Respiratory rate measuring device, respiratory rate measuring method, program and system

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

Technical Field

[0001] The present disclosure relates to a respiration rate measuring device, a respiration rate measuring method, a program, and a system.

Background Art

[0002] With the development of biometric measurement technology, it has become possible to acquire and monitor the biometric information of a subject using a wearable device. The biometric information is, for example, heart rate, body temperature, and SpO2. However, in health management, the state of respiration is also regarded as an important index. Especially among the elderly, many people suffer from respiratory diseases such as pneumonia.

[0003] As a method for monitoring the respiratory state, there are a method using thoracic impedance in combination with an ECG (Electrocardiogram) and a method for measuring the respiration rate by analyzing a pulse wave. However, these methods are easily affected by body movements such as turning over, and require a resting state to achieve a certain degree of accuracy in measurement.

[0004] Also, in clinical practice, a capnometer that measures the CO2 concentration in exhaled air is widely used for monitoring the respiratory state. However, in a capnometer connected to an artificial respiration circuit, the detected data is a substantially rectangular wave, and a natural respiration waveform cannot be obtained, so it is difficult to accurately grasp the respiratory state of the subject.

Summary of the Invention

Problems to be Solved by the Invention

[0005] The present disclosure provides a new technology for grasping the respiratory state.

Means for Solving the Problems

[0006] One aspect of the present disclosure is a respiratory rate measuring device for measuring respiratory rate, comprising: a first sensor device for acquiring data on fluctuations in the CO2 concentration in a subject's continuous exhaled breath; a second sensor device for detecting noise-type body movements of the subject that occur during the measurement period of the first sensor device; and a determination unit for determining the respiratory rate based on the number of peaks in the fluctuation data, excluding the portion of the fluctuation data corresponding to the time of occurrence of the noise-type body movements.

[0007] A first sensor device that acquires CO2 concentration fluctuation data can acquire fluctuation data for measuring the respiratory 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 respiratory rate. A determination unit that determines the respiratory rate based on the number of peaks in the fluctuation data, excluding the portion of the fluctuation data corresponding to the time of occurrence of the noise-type body movement, can more accurately measure the respiratory rate using CO2 concentration fluctuation data.

[0008] One aspect of this disclosure is a respiratory rate measurement method for a respiratory rate measuring device equipped with a CO2 sensor, comprising: acquiring fluctuation data of the CO2 concentration in a subject's continuous exhaled breath using the CO2 sensor; generating frequency data by frequency-converting the fluctuation data; and, from the frequency data, determining the number of peaks in the CO2 concentration that exceed a predetermined threshold for the fluctuation data of the CO2 concentration corresponding to a predetermined frequency band including the subject's natural breathing, as the respiratory rate. According to this, respiratory rate can be measured more accurately using a CO2 sensor used as a chip module.

[0009] One aspect of this disclosure is a program configured to be executed by at least one processor, which includes instructions for executing the respiratory rate measurement method. This allows for more accurate measurement of respiratory rate using CO2 concentration fluctuation data.

[0010] One aspect of this disclosure is a program that causes at least one processor to function as at least a communication unit and a determination unit, wherein the communication unit is configured to acquire fluctuation data of CO2 concentration in the subject's exhaled breath and detection data relating to the subject's noise-type body movements, and the determination unit is configured to determine the subject's respiratory rate based on the fluctuation data and the detection data. This allows for more accurate measurement of respiratory rate using CO2 concentration fluctuation data.

[0011] One aspect of the present disclosure is a system comprising at least one processor and a program that causes the processor to function as at least a communication unit and a determination unit, wherein the communication unit is configured to acquire fluctuation data of CO2 concentration contained in the subject's exhaled breath and detection data relating to the subject's noise-type body movements, and the determination unit is configured to determine the subject's respiratory rate based on the fluctuation data and the detection data. This system makes it possible to measure the respiratory rate using CO2 concentration fluctuation data more accurately. [Effects of the Invention]

[0012] According to this disclosure, respiratory rate can be measured using CO2 concentration fluctuation data. [Brief explanation of the drawing]

