WO2024106544A1

WO2024106544A1 - Respiration count measurement device, respiration count measurement method, program, and system

Info

Publication number: WO2024106544A1
Application number: PCT/JP2023/041548
Authority: WO
Inventors: 拓則島崎; 大祐安在; 充宏福田; 大和青木
Original assignee: 株式会社メッツ; 拓則島崎; 有限会社エムズ; 大祐安在
Priority date: 2022-11-17
Filing date: 2023-11-17
Publication date: 2024-05-23

Abstract

Provided is a respiration count measurement device (100), comprising: a first sensor device (100) which detects a variation in the concentration of CO2 included in the exhalation of a subject; a second sensor device (120) which detects a noise type body motion of the subject generated in a measurement period of the first sensor device (110); and a determination unit (131b) which determines the respiration count of the subject on the basis of variation data of CO2 concentration detected in the first sensor device (110). In addition, the determination unit (131b) uses, among the variation data, CO2 concentration data generated by the noise type body motion as noise data that is not counted as the respiration count to determine the respiration count.

Description

Respiration rate measuring device, respiration rate measuring method, program and system

This disclosure relates to a respiratory rate measurement device, a respiratory rate measurement method, a program, and a system.

With the development of biometric technology, it is now possible to obtain and monitor the biological information of subjects using wearable devices. Such biological information includes, for example, heart rate, body temperature, and _SpO2 . However, respiratory status is also considered an important indicator in health management. Many elderly people, in particular, suffer from respiratory diseases such as pneumonia.

Methods for monitoring respiratory status include a method that uses thoracic impedance in conjunction with an ECG (Electrocardiogram) and a method that measures respiratory rate by analyzing pulse waves. However, these methods are easily affected by body movements such as turning over in bed, and require the patient to be at rest in order to achieve a certain level of accuracy in the measurements.

In addition, in clinical practice, capnometers that measure the _CO2 concentration in exhaled air are widely used to monitor the respiratory condition. However, with capnometers connected to artificial ventilation circuits, the detected data is an approximately rectangular wave, and a natural respiration waveform cannot be obtained, making it difficult to accurately grasp the respiratory condition of the subject.

This disclosure provides a new technology for understanding respiratory status.

One aspect of the present disclosure is a respiration rate measuring device that measures respiration rate, comprising: a first sensor device that acquires fluctuation data of _CO2 concentration in the subject's continuous exhaled breath; a second sensor device that detects noise-type body movement of the subject that occurs during a measurement period of the first sensor device; and a determination unit that determines the respiration rate based on the number of peaks in the fluctuation data, excluding a portion of the fluctuation data that corresponds to a time when the noise-type body movement occurs.

A first sensor device that acquires fluctuation data of _CO2 concentration can acquire fluctuation data for measuring the respiration rate during natural breathing. A second sensor device that detects noise-type body movements of the subject that occur during the measurement period of the first sensor device can detect noise-type body movements of the subject that may affect the measurement of the respiration rate. A determination unit that excludes a portion of the fluctuation data that corresponds to the occurrence time of the noise-type body movements and determines the respiration rate based on the number of peaks of the fluctuation data can more accurately measure the respiration rate using the fluctuation data of _CO2 concentration.

One aspect of the present disclosure is a respiration rate measurement method including: acquiring fluctuation data of _CO2 concentration in a subject's continuous exhalation by the _CO2 sensor in a respiration rate measurement device, generating frequency data by frequency-converting the fluctuation data, and regarding the fluctuation data of _the _CO2 concentration corresponding to a predetermined frequency band including the subject's natural breathing among the frequency data, determining the number of peaks of the _CO2 concentration exceeding a predetermined threshold as the respiration rate. This allows the respiration rate to be measured more accurately by using the _CO2 sensor used as a chip module.

One aspect of the present disclosure is a program configured to be executed by at least one processor and including instructions for performing the method for measuring respiration rate, which allows for more accurate measurement of respiration rate using fluctuation data of _CO2 concentration.

One aspect of the present disclosure is a program that causes at least one processor to function as at least a communication unit and a determination unit, the communication unit being configured to be able to acquire fluctuation data of _CO2 concentration in the exhaled breath of a subject and detection data related to noise-type body movements of the subject, and the determination unit being configured to be able to determine the respiratory rate of the subject based on the fluctuation data and the detection data. This allows for more accurate measurement of the respiratory rate using the fluctuation data of the _CO2 concentration.

One aspect of the present disclosure is a system including at least one processor and a program that causes the processor to function as at least a communication unit and a determination unit, the communication unit being configured to be able to acquire fluctuation data of _CO2 concentration contained in the breath of a subject and detection data related to noise-type body movements of the subject, and the determination unit being configured to be able to determine the respiratory rate of the subject based on the fluctuation data and the detection data. This allows for more accurate measurement of the respiratory rate using the fluctuation data of the _CO2 concentration.

According to the present disclosure, respiration rate can be measured using fluctuation data of _CO2 concentration.

FIG. 1 is a front view showing an example of a schematic configuration of a respiration rate measuring device according to an embodiment. FIG. 2 is a block diagram showing a schematic functional configuration of a respiration rate measuring device according to one embodiment. 1 is a flow chart illustrating one aspect of a process for measuring respiration rate by a respiration rate measurement device according to one embodiment. FIG. 13 is an illustration of the filter output normalized by the maximum _CO2 concentration detected by the respiration rate measurement device according to one embodiment. 10 is a flow chart illustrating another aspect of a process for measuring respiration rate by a respiration rate measurement device according to one embodiment. 6 is an explanatory diagram showing an example of a respiration rate determination operation in the process of measuring the respiration rate shown in the flowchart of FIG. 5 . FIG. 7 is an explanatory diagram showing another example of the respiration rate determination operation in the process of measuring the respiration rate shown in the flowchart of FIG. 5 . FIG. FIG. 11 is an explanatory diagram of the operation of determining the respiratory rate in yet another aspect of the process of measuring the respiratory rate by the respiratory rate measuring device according to one embodiment. FIG. 1 is an explanatory diagram showing one aspect of a respiration rate measuring device according to one embodiment. FIG. 11 is an explanatory diagram showing another aspect of the respiration rate measuring device according to one embodiment. 11A and 11B are explanatory diagrams showing a respiration rate measuring device according to one embodiment. 12A-12D are explanatory diagrams showing a respiration rate measuring device according to one embodiment of the present disclosure. FIG. 2 is a block diagram showing a functional configuration of a system according to an embodiment. FIG. 14A is a graph showing the results of detection of CO ₂ concentration by the CO ₂ sensor when the subject is at rest, and FIG. 14B is a graph showing the results of detection of CO ₂ concentration by the CO ₂ sensor when the subject is turning over in bed. FIG. 15A is a graph showing the results of acceleration detection by the acceleration sensor when the subject is at rest, and FIG. 15B is a graph showing the results of acceleration detection by the acceleration sensor when the subject is turning over in sleep. 16A-16F are diagrams illustrating example respiratory waveforms that may be detected by a system according to one embodiment. 17A-17C are diagrams illustrating example respiratory waveforms that may be detected by a system according to one embodiment.

Below, a preferred embodiment of the present disclosure is described in detail. The embodiment described below does not unduly limit the content of the present disclosure described in the claims, and not all of the configurations described in the embodiment are necessarily essential as a solution for the present disclosure.

In the following explanation, terms indicating directions such as "up," "down," "left," and "right" are used for convenience of explanation and do not limit the method or manner of use. Terms such as "first" and "nth" (n is an integer) following "first" in this specification and claims are used as identification terms to distinguish between different elements and do not indicate a particular order or superiority/inferiority.

The terminology used in the following description is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present disclosure. Elements according to one aspect described in the present specification and claims are intended to include the plural, unless the context clearly dictates otherwise: singular or plural.

The term "and/or" is intended to refer to and include any and all possible combinations of one or more of the associated listed elements. For example, "A or B" means "A, B, or both A and B." "A," "B," and "both A and B" all each satisfy "A or B."

The terms "includes," "including," "comprises," and/or "comprising" used in this specification and in the claims are intended to specify the presence of certain features, operations, elements, or steps, but are not intended to exclude the presence or addition of one or more other features, operations, elements, steps, and/or groups thereof.

All embodiments and optional embodiments included in this disclosure may be combined with each other to form new embodiments. In addition, all technical features and optional technical features included in this disclosure may be combined with each other to form new technical features.

Schematic configuration of respiration rate measuring device 100

The schematic configuration of a respiration rate measuring device according to one embodiment of the present disclosure will be described with reference to the drawings. FIG. 1 is a front view showing an example of the schematic configuration of a respiration rate measuring device according to one embodiment of the present disclosure.

