110.

The monitoring system 100 detects danger to the resident 111 based on a series of images (ie, video) obtained from the camera 105. As an example, the detectable danger includes a fall of the resident 111, a state where the resident 111 is in a dangerous place (eg, a bed rail, etc.), and the like.

When the monitoring system 100 detects that the resident 111 is in danger, it notifies the caregivers 141, 143, etc. of this fact. As an example of a notification method, the monitoring system 100 notifies the mobile terminals 143, 144 of the caregivers 141, 142 of the danger of the resident 111. When receiving the notification, the mobile terminals 143 and 144 notify the caregivers 141 and 142 of the danger of the resident 111 by means of a message, voice, vibration, etc. Thereby, the caregivers 141 and 142 can immediately understand that the resident 111 is in danger, and can quickly rush to the resident 111.

Although FIG. 4 shows an example in which the monitoring system 100 includes one sensor box 119, the monitoring system 100 may include a plurality of sensor boxes 119. Further, although FIG. 4 shows an example in which the monitoring system 100 includes a plurality of mobile terminals 143 and 144, the monitoring system 100 can also be realized by a single mobile terminal.

The communication interface 104 of the sensor box 119 in this example transmits sensor data acquired by the Doppler sensor 106 to the cloud server 150 at any time.

The cloud server 150 stores the information on the hard disk 5, for example.
The management server 200 reads sensor data stored in the hard disk 5 of the cloud server 150 and executes predetermined processing. In this example, the condition of the subject is determined. For example, a resting state or an awake state is determined as the state of the subject.

The management server 200 notifies the caregiver of the subject's condition as necessary.
[Sensor data]
FIG. 5 is a diagram illustrating sensor data in a normal state of a subject acquired by the sensor box 119 based on the embodiment.

As shown in FIG. 5, reflected waves of microwaves are detected by the Doppler sensor. In normal healthy lungs, there is a pause after exhalation and inspiration, and the movement continues until expiration.

Also in this example, when the subject is in a normal state, a stopping motion occurs after a breathing motion. A case is shown in which there is a long pause after the breathing movement when the breathing rate is 15 breaths/minute.

As an example, a case where the stopping time of the stopping operation is 0.7 seconds is shown.
FIG. 6 is a diagram illustrating sensor data obtained by the sensor box 119 based on the embodiment when the subject is in an abnormal state.

As shown in FIG. 6, reflected waves of microwaves are detected by the Doppler sensor. For example, when the subject is in an abnormal state, the stopping motion after the breathing motion becomes shorter.

This is shown when there is a short stopping motion after the breathing motion when the breathing rate is 21.4 times/min.

As an example, a case where the stopping time of the stopping operation is 0.5 seconds is shown.
FIG. 7 is a diagram illustrating spectrum data of sensor data when the subject is in a normal state based on the embodiment.

In FIG. 7, the analysis unit 202 of the management server 200 reads out the sensor data shown in FIG. 5 stored in the hard disk 5 of the cloud server 150, and acquires spectrum data of the respiratory signal.

The horizontal axis represents the frequency (times/min) corresponding to respiration, and the vertical axis represents the state in which the maximum value of the signal strength is normalized to 1. In a normal state, a signal corresponding to respiration is shown at a position of 0.25 Hz. The breathing rate is 15 times/min. Furthermore, as a stop component after the breathing action, a signal corresponding to the stop action is shown at a position of 1 Hz.

FIG. 8 is a diagram illustrating spectrum data of sensor data when a subject is in an abnormal state based on the embodiment.

In FIG. 8, the analysis unit 202 of the management server 200 reads the sensor data shown in FIG. 6 stored in the hard disk 5 of the cloud server 150, and obtains spectrum data of the respiratory signal.

The horizontal axis represents the frequency (times/min) corresponding to respiration, and the vertical axis represents the state in which the maximum value of the signal strength is normalized to 1. In the case of an abnormal state, a signal corresponding to respiration is shown at a position of 0.356 Hz. The respiratory rate was 21.4 times/min. Furthermore, as a stop component after the breathing action, a signal corresponding to the stop action is shown at a position of 1.43 Hz.

Therefore, while the frequency of breathing motion in an abnormal state increases by 0.1 Hz, the frequency of stopping motion increases by 0.43 Hz. In other words, a quick response is required.

In abnormal conditions, the amount of ventilation in the lungs decreases, so in the case of pneumonia, the amount of ventilation is compensated for by the number of breaths. Similarly, in the case of fever, the respiratory rate is increased to take in more oxygen in order to generate heat. In other words, the body increases the rate of breathing to increase oxygen intake.

In this case, there is no stopping time, exhalation and inhalation are continuous, and the body does not make any other movements as much as possible.

FIG. 9 is a diagram illustrating sensor data obtained by the sensor box 119 based on the embodiment in another abnormal state of the subject.

As shown in FIG. 9, when the subject is in an abnormal state, the stopping motion after the breathing motion becomes even shorter. These short stop times do not constitute a rest, and are actually likely to result in a continuous waveform. Therefore, high frequency components decrease in an abnormal state.

FIG. 10 is a diagram illustrating spectrum data of sensor data when the subject is in another abnormal state based on the embodiment.

In FIG. 10, the analysis unit 202 of the management server 200 reads out the sensor data shown in FIG. 9 stored in the hard disk 5 of the cloud server 150, and acquires spectrum data of the respiratory signal.

The horizontal axis represents the frequency (times/min) corresponding to respiration, and the vertical axis represents the state in which the maximum value of the signal strength is normalized to 1. In the case of an abnormal state, a signal corresponding to respiration is shown at a position of 0.35 Hz. In this case, a case is shown in which the stop component after the breathing movement hardly appears.