[0013] [Figure 1] This is a front view showing an example of a schematic configuration of a respiratory rate measuring device according to one embodiment. [Figure 2] This is a block diagram showing the schematic configuration of the functions of a respiratory rate measuring device according to one embodiment. [Figure 3] This flowchart shows one aspect of the process of measuring respiratory rate using a respiratory rate measuring device according to one embodiment. [Figure 4] This is an explanatory diagram illustrating the filter output normalized by the maximum CO2 concentration detected by a respiratory rate measuring device according to one embodiment. [Figure 5]It is a flowchart showing another aspect of the process of measuring the respiratory rate by the respiratory rate measuring device according to an embodiment. [Figure 6] It is an explanatory diagram showing an example of the determination operation of the respiratory rate in the process of measuring the respiratory rate shown in the flowchart of FIG. 5. [Figure 7] It is an explanatory diagram showing another example of the determination operation of the respiratory rate in the process of measuring the respiratory rate shown in the flowchart of FIG. 5. [Figure 8] It is an operation explanatory diagram for determining the respiratory rate of still another aspect of the process of measuring the respiratory rate by the respiratory rate measuring device according to an embodiment. [Figure 9] It is an explanatory diagram showing one aspect of the respiratory rate measuring device according to an embodiment. [Figure 10] It is an explanatory diagram showing another aspect of the respiratory rate measuring device according to an embodiment. [Figure 11] FIGS. 11A and 11B are explanatory diagrams showing the respiratory rate measuring device according to an embodiment. [Figure 12] FIGS. 12A to 12D are explanatory diagrams showing the respiratory rate measuring device according to an embodiment of the present disclosure. [Figure 13] It is a block diagram showing the functional configuration of the system according to an embodiment. [Figure 14] FIG. 14A is a graph showing the detection result of the CO2 concentration by the CO2 sensor at rest, and FIG. 14B is a graph showing the detection result of the CO2 concentration by the CO2 sensor when turning over. [Figure 15] FIG. 15A is a graph showing the detection result of the acceleration by the acceleration sensor at rest, and FIG. 15B is a graph showing the detection result of the acceleration by the acceleration sensor when turning over. [Figure 16] FIGS. 16A to 16F are diagrams showing an example of the respiratory waveform that can be detected by the system according to an embodiment. [Figure 17] FIGS. 17A to 17C are diagrams showing an example of the respiratory waveform that can be detected by the system according to an embodiment.

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, preferred embodiments of the present disclosure will be described in detail. The embodiments described below do not unduly limit the content of the present disclosure described in the claims, and not all of the configurations described in the embodiments are necessarily essential as the solution means of the present disclosure.

[0015] In the following description, the terms indicating the directions of "up", "down", "left", and "right" are used for convenience of explanation and do not limit the usage method and usage mode. The terms such as "first" and "nth" (n is an integer) following "first" described in this specification and the claims are used as identification terms for distinguishing different elements and do not indicate a specific order or superiority or inferiority.

[0016] The terms used in the following description are only intended to describe a specific embodiment and are not intended to limit the scope of the present disclosure. Components according to an aspect described in this specification and the claims are intended to include the plural form as well, unless clearly stated in the context that they are in the singular or plural form.

[0017] The term "and / or" refers to any one or more and all possible combinations of the related listed elements and is intended to include this. For example, "A or B" means "A, B, or both A and B". "A", "B", and "both A and B" each satisfy "A or B".

[0018] The terms "includes", "including", "comprises", and / or "comprising" described in this specification and the claims are used to specify the existence of features, operations, elements, and steps. However, they are used as terms that do not exclude the existence or addition of one or more other features, operations, elements, steps, and / or groups thereof.

[0019] All embodiments and optional embodiments included in this disclosure may be combined to form new embodiments. Furthermore, all technical features and optional technical features included in this disclosure can be combined to form new technical features.

[0020] Outline configuration of the respiratory rate measuring device 100

[0021] The schematic configuration of a respiratory rate measuring device according to one embodiment of this disclosure will be described with reference to the drawings. Figure 1 is a front view showing an example of the schematic configuration of a respiratory rate measuring device according to one embodiment of this disclosure.

[0022] The respiratory rate measuring device 100 can be used by anyone 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 respiratory status, in the health management of subjects. Potential subjects include, for example, patients hospitalized in medical institutions, elderly people residing in nursing homes or care facilities, elderly people in evacuation shelters during disasters, injured or ill people at emergency or disaster sites, elderly people receiving home care, and patients with respiratory diseases, but the subjects are not limited to these people.

[0023] As shown in Figure 1, the respiratory rate measuring device 100 comprises 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 mounted on different positions on the same side of the sensor body 105, or on opposite sides. The CO2 sensor 110 and the noise detection sensor 120 are connected to the microcomputer 130 via connecting wires 140 (140a, 140b), respectively.

[0024] As shown in Figure 1, the CO2 sensor 110 and the noise detection sensor 120 are located within the sensor body 105, 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 target object according to its type. Therefore, its arrangement is not limited to a position within the sensor body 105, and it may be placed at a location away from the sensor body 105.