Anyone can use the respiratory rate measuring device 100 as a "subject." It is particularly useful for people who require continuous health management. The respiratory rate measuring device 100 can measure the respiratory rate, which is an indicator of the respiratory condition in the health management of the subject. Potential subjects include, for example, patients hospitalized at medical institutions, elderly people living in nursing homes or care facilities, elderly people in evacuation centers during disasters, injured people at emergency or disaster sites, elderly people receiving home care, and people with respiratory diseases, but subjects are not limited to these people.

As shown in Fig. 1, the respiration rate measuring device 100 includes a sensor body 105 and a microcomputer 130. The sensor body 105 includes a _CO2 sensor 110 as a first sensor device and a noise detection sensor 120 as a second sensor device. The _CO2 sensor 110 and the noise detection sensor 120 are provided at different positions, such as on the same side of the sensor body 105 or on opposite sides of the sensor body 105. The _CO2 sensor 110 and the noise detection sensor 120 are connected to the microcomputer 130 via connection lines 140 (140a, 140b).

The _CO2 sensor 110 and the noise detection sensor 120 are provided in the sensor body 105 as shown in Fig. 1, but the arrangement of these sensors is not limited to this. The noise detection sensor 120 only needs to be able to measure the physical quantity of the measurement target according to its type. Therefore, the arrangement is not limited to a position within the sensor body 105, and it may be arranged at a position away from the sensor body 105.

The sensor body 105 is provided with an attachment member 150 that is used by the subject to wear it. The subject uses an attachment. Examples of the attachment include head attachment and body attachment. Examples of the head attachment include a face shield that covers the area around the mouth and a sanitary mask. Examples of the body attachment include clothing and a neck-hanging member such as a necklace. The attachment member 150 is formed in a belt shape that extends from the left and right sides of the sensor body 105. This belt-shaped attachment member 150 can hold the various attachments mentioned above. For example, the attachment member 150 can be formed in whole or in part from a resin molded body, fabric, stretchable fabric, rubber-like elastic body, or a combination thereof.

The manner in which the sensor body 105 is attached to the subject is not limited to the above. For example, the sensor body 105 may be configured so that an attachment member is attached to the ear like a eyeglass frame, and the sensor body 105 is positioned near the mouth. The respiration rate measuring device 100 may also be in the shape of a handheld rod like an interview microphone. In this case, a nurse uses the sensor body 105 by bringing it close to the area around the patient's mouth. In this way, the sensor body 105 does not have to be attached to the subject via an attachment member.

The _CO2 sensor 110 has a function as a first sensor device that detects fluctuations in the _CO2 concentration contained in the breath of the subject. The _CO2 sensor 110 is provided at a position of the sensor body 105 that faces the mouth periphery of the subject when the subject wears it in order to detect fluctuations in the _CO2 concentration contained in the breath of the subject. A gas sensor can be used as the _CO2 sensor 110. Specifically, for example, a metal oxide (MOX) gas sensor that detects volatile organic compounds (VOCs) contained in the breath can be used. The _CO2 sensor 110 exemplified here can be one that uses an equivalent carbon dioxide method. The equivalent carbon dioxide method calculates an equivalent _CO2 concentration ( _eCO2 concentration) from the concentration value of the measured volatile organic compounds (VOCs). The calculation process is performed by a microcomputer 130 connected to the _CO2 sensor 110. The measurement data of the _CO2 sensor 110 is transmitted to the microcomputer 130 via a connection line 140a. Although FIG. 1 illustrates one connection line 140a, a configuration including a plurality of connection lines may be used.

The noise detection sensor 120 functions as a second sensor device that detects noise-type body movements of the subject occurring during a measurement period of the _CO2 sensor 110 for measuring the subject's respiratory rate. The noise detection sensor 120 is disposed in the sensor body 105 near the _CO2 sensor 110. The noise detection sensor 120 detects noise-type body movements.

The noise type body movement described in this specification and claims refers to the movement of the subject that affects the fluctuation of the _CO2 concentration due to the natural breathing of the subject and causes the accuracy of the measurement of the respiratory rate of the subject to be reduced. The movement may include conscious and unconscious movements. More specifically, examples of noise type body movements include body movement changes such as the subject turning over in bed, coughing, sneezing, yawning, hiccups, talking, and other cardiopulmonary movements other than breathing of the subject, but are not limited to these.

The noise detection sensor 120 obtains data on physical quantities for identifying the presence or absence of noise-type body movements that affect the fluctuation of the _CO2 concentration due to factors other than breathing and reduce the accuracy of the measurement of the subject's breathing rate. The detection data on the noise-type body movements of the noise detection sensor 120 is transmitted to the microcomputer 130 via a connection line 140b. Although one connection line 140b is shown in FIG. 1, a configuration including multiple connection lines may be used.

Specifically, the noise detection sensor 120 may be at least one of a microphone element, an acceleration sensor, a humidity sensor, a pressure sensor, or a _CO2 sensor, but is not limited thereto and may be other sensors. The microphone element as the noise detection sensor 120 detects the fluctuation of sound generated by noise-type body movements including body movement changes and the operation of the subject's cardiopulmonary function other than breathing, such as coughing, sneezing, yawning, hiccups, and talking. The acceleration sensor as the noise detection sensor 120 detects the fluctuation of vibration generated by noise-type body movements. The humidity sensor as the noise detection sensor 120 detects the fluctuation of humidity due to moisture contained in the exhaled air generated by the operation of the cardiopulmonary function other than breathing, such as coughing, sneezing, yawning, hiccups, and talking, as the noise-type body movements. The pressure sensor as the noise detection sensor 120 detects the fluctuation of the pressure of the exhaled air generated by the operation of the cardiopulmonary function other than breathing, such as the noise-type body movements.

The _CO2 sensor as the noise detection sensor 120 (also referred to as the "second _CO2 sensor" in this disclosure) can be provided on the opposite side of the sensor body 105 to the side on which the _CO2 sensor 110 as the first sensor device (also referred to as the "first _CO2 sensor" in this disclosure) is provided in order to detect the fluctuation of the _CO2 concentration in the external environment of the subject, but is not limited thereto, and can be provided around the subject's neck or other positions that are not affected by the subject's breathing. The _CO2 sensor as the noise detection sensor 120 is, for example, an equivalent carbon dioxide type CO2 sensor, and detects the fluctuation of the _CO2 concentration in the external environment that is not affected by the fluctuation of the _CO2 concentration due to the subject's breathing during the operation of the cardiopulmonary function other than the breathing of the subject (changes in body movement, coughing, sneezing, yawning, hiccups, conversation, etc.) as the _noise type body movement.

In this way, the microphone element, acceleration sensor, humidity sensor, pressure sensor, or _CO2 sensor measures a physical quantity that can be detected, and the occurrence of various noise-type body movements that may occur in the subject can be detected by using the measurement data. The noise detection sensor 120 can be configured by a combination of one or more sensors of the same or different types.

The microcomputer 130 has a function of controlling the operation of each component of the respiration rate measuring device 100. The microcomputer 130 has a function of determining the respiration rate of the subject based on the detection data of the _CO2 sensor 110 and the noise detection sensor 120. Details regarding the functions of the microcomputer 130 will be described later.

Functional configuration of the respiration rate measuring device 100

Next, the functional configuration of a respiration rate measuring device according to an embodiment of the present disclosure will be described with reference to the drawings. FIG. 2 is a block diagram showing a schematic functional configuration of a respiration rate measuring device according to an embodiment of the present disclosure.

As described above, the respiration rate measuring device 100 has a sensor body 105 equipped with a plurality of sensors. The plurality of sensors are a _CO2 sensor 110 and a noise detection sensor 120. The sensor body 105 is provided with one _CO2 sensor 110 and one noise detection sensor 120, but two or more may be provided. For example, as the noise detection sensor 120, two or more noise detection sensors 120 may be provided to detect different noise-type body movements, such as a combination of a microphone element and an acceleration sensor, or a combination of a microphone element and a second _CO2 sensor, to remove noise data based on a wider variety of noise-type body movements and improve the measurement accuracy of the respiration rate.