Therefore, when the number of breathing increases, if the frequency component according to the stop motion that is higher than the frequency corresponding to the breathing motion is small, it is possible to determine that there is an abnormal state.

As an example, if the number of breaths is 19 times or more, and the power spectrum of the frequency component that follows the stop motion, which is higher than the frequency corresponding to the breathing motion, is less than a predetermined amount (close to 0), it is determined that it is an abnormal state. It is possible to do so. The amount below the predetermined amount can be set to any value. In addition, in this example, a case where the number of respirations is 19 or more will be described as an increase in the number of respirations, but the number of respirations is not limited to this and can be set to any value.

(Modified example)
FIG. 11 is a diagram illustrating spectrum data of sensor data in a normal state based on a modification of the embodiment.

As shown in FIG. 11, the analysis unit 202 of the management server 200 reads sensor data stored in the hard disk 5 of the cloud server 150 and acquires spectrum data of the respiratory signal. The horizontal axis represents the number of breaths per minute, and the vertical axis represents the maximum value normalized to 1.

FIG. 12 is a diagram illustrating the respiration rate in a normal state based on a modification of the embodiment.
As shown in FIG. 12, in this example, the average value of the respiration rate is 17 breaths/min.

Regarding the spectral data in FIG. 11, the sum of powers of the spectral data from the average value of the respiration rate to 100 breaths/min is 12.1.

FIG. 13 is a diagram illustrating spectrum data of sensor data in an abnormal state based on a modification of the embodiment.

As shown in FIG. 13, the analysis unit 202 of the management server 200 reads sensor data stored in the hard disk 5 of the cloud server 150 and acquires spectrum data of the respiratory signal. The horizontal axis represents the number of breaths per minute, and the vertical axis represents the maximum value normalized to 1.

FIG. 14 is a diagram illustrating the respiration rate in an abnormal state based on a modification of the embodiment.
As shown in FIG. 14, in this example, the average value of the respiration rate is 20 breaths/min.

Regarding the spectral data in FIG. 13, the sum of powers of the spectral data from the average value of the respiration rate to 100 breaths/min is 3.8.

When the number of breaths increases, if the sum of powers of spectrum data of frequency components higher than the frequency corresponding to the breathing motion is smaller than a predetermined amount, it can be determined that the state is abnormal.

FIG. 15 is a diagram illustrating determination of an abnormal state based on a modification of the embodiment.
As shown in FIG. 15, when a person is at rest, the person's movements are not always constant, so the sum of powers of spectrum data of frequency components higher than the frequency corresponding to breathing motion varies. For example, in a state where the body is stationary even at rest, there may be no movement at frequencies higher than the respiratory rate.

On the other hand, in the case of an abnormal state, the sum of powers of spectral data of frequency components higher than the frequency corresponding to the breathing motion is in a steady state and its value is small.

Therefore, as an example, if the number of breaths is 19 times or more, and the sum of the powers of the spectrum data of frequency components higher than the frequency corresponding to the breathing movement is smaller than a predetermined amount (index value 4 in this example), It is possible to determine that the state is abnormal.

Alternatively, as another judgment method, for example, evaluate every minute for 10 minutes, measure the number of times the frequency reaches a predetermined amount (index value less than 4), and if the frequency exceeds the predetermined amount, it is abnormal. It may be determined that the state is the same.

The embodiments disclosed this time should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is indicated by the claims rather than the above description, and it is intended that equivalent meanings and all changes within the scope of the claims are included.

This technology is applicable to information obtained in hospitals, nursing homes, nursing homes, and other facilities.

100 system, 101,221 control device, 106 Doppler sensor, 107 wireless communication device, 108 storage device, 109 door, 110,120 living room, 111,121,910,920,930,950 resident, 112 chest of drawers, 113 bed, 114 toilet, 115 care call handset, 116 toilet sensor, 117 sensor, 118 door sensor, 119 sensor box, 130 management center, 140 access point, 141,142 caregiver, 143,144 mobile terminal, 150 cloud server, 190 network, 200 management server, 226 display, 229 input device, 241 care call button, 290 vital sensor, 300 computer system.

Claims (2)

a detection unit that irradiates a subject with microwaves and detects reflected waves reflected from the subject;
an analysis unit that detects breathing of the subject and body movements other than breathing of the subject based on the reflected waves detected by the detection unit;
a determination unit that determines that breathing is abnormal based on the detection result of the analysis unit ,
The analysis section includes:
generating a spectrum signal based on the reflected wave detected by the detection unit;
detecting a frequency signal caused by the subject's breathing based on the spectrum signal;
detecting a frequency signal caused by body movement other than breathing of the subject that is higher than the frequency signal;
The determination unit determines whether the number of breaths according to frequency signals caused by breathing of the subject is equal to or greater than a predetermined number, and the sum of powers of frequency signals caused by body movements other than breathing of the subject is less than a predetermined value. A condition monitoring device that determines breathing abnormality in certain cases . irradiating a subject with microwaves and detecting reflected waves reflected from the subject;
Detecting the subject's breathing and body movements other than the subject's breathing based on the detected reflected waves;
a step of determining a respiratory abnormality based on the detection result of the body movement,
The step of detecting the body movement includes:
Generates a spectral signal based on the detected reflected waves,
detecting a frequency signal caused by the subject's breathing based on the spectrum signal;
Detecting a frequency signal caused by a body movement other than breathing of the subject that is higher than the frequency signal,
In the step of determining, the number of breaths according to frequency signals caused by breathing of the subject is equal to or greater than a predetermined number, and the sum of powers of frequency signals caused by body movements other than breathing of the subject is less than a predetermined value. A condition monitoring method that determines breathing abnormality when

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