As shown in FIG. 2, the respiration rate measuring device 100 may be configured such that the microcomputer 130 includes a control unit 131, a communication unit 132, an operation unit 133, a display unit 134, a ROM 135, and a RAM 136. The communication unit 132 functions as an interface when transmitting and receiving data to and from the outside via a network 2 (see FIG. 13). The communication method of the communication unit 132 may be wireless communication such as LTE (long term evolution), Wi-Fi (registered trademark), or Bluetooth (registered trademark). The operation unit 133 is composed of input buttons, a touch panel, etc., and has a function of inputting predetermined commands and data to the control unit 131. The display unit 134 has a function of outputting the results of calculations by the control unit 131 and the results of input by the operation unit 133 on a screen display, and is composed of, for example, an LCD screen, etc.

The control unit 131 has a function of controlling the operation of each component of the respiratory rate measuring device 100 by executing various programs stored in the ROM 135. The control unit 131 also has a function of storing the necessary data, etc., in the RAM 136, which temporarily stores the necessary data, etc., as appropriate when executing these various processes. Therefore, the control operations by the control unit 131 can access the ROM 135 and RAM 136, display data on the display unit 134, operate the operation unit 133, and send and receive various information via the network 2 using the communication unit 132 as an interface when communicating with the outside.

Furthermore, the control unit 131 may have a function of receiving detection data (also referred to as "measurement data" or "variation data" in this specification and claims) from each of the _CO2 sensor 110 and the noise detection sensor 120, judging the respiratory rate of the subject to be measured based on the detection data, and transmitting the judgment result to the outside. As shown in Figure 2, the control unit 131 includes a receiving unit 131a, a judging unit 131b, and a transmitting unit 131c.

The receiving unit 131a has a function of controlling reception of detection data from the _CO2 sensor 110 and the noise detection sensor 120. The receiving unit 131a also has a function of controlling reception of various data from external devices.

The determination unit 131b has a function of performing a determination operation required when performing various operations of the respiration rate measuring device 100. Specifically, the determination unit 131b has a function of determining whether various data is transmitted to and received from an external device via the communication unit 132 of the respiration rate measuring device 100. The determination unit 131b also has a function of performing arithmetic processing using detection data obtained from the _CO2 sensor 110 and the noise detection sensor 120 to determine the respiration rate of the subject.

Specifically, the determination unit 131b uses FFT analysis, wavelet analysis, AI, etc. to calculate the subject's respiratory rate and respiratory pattern based on the detection data of the _CO2 sensor 110 to determine the respiratory rate. The determination unit 131b also has a function of determining the subject's respiratory rate by using _CO2 concentration data generated by noise-type body movement among the fluctuation data detected by the _CO2 sensor 110 as noise data that is not counted as the subject's respiratory rate. Details of the operation of the determination unit 131b to determine the subject's respiratory rate will be described later.

The transmission unit 131c has a function of controlling the transmission of various data to external devices. In this embodiment, the transmission unit 131c controls the transmission of the detection data of the _CO2 sensor 110 and the detection data related to the noise type body movement detected by the noise detection sensor 120 to, for example, the administrator terminal 30 (see FIG. 13) or the server device 10 (see FIG. 13). In addition, the transmission unit 131c controls the transmission of the judgment result of the judgment unit 131b to, for example, the administrator terminal 30 or the server device 10 (see FIG. 13).

The transmitting unit 131c has a function of transmitting the measurement data of the _CO2 sensor 110 and the detection data related to the noise-type body movement detected by the noise detection sensor 120 to an external device at a predetermined time interval. The predetermined time can be set, for example, at a fixed time interval (for example, every minute) or at an arbitrary time interval. The transmitting unit 131c may also vary the predetermined time depending on the remaining battery level. For example, if the remaining battery level exceeds 50%, the data may be transmitted every minute, and if the remaining battery level is 50% or less, the data may be transmitted every 10 minutes. The remaining battery level value and the transmission time can be set arbitrarily.

Furthermore, the transmitting unit 131c may accumulate multiple pieces of detection data detected before transmitting data, and transmit the accumulated multiple pieces of detection data collectively at predetermined time intervals. This can reduce battery consumption. The detection data transmitted by the transmitting unit 131c may be any of (1) actual measurement data measured by each detection sensor, (2) processed data obtained by arithmetic processing of the actual measurement data, or (3) both the actual measurement data and the processed data. The form in which the sensor detection data is transmitted may be changed depending on the function of the determining unit 131b, the remaining battery power, etc.

In this way, the respiration rate measuring device 100 is capable of determining the respiration rate of the subject wearing the respiration rate measuring device 100 based on the fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110 and the detection data related to the noise type body movement detected by the noise detection sensor 120. The respiration rate measuring device 100 is also capable of transmitting and receiving data of the respiration rate of the subject between the administrator terminal 30 (see FIG. 13) and the server device 10. Details of determining the respiration rate of the subject and managing the health condition using the respiration rate measuring device 100 of this embodiment will be described later.

Flow of measuring respiration rate by the respiration rate measuring device 100

First flow (Figure 3)

Next, a method for measuring a respiratory rate using a respiratory rate measurement device according to an embodiment of the present disclosure will be described with reference to the drawings. FIG. 3 is a flowchart showing the operation of measuring a respiratory rate using a respiratory rate measurement device according to an embodiment of the present disclosure.

The method of measuring respiratory rate using the respiratory rate measuring device 100 is executed by a program that operates a computer included in a system 1 (see FIG. 13) that uses the respiratory rate measuring device 100. The program that executes the method of measuring respiratory rate using the respiratory rate measuring device 100 is a program that causes one or more processors (computer devices) connected to a network to measure the respiratory rate of the subject. The program that performs the method of measuring respiratory rate of this embodiment causes one or more processors (computer devices) connected to a network to execute the operation flow shown in FIG. 3.

Measurement is started by, for example, pressing the measurement start button of the respiration rate measuring device 100 as a trigger. First, the _CO2 sensor 110 detects the fluctuation of the _CO2 concentration contained in the subject's breath (step S1). The data acquired here is fluctuation data of the _CO2 concentration measured from consecutive breaths during a predetermined measurement time. In this embodiment, the _CO2 sensor 110 detects the equivalent _CO2 concentration by calculating the equivalent _CO2 concentration ( _eCO2 concentration) from the concentration value of the volatile organic compounds (VOCs) contained in the detected breath of the subject. The detection data of the _CO2 sensor 110 is transmitted to the microcomputer 130 (step S2).

When the fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110 is transmitted to the microcomputer 130, the determination unit 131b monitors the detection data of the _CO2 sensor 110 and estimates the respiratory rate from the waveform of the fluctuation data of the _CO2 concentration (step S3).

Here, the waveform of the fluctuation data of the _CO2 concentration (referred to as the _CO2 concentration waveform in this specification and claims) is a waveform expressed with time on the X-axis and _CO2 concentration on the Y-axis. Usually, the peaks of the _CO2 concentration that appear in the _CO2 concentration waveform at regular regular intervals can be understood as one breath due to natural breathing. One breath is understood as a combination of one exhalation and one inhalation. The peak of _{the CO2} concentration is usually detected in the exhalation. The respiratory rate can be calculated by the following formula.

R = Nγ/T
where R is the respiratory rate [bpm], Nγ is the number of detected respiratory rates, and T is the measurement time [min.].

The breathing rate during natural breathing performed by a healthy person unconsciously is said to be about 12 to 23 breaths per minute. Here, we will assume that the breathing rate of the subject during natural breathing is 22.5 bpm. This breathing rate can be set to any desired rate. The breathing rate can be set, for example, according to the subject. It can also be set according to the subject's gender, physique, health condition, etc.

In the case where the respiratory rate is 22.5 bpm, when the fluctuation data of the _CO2 concentration waveform of natural breathing is frequency converted to generate frequency data, the main frequency component is 0.375 Hz (=22.5 bpm). Therefore, the peak of the _CO2 concentration measured corresponding to 0.375 Hz can be estimated as the time when breathing has taken place, and can be counted as the respiratory rate. However, it is rare for the human body to always breathe at exactly the same time intervals in natural breathing.

Therefore, it is more accurate to grasp the frequency component of the _CO2 concentration waveform that should be grasped as the respiration of natural breathing as a frequency band, not as one specific frequency component. Therefore, as an example, a frequency band can be set in which the low frequency component is 0.275 Hz and the high frequency component is 0.475 Hz (band pass filter processing). And the number of peaks of the _CO2 concentration waveform included in that frequency band is useful for counting the respiration rate due to natural breathing.

Furthermore, by setting such a frequency band, it is also useful to count the number of breaths of natural breathing more accurately. That is, natural breathing may include fluctuations in _CO2 concentration due to factors other than breathing. By setting the frequency band as described above, it becomes possible to eliminate noise appearing as a frequency component on the low frequency side and noise appearing as a frequency component on the high frequency side, and the number of breaths can be counted more accurately. An example of noise appearing as a frequency component on the low frequency side is slow breathing, such as multiple deep breaths. An example of noise appearing as a frequency component on the high frequency side is fast breathing, such as hyperventilation. By eliminating such breathing, the number of breaths due to natural breathing can be counted more accurately.

The frequency band is set as described above, and the peak of _the _CO2 concentration whose maximum value exceeds a predetermined threshold value is counted as one breath for the fluctuation data of the CO2 concentration contained therein. The reason for setting the maximum threshold value here is to filter the data to be grasped as respiration by the value of the _CO2 concentration (the " _CO2 concentration value" includes a calculated value obtained by performing a predetermined calculation process on the value) to make only the data to be grasped as respiration the target data for the respiration rate count. This allows for more accurate measurement (estimation) of the respiration rate. If the above-mentioned set value of the respiration rate is assumed, the threshold value is set, for example, to 0.37 for the filter output (output of the band-pass filter process) normalized by the maximum value of the _CO2 concentration, as shown in FIG. 4. However, the threshold value of the _CO2 concentration set here can be set to any value. The threshold value can be set, for example, according to the subject. It can also be set according to the gender, physique, health condition, etc. of the subject. When the threshold value is set by the absolute value of the _CO2 concentration, for example, 60 to 70% of the peak value of the absolute value of the _CO2 concentration is set as the threshold value.

By using the above-described method for measuring respiration rate, the respiration rate of the subject can be determined (estimated) from fluctuation data of the _CO2 concentration.

According to the experiments of the present inventors, it has been confirmed that there is no significant difference in the measurement accuracy of the respiration rate between the _CO2 concentration fluctuation data measured at rest during the measurement period by the above-mentioned method and the _CO2 concentration fluctuation data measured by turning over in bed to imitate body movement during the measurement period, even when comparing the _CO2 concentration waveform and the output waveform normalized by the maximum value after the above-mentioned band pass filter processing. In other words, it can be seen that the respiration rate measurement device 100 and the above-mentioned respiration rate measurement method are measurement methods that are not easily affected by changes in body movement.

The respiration rate measurement can be completed by the above steps. As an example, the measurement can be completed by pressing the measurement end button on the respiration rate measurement device 100. However, to ensure even greater accuracy, the following further processing can also be performed.

That is, it is determined whether or not noise-type body movement that is a factor in fluctuations in the CO ₂ concentration caused by something other than the subject's breathing has been detected (step S4).

The various sensors of the noise detection sensor 120 detect the following physical quantities and transmit the detection data to the microcomputer 130 (step S5).
・Microphone element: Sounds emitted when the subject's body movements change, or when they cough, yawn, talk, etc. ・Acceleration sensor: Vibrations emitted when the subject's body movements change, or when they cough, yawn, talk, etc. ・Humidity sensor: Humidity of the breath when the subject coughs, sneezes, yawns, talks, etc. ・Pressure sensor: Pressure of the breath when the subject coughs, sneezes, yawns, talks, etc.

When the microcomputer 130 receives the detection data from the noise detection sensor 120, the determination unit 131b performs noise removal (step S6), and then the determination unit 131b determines the respiratory rate using FFT analysis, wavelet analysis, AI, etc. (step S7). At this time, the method of determining the respiratory rate after performing noise removal differs depending on the mode of the noise detection sensor 120.

That is, when the noise detection sensor 120 is a microphone or an acceleration sensor, if a sound or vibration that is a noise type body movement is detected, the respiration waveform of the _CO2 concentration data detected by the _CO2 sensor during that time is not counted as the respiration rate, thereby removing the noise.Then, the determination unit 131b regards the _CO2 concentration fluctuation data detected by the _CO2 sensor other than the period detected by the microphone or acceleration sensor as respiration, and determines the respiration rate using FFT analysis, wavelet analysis, AI, etc.In this way, when the noise detection sensor 120 is a microphone or an acceleration sensor, the determination unit 131b determines the respiration rate of the subject by using the fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110 during the period in which the noise type body movement is detected by the noise detection sensor 120 as noise data that is not counted.

On the other hand, when the noise detection sensor 120 is a humidity sensor or a pressure sensor, even if the humidity or pressure that becomes noise data is detected, the _CO2 concentration fluctuation data detected by the _CO2 sensor 110 is regarded as a respiration waveform to be used for measuring the respiration rate, and the respiration rate is measured. Then, the waveform pattern of the detection data of the humidity sensor or pressure sensor is confirmed, and the respiration rate is estimated from the waveform pattern by FFT analysis, wavelet analysis, adaptive filter, AI, etc. In this way, when the noise detection sensor 120 is a humidity sensor or a pressure sensor, the determination unit 131b determines the respiration rate by estimation based on the analysis result of the waveform pattern of the _CO2 concentration fluctuation data detected by the _CO2 sensor 110 and the waveform pattern of the detection data related to the noise-type body movement detected by the noise detection sensor 120.

If no noise-type body movement of the subject is detected in step S4, the determining unit 131b determines in step S3 that the respiratory rate estimated based on the fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110 is the respiratory rate as it is.

In this manner, in this embodiment, the respiratory rate of the subject is estimated from the detection data of the _CO2 sensor 110. Then, when the noise type body movement of the subject occurring during the measurement period of the _CO2 sensor 110 is detected, the _CO2 concentration data generated by the noise type body movement among the detection data of the _CO2 sensor 110 is used as noise data that is not counted as the respiratory rate, and the final respiratory rate of the subject P is determined. Therefore, even if the noise type body movement occurs due to the change in the body movement of the subject P or the operation of the cardiopulmonary function other than the breathing of the subject, such as coughing, sneezing, yawning, and talking, the noise associated with the noise type body movement is removed before the respiratory rate of the subject is determined, so that the influence of the noise type body movement can be reduced and the respiratory rate can be grasped with high accuracy.

Second flow (Figure 5)

The method of measuring the respiratory rate using the respiratory rate measuring device 100 according to this embodiment is not limited to the flowchart shown in FIG. 3, and can be performed, for example, as shown in the flowchart in FIG. 5.

Measurement is started, for example, by pressing the measurement start button of the respiration rate measuring device 100 ("START" in FIG. 5). At the same time as the measurement starts, a timer that measures the measurement time is operated, and the _CO2 sensor 110 detects the fluctuation of the _CO2 concentration contained in the subject's breath (step S11). The fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110 is continuously transmitted to the microcomputer 130 (step S12).

The determination unit 131b of the microcomputer 130 continues to detect whether the received fluctuation data of the _CO2 concentration includes data indicating noise-type body movement (step S13). If the determination unit 131b determines that no noise-type body movement is detected, it determines the respiratory rate from the fluctuation data of the _CO2 sensor 110 (step S14). Here, "determining the respiratory rate" means that one or more breaths can be counted.

On the other hand, if a noise-type body movement of the subject is detected in step S13, the process returns to step S11 and repeats the above steps. Then, the measurement of the respiratory rate based on the fluctuation data of the _CO2 concentration is continued until the respiratory rate can be determined based on the fluctuation data without the detection of the noise-type body movement. Note that, when the noise-type body movement of the subject is detected in step S14 and the process returns to step S1, the timer may be reset.

After the respiration rate is determined from the fluctuation data of the _CO2 sensor 110 in step S14, it is then determined whether or not to continue measuring the respiration rate (step S15). The criteria for determining whether or not to continue the measurement (measurement termination criteria) can be set in various ways, and the following are examples.
When a "certain number of breaths" is reached (e.g. 100)
When a "specific measurement time" is reached (e.g., 1 minute, 1 hour, 1 day, 1 week, unlimited)
When a "specific operation" is performed on the respiration rate measuring device 100 (for example, when the measurement end button of the respiration rate measuring device 100 is pressed, when the respiration rate measuring device 100 is turned off, etc.)

If the measurement end criterion is reached in step S15, the respiratory rate measurement ends ("END" in Figure 5). If the measurement end criterion is not reached in step S15, the process returns to step S11 and the above steps are repeated. The measurement is repeated until the measurement end criterion is reached in step S15.

5, the determination unit 131b determines the respiration rate by counting the number of peaks of the fluctuation data of the _CO2 concentration detected by the _CO2 sensor only when there is no noise-type body movement. Therefore, it is not necessary to perform FFT analysis or wavelet analysis on the detection data related to the noise-type body movement, or to remove noise, so that the respiration rate of the subject can be easily measured with fewer steps.

Also, various respiratory rate measurements can be performed depending on the measurement termination criteria set in step S15. As an example, if a "specific measurement time" is selected as the measurement termination criterion and set to "one minute," it is possible to measure the one-minute respiratory rate during normal breathing. This is considered to be an appropriate measurement for grasping the respiratory rate from a clinical perspective, and is suitable for grasping the one-minute respiratory rate more accurately, for example, in emergency and disaster sites where facilities are inadequate, and in evacuation shelters during disasters.

Furthermore, if "specific action" is selected and set to "when the measurement end button of the respiration rate measuring device 100 is pressed," the respiration rate can be measured continuously. This is suitable, for example, for continuously measuring the respiration rate of patients recuperating in hospitals or at home, and for finding signs of abnormalities in their physical condition.

Next, an example of the respiration rate determination operation (step S14) in the flowchart for measuring the respiration rate using the respiration rate measurement device shown in Figure 5 will be explained using Figures 6 and 7 as examples.

Here, two examples of methods for measuring respiratory rate will be explained. One is a method in which the current time is used as the reference time to measure the number of breaths occurring from the present time, as shown in Figure 6. The other is a method in which the current time is used as the reference time to measure the number of breaths going back to the past, as shown in Figure 7. For ease of explanation, the following will explain an example in which the respiratory rate is measured for 60 seconds (one minute) during normal breathing.

First example of respiratory rate measurement (Figure 6)

The origin "0" at the left end of the number lines in Figures 6A, 6B, and 6C is the start of measurement. As shown in Figure 6A, if no noise-type body movement of the subject, such as coughing, yawning, or talking, is detected, the respiratory rate measured during the first 60-second measurement period T1 from the start of measurement is determined as the subject's respiratory rate as is. Then, the subject's respiratory rate is measured in the same manner during the next 60-second measurement period T2.

On the other hand, if noise-type body movement is detected for a noise occurrence time n (s) (e.g., 15 seconds) within one minute of starting measurement, the respiration rate is measured for 60 seconds from the end of the noise-type body movement occurrence period Tn, as shown in Figure 6B, and if no noise-type body movement is detected during that time, the respiration rate measured in the 60-second measurement period T1 from the end of the noise-type body movement is determined to be the subject's respiration rate. With this measurement method, it is possible to measure the respiration rate of normal breathing over one continuous minute. In addition, because the period in which noise-type body movement occurs can be identified, it is also possible to confirm what happened to the patient at that time.

Also, if a noise-type body movement is detected within one minute after the start of measurement for a noise occurrence time n(s) (for example, 15 seconds), the subject's respiration rate may be determined from the measurement data of the respiration rate for a period of 60 seconds plus 15 seconds, which is the noise occurrence time n(s) during which the noise-type body movement was detected, as shown in Fig. 6C. In this case, the sum of the time _T1a from the start of measurement until the noise-type body movement occurs and the time _T1b from the end of the noise-type body movement until the measurement of the respiration rate ends is T1, that is, one minute (60 seconds). In this measurement method, the respiration rate for one minute is measured after removing the section in which the noise-type body movement was detected.

Second example of respiratory rate measurement (Figure 7)

The origin "0" at the right end of the number lines in Figures 7A, 7B, and 7C is the current time. In this example, the current time is set as the reference time for measuring the respiration rate, and the respiration rate is measured by tracing back from the current time to past respiration rate measurement data. For example, by looking at the respiration rate measurement data for the past one minute (60 seconds) from the current time, if no noise-type body movement of the subject, such as coughing, yawning, or talking, is detected during the measurement period, the respiration rate measured during the past measurement period T1, the first 60 seconds from the current time, which is the measurement reference time, is determined to be the subject's respiration rate as is, as shown in Figure 7A.

On the other hand, if noise-type body movement is detected for a noise occurrence time n(s) (e.g., 15 seconds) within the first minute from the current time, the breathing rate is measured for 60 seconds from the point at which the noise-type body movement detection ends, as shown in Figure 7B, and if no noise-type body movement is detected during that time, the breathing rate measured during the 60-second measurement period T1 from the point at which the noise-type body movement ends is determined to be the breathing rate of the subject. With this measurement method, the breathing rate of normal breathing can be measured for one continuous minute without interruption. In addition, because the period in which the noise-type body movement occurs can be identified, it is also possible to confirm what happened to the patient at that time.

Also, if a noise-type body movement of a noise occurrence time n(s) (for example, 15 seconds) is detected within the first minute from the current time, the respiration rate of the subject may be determined from the measurement data of the respiration rate of the past time, which is 60 seconds plus 15 seconds, which is the noise occurrence time n(s) when the noise-type body movement was detected, as shown in Fig. 7C. In this case, the sum of the time _T1a from the start of measurement to the occurrence of the noise-type body movement and the time _T1b from the end of the noise-type body movement to the end of the measurement of the respiration rate is 1 minute (60 seconds). In this measurement method, the respiration rate is measured for 1 minute after removing the section in which the noise-type body movement was detected.

In this manner, in this embodiment, the respiration rate can be easily determined by counting the respiration rate from the present time, which is the measurement reference time, to a predetermined time in the future or past (60 seconds). That is, the determination unit 131b can accurately determine the respiration rate by counting the number of peaks of the fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110 only when no noise-type body movement occurs within a predetermined time in the future or past from the measurement reference time.

The noise detection sensor 120 detects CO _２2 Example of measuring respiration rate when using a sensor (Figure 8)

A method of measuring the respiration rate by the respiration rate measuring device 100 when the noise detection sensor 120 is a noise-detecting _CO2 sensor will be described with reference to FIG.

In this embodiment, as shown in Fig. 8, the _CO2 sensor 110 and the noise detection sensor 120, which is a _CO2 sensor, each acquire fluctuation data of the _CO2 concentration. When a microphone element or the like is used as the noise detection sensor 120, a noise type fluctuation is detected by a physical quantity different from the fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110. On the other hand, the example of Fig. 8 is an example in which a noise type fluctuation is detected by measuring the same physical quantity ( _CO2 concentration). The fluctuation data is input to the determination unit 131b via the data processing unit 137.

The data processing unit 137 has a function of canceling (offsetting) artifacts contained in the detection data of both

sensors

110 and 120. For this purpose, the data processing unit 137 can hold statistical properties such as the average value and variance value of each artifact, and the correlation value between both artifacts as data. Then, by using this to offset both artifacts, the artifacts contained in the detection data of the CO ₂ sensor 110 are removed, and clean CO ₂ concentration fluctuation data for measuring the respiration rate is obtained and output to the determination unit 131b. In this case, the data processing unit 137 can be configured with an adaptive filter or AI that offsets both artifacts. Note that a bandpass filter may be provided between both

sensors

110 and 120 and the data processing unit 137 to extract frequency components for measuring the respiration rate from the detection data.

Here, the artifact is a change in _CO2 that varies due to factors other than respiration. Specifically, the _CO2 concentration variation data on which the measurement data of the respiration rate is based includes artifact A, which is _CO2 that varies due to factors other than respiration, and the detection data of the noise detection sensor 120 includes artifact B, which is _CO2 that varies due to factors other than respiration. This artifact B is data as noise-type body movement. The artifacts A and B may be _CO2 detected due to the same factor other than respiration, or _CO2 detected due to different factors. The artifacts A and B depend on the placement locations of the

sensors

110 and 120. When the artifacts A and B are _CO2 detected based on different factors, the correlation between these artifacts A and B becomes large when the placement locations of the

sensors

110 and 120 are close to each other. Therefore, the data processing unit 137 can transmit fluctuation data of the substantial CO2 concentration contained in the subject's breath to the determination unit _131b by removing artifact A, which is a change in _CO2 that fluctuates due to factors other than breathing, from the detection data of the _CO2 sensor 110 based on the correlation between artifacts A and B contained in the detection data of these

sensors

110 and 120. On the other hand, when artifacts A and B are _CO2 detected based on the same factor, it is possible to remove artifact A contained in the detection data of the _CO2 sensor 110 by making the data processing unit 137 function as a differential amplifier. Then, the determination unit 131b calculates the subject's breathing rate based on the fluctuation data.

In this manner, in this embodiment, the determination unit 131b determines the respiration rate of the subject based on the fluctuation data of the substantial _CO2 concentration of the _CO2 sensor 110 obtained by canceling the artifacts contained in the detection data of both

sensors

110 and 120 in the data processing unit 137. That is, the data processing unit 137 performs data processing to cancel the artifact A contained in the detection data of the CO2 sensor 110, which is the _CO2 sensor for measuring respiration rate, by an adaptive filter or AI based on the data of the artifact B contained in the fluctuation data of the _CO2 concentration of the external environment in the noise detection sensor 120, and then extracts the fluctuation data of _the substantial _CO2 concentration used to measure the respiration rate of the subject. Then, the determination unit 131b determines the respiration rate of the subject based on the output data processed by the data processing unit 137. Therefore, even if the occurrence of noise-type body movement is detected from fluctuation data of _CO2 concentration in the external environment, the subject's respiratory rate can be accurately determined by performing data processing to cancel artifacts contained in the detection data of both

sensors

110, 120.

Application examples of the respiration rate measuring device 100

Next, an application example of the respiratory rate measuring device 100 of this embodiment will be described with reference to the drawings. FIG. 9 is an explanatory diagram showing one aspect of the respiratory rate measuring device 100 according to this embodiment, and FIG. 10, FIG. 11, and FIG. 12 are explanatory diagrams showing other aspects of the respiratory rate measuring device 100 according to this embodiment.

Considering the miniaturization and real-time nature of the device, the respiration rate measuring device 100 uses a low-power, high-sampling-grade equivalent carbon dioxide sensor as the _{CO2 sensor 110. In order to continuously measure the fluctuations in the concentration of CO2 contained in the breath of the subject P, the respiration rate measuring device 100 uses the CO2} _sensor ₁₁₀ as a wearable sensor that can be attached to an appliance located around the oral cavity of the subject P.

For example, as shown in Fig. 9, the respiration rate measuring device 100 is attached to the inside of a sanitary mask M1 as a "gear" or "head gear" worn by the subject P, with the sensor body 105 attached via an attachment member 150. In this way, by attaching the sensor body 105 including the _CO2 sensor 110 to the inside of the sanitary mask M1, measurement data of the concentration of _CO2 contained in the breath of the subject P measured by the _CO2 sensor 110 is transmitted to the microcomputer 130. Then, the microcomputer 130 executes a process of determining the respiration rate of the subject P based on the detection data of the _CO2 sensor 110 and the detection data of the noise detection sensor 120.

10, the respiration rate measuring device 100 can also be used by attaching the sensor body 105 to the inside of a medical oxygen mask M2 as a "bracing" or "head bracing" worn by the subject P in a medical field with an attachment member 150. In this way, by attaching the sensor body 105 to the inside of the oxygen mask M2 covering the oral cavity of the patient who is the subject P, the _CO2 concentration contained in the breath of the subject P can be measured by the _CO2 sensor 110. For this reason, the microcomputer 130 similarly executes a process of determining the respiration rate of the subject P based on the measurement data of the _CO2 sensor 110 and the detection data detected by the noise detection sensor 120.

Furthermore, in the respiration rate measuring device 101, as shown in Fig. 11A, the mounting member for mounting the sensor body 105 including the _CO2 sensor 110 and the noise detection sensor 120 may be a hook 151 that can be engaged with the tube M3a. By using the hook 151 as the mounting member for mounting the sensor body 105 in this way, as shown in Fig. 11B, the sensor body 105 can be mounted to the tube M3a near the nasal cavity of a heated humidifier (example of the product name is "Nasal High Flow") M3 by the hook 151. Therefore, by measuring the _CO2 concentration contained in the exhaled air near the nasal cavity of the subject P with the _CO2 sensor 110, the microcomputer 130 similarly executes the process of determining the respiration rate of the subject P.

In addition, as shown in FIG. 12A, the respiration rate measuring device 102 can be configured such that the attachment member for attaching the sensor body 105 is a necklace member 152 as an "orthosis" or "body orthosis" that is hung around the neck of the subject P. The necklace member 152 may be configured to have a plurality of sensor bodies 105 attached at a predetermined interval. By configuring the respiration rate measuring device 102 in this way, the CO 2 sensor 110 of the sensor body 105 can measure the concentration of CO ₂ contained in the breath of the subject P during natural breathing, whether the subject P is sleeping as shown in FIG. 12B, standing and facing forward as shown in FIG. 12C, or standing and facing sideways as shown in FIG. 12D. Therefore, in the same manner, the microcomputer 130 can execute the process of determining _the respiration rate of the subject P.

In this way, the respiration

rate measuring devices

100, 101, and 102 use a small equivalent carbon dioxide type sensor as the _CO2 sensor 110 that continuously measures the fluctuations in the concentration of _CO2 contained in the breath of the subject P. Therefore, by easily attaching it to various tools and devices that the subject P covers around the oral cavity, it is possible to accurately detect the fluctuations in the concentration of _CO2 with low power consumption and high sampling grade.

Functional configuration of a system using a respiration rate measuring device

Next, the functional configuration of system 1 using a respiratory rate measurement device will be described with reference to the drawings. FIG. 13 is a block diagram showing the functional configuration of a system according to an embodiment of the present disclosure. Note that FIG. 13 focuses only on the server device 10, data storage unit 20, administrator terminal 30, and respiratory rate measurement device 100 provided in system 1, and describes in detail the functions of each component.

In the system 1 of this embodiment, a server device 10 is connected to a data storage unit 20, an administrator terminal 30, a subject terminal 40, and a respiration rate measuring device 100 via a network 2. As a result, the server device 10 stores in the data storage unit 20 a database of fluctuation data of the _CO2 concentration contained in the exhaled breath received from the respiration rate measuring device 100 worn by the subject P and detection data related to noise-type body movements that are fluctuation factors of the _CO2 concentration caused by factors other than the subject's breathing, while allowing an administrator using the administrator terminal 30 to manage the health condition of each subject.

As shown in FIG. 13, the server device 10 includes a communication unit 11, an operation unit 12, a display unit 13, a control unit 14, a ROM 15, and a RAM 16. The server device 10 configures a "respiratory rate management server" having multiple functional units by the control unit 14 executing a "program," and performs information processing using the multiple functional units.

The communication unit 11 has a function as an interface for transmitting and receiving data to and from the outside via the network 2. In this embodiment, the communication unit 11 is configured to be able to acquire fluctuation data of the _CO2 concentration contained in the subject's breath and detection data related to the noise-type body movement of the subject.

The operation unit 12 has a function of inputting a predetermined command to the control unit 14, which is a data input device such as a keyboard, mouse, or touch panel, to operate the server device 10 as appropriate. The display unit 13 has a function of outputting the calculation results by the control unit 14 and information from the data storage unit 20, which is a database, on a screen display, and is composed of, for example, a liquid crystal screen. The display unit 13 is also capable of displaying a graph showing the fluctuation of the concentration of _CO2 contained in the breath of a subject wearing the respiration rate measuring device 100 and a trend of noise data.

The control unit 14 has a function of controlling the operation of each component of the server device 10 by one or more processors executing various programs stored in the ROM 15. The control unit 14 also has a function of storing the necessary data, etc., in the RAM 16, which temporarily stores the necessary data, etc., as appropriate when executing these various processes. Therefore, the control operations by the control unit 14 can access the ROM 15, RAM 16, and data storage unit 20, display data on the display unit 13, operate the operation unit 12, and send and receive various information via the network 2 using the communication unit 11 as an interface when communicating with the outside world.

13, the control unit 14 includes a receiving unit 14a, a determining unit 14b, a transmitting unit 14c, and a generating unit 14d. The receiving unit 14a has a function of controlling reception of various data from the data storage unit 20, the administrator terminal 30, and the respiration rate measuring device 100 via the communication unit 11. The receiving unit 14a is controlled to receive fluctuation data of the _CO2 concentration contained in the detected exhaled breath of the subject P and detection data related to the noise type body movement of the subject, which are transmitted from the respiration rate measuring device 100 to the server device 10 at predetermined time intervals.

The determination unit 14b has a function of performing a determination operation required when executing various operations of the server device 10. For example, the determination unit 14b determines whether various data is transmitted/received between the administrator terminal 30 and the respiration rate measuring device 100 via the communication unit 11 of the server device 10. In this embodiment, the determination unit 14b has a function of determining the respiration rate of the subject P based on fluctuation data of the _CO2 concentration contained in the exhaled breath of the subject P measured by the _CO2 sensor 110 of the respiration rate measuring device 100 and detection data related to noise-type body movement detected by the noise detection sensor 120.

The transmission unit 14c has a function of controlling the transmission of various data to the data storage unit 20, the administrator terminal 30, and the respiratory rate measurement device 100 via the communication unit 11. The transmission unit 14c has a function of transmitting the judgment result of the judgment unit 14b to the administrator terminal 30.

The generating unit 14d has a function of performing arithmetic processing on various data to generate data. For example, the generating unit 14d can generate display data. Examples of the display data include a trend graph of fluctuation data of the _CO2 concentration contained in the breath of the subject detected by the respiration rate measuring device 100 and a trend graph of fluctuation of detection data related to the noise-type body movement of the subject detected by the noise detection sensor 120. The display data generated by the generating unit 14d can be transmitted to an external device such as the administrator terminal 30 through the communication unit 11. In the external device, the display data can be displayed on a display unit such as a display screen.

The data storage unit 20 is an external storage device capable of storing various data. In this embodiment, the data storage unit 20 functions as a database for storing, for each subject, detection data including fluctuation data of the _CO2 concentration contained in the breath of the subject P measured by the _CO2 sensor 110 of the respiration rate measuring device 100, and detection data related to noise-type body movement detected by the noise detection sensor 120. In addition, the data storage unit 20 is updated every time the detection data of the _CO2 sensor 110 and the detection data related to noise-type body movement are updated.

The administrator terminal 30 is a terminal device used by the administrator, and includes a communication unit 31, an operation unit 32, a display unit 33, a control unit 34, and a storage unit 35, as shown in Fig. 13, so as to perform necessary operations such as transmission and reception of various information and calculation processing. The administrator terminal 30 is configured to access the server device 10, so as to display on the display unit 33 data for display related to detection data, such as fluctuation data of the _CO2 concentration contained in the exhaled breath of the subject P wearing the respiration rate measuring device 100 and a trend graph of the fluctuation data.

In this way, in the system 1 of this embodiment, the server device 10 is connected to the data storage unit 20, the administrator terminal 30, and the respiratory rate measuring device 100 via the network 2. The server device 10 determines the respiratory rate of each subject based on the detection data received from the subjects and the detection data related to noise-type body movements, and controls the execution of a health management application service that manages the health condition of each subject. As a result, the server device 10 can comprehensively manage the physical condition of the subject wearing the respiratory rate measuring device 100 who is the subject of health management.

The server device 10 of the system 1 may be realized by software or by hardware. When realized by software, various functions can be realized by the control unit 14, which serves as a CPU, executing a program that operates the system 1. The program of this embodiment may be stored in the ROM 15 built into the server device 10, or may be stored in a non-transitory computer-readable recording medium.

The server device 10 of the system 1 may also be realized by reading out a program stored in a storage device serving as an external storage device, using so-called cloud computing. In this case, the _CO2 concentration fluctuation data obtained from the CO2 sensor 110 of the respiration rate measuring device ₁₀₀ and the detection data related to noise-type body movements obtained from the noise detection sensor 120 may be stored in the server device 10 on the cloud, and data analysis may be performed using time series analysis, cluster analysis, artificial intelligence, etc.

Functions and Effects of the Embodiments

Next, the operation and effects of the respiratory rate measuring device 100 and system 1 according to this embodiment will be described.

(1) The peak of the CO2 concentration can be detected in the same manner for the fluctuation of the _CO2 concentration contained in the breath of the subject detected by the _CO2 sensor at rest as shown in Fig. 14A and the fluctuation of _the _CO2 concentration at the time of body movement as shown in Fig. 14B. In contrast, the peak of the acceleration fluctuation of the subject detected by the acceleration sensor can be detected at rest as shown in Fig. 15A, whereas the peak of the acceleration fluctuation varies during body movement as shown in Fig. 15B. Therefore, during body movement, the fluctuation of the acceleration of the subject detected by the acceleration sensor is significantly different from that at rest, and the peak of the _CO2 concentration cannot be detected in the same manner as during rest.

Therefore, the inventors conducted extensive research to solve the problem of measuring respiratory rate without being affected by changes in body movement. They focused on the fluctuations in the _CO2 concentration in the subject's breath and discovered the possibility of continuously monitoring respiratory status by monitoring changes in _CO2 concentration using a small wearable sensor.

(2) The inventors of the present invention have conducted extensive research to solve the above-mentioned problems, and have found that the respiration rate estimated based on the number of times that the output data obtained by processing the measurement data related to the fluctuation of the _CO2 concentration of the equivalent carbon dioxide type _CO2 sensor with a bandpass filter exceeds a predetermined threshold has a correlation with the actual respiration rate of the subject. For this reason, in this embodiment, the equivalent carbon dioxide type _CO2 sensor 110 is used as a small wearable sensor. Then, by counting the number of times that the output data obtained by processing the measurement data of the equivalent carbon dioxide type _CO2 sensor 110 with a bandpass filter exceeds a predetermined threshold, the respiration rate of the subject can be easily estimated with high accuracy.

(3) The respiration rate measuring device 100 can determine the respiration waveform pattern of the subject by monitoring the fluctuation data of the _CO2 concentration contained in the subject's breath. Therefore, not only the respiration rate of the subject but also biological information related to respiration such as respiration depth (amplitude) and respiration interval can be grasped, so that the health condition or disease state of the subject can be grasped from the respiration waveform pattern of the subject.

For example, assuming that the normal breathing waveform pattern shown in Figure 16A is 16 to 20 breaths per minute, if a breathing waveform pattern during tachypnea of 25 or more breaths per minute as shown in Figure 16B is detected, this may suggest a connection to the subject's fever or excited state.

As shown in Figure 16C, if a respiratory waveform pattern is detected in which the respiratory rate is the same as normal but the amplitude of the respiratory waveform is large and the depth of breathing is deep, this may suggest an association with anemia or hyperthyroidism in the subject.

As shown in Figure 16D, if a breathing waveform pattern is detected in which the breathing rate is normal but the amplitude of the breathing waveform is small and the breathing depth is shallow, this may suggest an association with paralysis of the subject's respiratory muscles or intoxication with sleeping pills or morphine.

As shown in Figure 16E, when a bradypnea (slow breathing) pattern of 9 breaths/min or less is detected, this may indicate an association with increased intracranial pressure or bronchial obstruction in the subject.

As shown in Figure 16F, if a respiratory waveform pattern is detected in which the respiratory rate and depth are increased compared to normal, this may suggest that the subject is exercising, has a high fever, or is suffering from neurosis.

The respiration rate measuring device 100 can detect respiration waveform patterns. Therefore, for example, as shown in FIG. 17A, when a Cheyne-Stokes type respiration waveform pattern is detected, in which the depth and rate of breathing gradually increase, then gradually decrease, and finally apnea occurs, this may suggest that the subject is in the final stages of brain disease, uremia, heart disease, poisoning, or various other diseases.

As shown in Figure 17B, if a Biot-type respiratory waveform pattern is detected in which the same shallow breathing is repeated four or five times, followed by apnea, and this cycle is repeated, this may suggest that the subject has a brain tumor, meningitis, or spinal cord injury.

As shown in Figure 17C, if a Kussmaul-type respiratory waveform pattern is detected, which is a periodic waveform with sustained, extremely loud breathing and high-pitched noise, this may indicate that the subject is in a diabetic or uremic coma.

(4) Related techniques for monitoring respiratory status include, for example, a method using thoracic impedance in combination with an ECG (Electrocardiogram) and a method for measuring respiratory rate by analyzing pulse waves. However, the method using thoracic impedance in combination with an ECG and the method using pulse waves are significantly affected by changes in body movement, and the subject needs to be in a resting state to measure the respiratory rate. In addition, in clinical settings, capnometers that measure the _CO2 concentration in exhaled air are widely used to monitor respiratory status, but due to their lack of portability, they are difficult to apply to continuous monitoring of elderly people in evacuation shelters, etc.

In addition, when the respiration rate measuring device 100 determines the respiration rate from the detection data of the _CO2 sensor 110, in order to reduce the influence of _CO2 concentration changes caused by factors other than respiration, the detection data of the _CO2 sensor 110 is subjected to bandpass filter processing. However, when the subject breathes while coughing, yawning, talking, etc., the _CO2 concentration changes caused by coughing, yawning, talking, etc. may have frequency components close to respiration. Therefore, even if bandpass filter processing is performed on the detection data of the _CO2 sensor 110, breathing accompanied by coughing, yawning, talking, etc., which is a noise type body movement that hinders accurate determination of the subject's respiration rate, is not removed, so the subject's respiration rate may not be determined to be an appropriate number.

For this reason, the respiration rate measuring device 100 is provided with a noise detection sensor 120 near the _CO2 sensor 110 to detect noise-type body movements that are a factor in fluctuations in the _CO2 concentration caused by factors other than the subject's breathing. By providing the noise detection sensor 120 in this way, the respiration rate measuring device 100 determines the subject's respiration rate after removing the respiration rate accompanied by coughing, yawning, talking, etc. as noise data. This makes it possible to more accurately determine the subject's respiration rate by removing the effects of cardiopulmonary functions other than breathing, such as coughing, yawning, and talking, in addition to changes in the subject's body movements.

In particular, when a microphone or an acceleration sensor is used as the noise detection sensor 120, the respiration rate measuring device 100 performs noise removal from the fluctuation data of the _CO2 concentration detected by the _CO2 sensor 110, and then determines the respiration rate after not counting, as the respiration rate, detection data during a period in which noise-type body movement is detected by the noise detection sensor 120. By operating in this manner, the respiration rate measuring device 100 can reduce erroneous detection of the respiration rate due to the influence of cardiopulmonary actions other than breathing, such as coughing, yawning, and talking.

Furthermore, when a humidity sensor or a pressure sensor is used as the noise detection sensor 120, the respiration rate measuring device 100 determines the respiration rate after estimation based on the analysis results of the waveform pattern of the measurement data of the _CO2 sensor 110 and the waveform pattern of the detection data related to the noise-type body movement detected by the noise detection sensor 120. By operating in this manner, the respiration rate measuring device 100 can similarly reduce erroneous detection of the respiration rate due to the influence of cardiopulmonary movements other than breathing, such as coughing, yawning, and talking.

In this way, by applying the respiration rate measuring device 100, the system 1, and the program of this embodiment, the respiration rate of the subject can be accurately determined without being affected by noise-type body movements such as changes in the subject's body movements and cardiopulmonary functions other than breathing, such as coughing, yawning, and talking. In particular, the respiration rate measuring device 100 uses a small _CO2 sensor of the equivalent carbon dioxide type as a means for detecting fluctuation data of the _CO2 concentration contained in the subject's breath. Therefore, the CO2 sensor can be easily attached to a sanitary mask or face shield that covers the subject's mouth area, or various medical devices such as an _oxygen mask that are used around the subject's mouth area, making it possible to measure the subject's respiration rate in a wearable and versatile manner.

(5) The respiration rate measuring device 100 uses a small wearable sensor as the _CO2 sensor 110 that detects the variation of the _CO2 concentration contained in the breath of the subject. Therefore, for example, in order to respond to a sudden change in the condition of the elderly or the like in an evacuation shelter during a disaster, the sensor body 105 including the _CO2 sensor 110 can be attached to the sanitary mask or face shield of the elderly or the like who will be the subject, and the respiration rate of the subject can be easily determined and the health condition of each subject can be managed. In particular, even in an evacuation shelter in a depopulated area where medical resources are insufficient, a wide range of vital information related to breathing, such as the subject's respiration rate, respiration rhythm, depth, and respiration pattern, can be remotely monitored by using a wearable sensor that can be easily attached, making it possible to appropriately manage the health condition of subjects such as the elderly.

Variations

The above embodiment is an example of one aspect of the present disclosure. The above embodiment can also be implemented as the following exemplary modified examples.

In the above embodiment, the respiration rate measuring device 100 is exemplified as including a sensor body 105 and a microcomputer 130. However, a sensor module including a microcomputer can be used as the sensor body 105. In this case, the microcomputer 130 can be integrated with the sensor body 105. That is, the sensor body 105 can be integrated with the microcomputer 130 that processes the measured data. In this case, the connection line 140 can be omitted.

In the above embodiment, the microcomputer 130 is exemplified as having an operation unit 133 and a display unit 134. However, these are not essential components of the microcomputer 130 and can be omitted. In this case, the functions corresponding to the operation unit 133 and the display unit 134 may be provided in a computing device such as a smartphone or tablet. This means that the microcomputer 130 does not necessarily have to be configured as a single hardware device. Therefore, the microcomputer 130 can be configured as one or more hardware devices.

Although each embodiment of the present disclosure has been described in detail, it will be readily apparent to those skilled in the art that many modifications are possible that do not substantially depart from the novelties and effects of the present disclosure. Therefore, all such modifications are intended to be included within the scope of the present disclosure.

For example, a term that is described at least once in the specification or drawings together with a different term having a broader or synonymous meaning may be replaced with that different term anywhere in the specification or drawings. In addition, the configuration and operation of the respiration rate measuring device are not limited to those described in one embodiment of the present disclosure, and various modifications are possible.

Reference Signs List 1 System 2 Network 10

Server device

11, 31

Communication unit

12, 32

Operation unit

13, 33

Display unit

14, 34 Control unit

14a Receiving unit

14b Determination unit

14c Transmitting unit

14d Generation unit 15 ROM
16 RAM
20 Data storage unit 30 Administrator terminal 35 Storage unit 100 Respiration rate measuring device 105 Sensor body 110 _CO2 sensor (first sensor device)
120 Noise detection sensor (second sensor device)
130 Microcomputer 131 Control section

131a Receiving section

131b Determination section

131c Transmitting section 132 Communication section 133 Operation section 134 Display section 135 ROM
136 RAM
137 Data processing unit 140 Connection line

140a Connection line

140b Connection line 150 Connection member 151 Hook 152 Necklace member (wearable equipment, body equipment)
M1 Hygienic mask (wearable device, head device)
M2 Oxygen Mask (Wearable Equipment, Headgear)
M3 Heated Humidifier (Wearable Device, Head Device)
M3a Tube

Claims

In a respiration rate measuring device for measuring respiration rate,
A first sensor device for acquiring fluctuation data of CO2 concentration in the subject's continuous exhaled breath;
a second sensor device that detects noise-type body movements of the subject occurring during a measurement period of the first sensor device;
and a determination unit that excludes a portion of the variation data corresponding to an occurrence time of the noise-type body movement from the variation data and determines the respiratory rate based on a number of peaks in the variation data.
Respiratory rate measuring device.
the determining unit performs frequency conversion on the variation data, and measures the respiratory rate based on the number of times that the variation data corresponding to a predetermined frequency band including the natural breathing of the subject exceeds a predetermined threshold.
2. The respiration rate measuring device according to claim 1.
the determination unit determines the respiratory rate by counting the number of peaks in the variation data excluding a portion of the variation data corresponding to an occurrence time of the noise-type body movement.
2. The respiration rate measuring device according to claim 1.
the determination unit determines the respiratory rate by estimation based on an analysis result of a waveform pattern of the variation data and a waveform pattern of the detection data of the noise-type body movement of the second sensor device.
2. The respiration rate measuring device according to claim 1.
the determination unit determines the respiratory rate by counting the number of peaks in the variation data when the noise-type body movement does not occur within a predetermined time period.
2. The respiration rate measuring device according to claim 1.
The second sensor device is at least one of a microphone element, an acceleration sensor, a humidity sensor, a pressure sensor, and a CO2 sensor.
2. The respiration rate measuring device according to claim 1.
Further, the respiration rate measuring device includes a communication unit that transmits the variation data and the detection data of the noise-type body movement.
2. The respiration rate measuring device according to claim 1.
The noise type body movement is at least one of a change in the body movement of the subject or a cardiopulmonary function other than breathing of the subject.
2. The respiration rate measuring device according to claim 1.
The first sensor device is a CO2 sensor of the equivalent carbon dioxide type;
2. The respiration rate measuring device according to claim 1.
The first sensor device is a wearable sensor that can be worn by the subject.
2. The respiration rate measuring device according to claim 1.
Furthermore, the respiration rate measuring device includes an attachment member for attaching to at least one of a head attachment and a body attachment worn by the subject.
2. The respiration rate measuring device according to claim 1.
In a respiration rate measuring device equipped with a CO2 sensor,
Obtaining fluctuation data of CO2 concentration in the subject's continuous exhaled breath by the CO2 sensor;
generating frequency data by frequency-converting the fluctuation data;
The method includes: determining, as a respiration rate, a number of peaks of the CO2 concentration exceeding a predetermined threshold value for the fluctuation data of the CO2 concentration corresponding to a predetermined frequency band including the natural respiration of the subject, among the frequency data;
How to measure respiratory rate.
A program configured to be executed by at least one processor, comprising:
comprising instructions for carrying out the method of claim 12,
program.
A program for causing at least one processor to function as at least a communication unit and a determination unit,
The communication unit is configured to be able to acquire fluctuation data of a CO2 concentration in the breath of the subject and detection data related to noise-type body movements of the subject;
The determination unit is configured to be able to determine the respiratory rate of the subject based on the variation data and the detection data.
program.
At least one processor;
A system including: a program that causes the processor to function as at least a communication unit and a determination unit;
The communication unit is configured to be able to acquire fluctuation data of a CO2 concentration contained in the subject's exhaled breath and detection data related to noise-type body movements of the subject;
The determination unit is configured to be able to determine the respiratory rate of the subject based on the variation data and the detection data.
system.