[0025] The sensor body 105 is provided with an attachment member 150 for the subject to wear. The subject uses an orthosis. Examples of orthoses include head orthoses and body orthoses. Examples of head orthoses include face shields that cover the area around the mouth and sanitary masks. Examples of body orthoses include clothing and neck-worn members such as necklaces. The attachment member 150 is formed in the shape of a belt extending from the left and right sides of the sensor body 105. This belt-shaped attachment member 150 can hold the various orthoses mentioned above. 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.

[0026] The mounting method for attaching the sensor body 105 to the subject is not limited to those described above. For example, it may be configured so that the mounting member is secured to the ear, like the frame of eyeglasses, and the sensor body 105 is positioned near the mouth. The respiratory rate measuring device 100 may also be in the shape of a handheld rod, like an interview microphone. In this case, the nurse will use the sensor body 105 by bringing it close to the area around the patient's mouth. In this way, the sensor body 105 has mounting members It does not have to be attached to the subject via an intermediary.

[0027] The CO2 sensor 110 functions as a first sensor device for detecting fluctuations in the CO2 concentration in the subject's exhaled breath. To detect fluctuations in the CO2 concentration in the subject's exhaled breath, the CO2 sensor 110 is positioned at a location on the sensor body 105 that faces the subject's oral cavity when the subject is wearing it. A gas sensor can be used as the CO2 sensor 110. Specifically, for example, a volatile organic compound (VOC) sensor can be used to detect VOCs in exhaled breath. A metal oxide (MOX) gas sensor can be used to detect volatile organic compounds (VOCs). The CO2 sensor 110 exemplified here may be of the equivalent carbon dioxide method. The equivalent carbon dioxide method calculates the equivalent CO2 concentration (eCO2 concentration) from the measured concentration of volatile organic compounds (VOCs). This calculation process is performed by a microcomputer 130 connected to the CO2 sensor 110. The measurement data from the CO2 sensor 110 is transmitted to the microcomputer 130 via a connection line 140a. Although Figure 1 shows one connection line 140a, a configuration including multiple connection lines is also possible.

[0028] The noise detection sensor 120 functions as a second sensor device that detects noise-type body movements of the subject that occur during the measurement period of the CO2 sensor 110, which is used to measure the subject's respiratory rate. The noise detection sensor 120 is located in the vicinity of the CO2 sensor 110 within the sensor body 105. The noise detection sensor 120 detects noise-type body movements.

[0029] Noise-type body movements as described herein and in the claims refer to the subject's movements that affect fluctuations in CO2 concentration due to the subject's natural breathing, thereby reducing the accuracy of measuring the subject's respiratory rate. Such movements may include both conscious and unconscious movements. More specifically, examples of noise-type body movements include, but are not limited to, changes in the subject's body movements such as turning over in bed, coughing, sneezing, yawning, hiccups, and talking, which are cardiopulmonary functions other than breathing.

[0030] The noise detection sensor 120 acquires data on physical quantities to identify the presence or absence of noise-type body movements that affect fluctuations in CO2 concentration caused by factors other than respiration, thereby reducing the accuracy of measuring the subject's respiratory rate. The detection data regarding noise-type body movements from the noise detection sensor 120 is transmitted to the microcomputer 130 via the connection line 140b. Although Figure 1 shows one connection line 140b, the configuration may include multiple connection lines.

[0031] The noise detection sensor 120 may be, specifically, at least one of a microphone element, an acceleration sensor, a humidity sensor, a pressure sensor, or a CO2 sensor, but is not limited to these, and may be other sensors. The microphone element as the noise detection sensor 120 detects fluctuations in sound generated by noise-type body movements, including changes in body movement and cardiopulmonary functions other than breathing, such as coughing, sneezing, yawning, hiccuping, and talking. The acceleration sensor as the noise detection sensor 120 detects fluctuations in vibration generated by noise-type body movements. The humidity sensor as the noise detection sensor 120 detects fluctuations in humidity due to moisture contained in exhaled breath generated by cardiopulmonary functions other than breathing, such as coughing, sneezing, yawning, hiccuping, and talking, as a noise-type body movement. The pressure sensor as the noise detection sensor 120 detects fluctuations in exhaled breath pressure generated by the aforementioned cardiopulmonary functions other than breathing, as a noise-type body movement.

[0032] The CO2 sensor as the noise detection sensor 120 (also referred to in this disclosure as the "second CO2 sensor") can be installed on the sensor body 105 on the side opposite to the side where the CO2 sensor 110 as the first sensor device (also referred to in this disclosure as the "first CO2 sensor") is installed, in order to detect fluctuations in the CO2 concentration of the subject's external environment. However, it is not limited to this, and can be installed around the subject's neck or other locations 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 as noise-type body movement, it detects fluctuations in the CO2 concentration of the external environment that are not affected by fluctuations in CO2 concentration due to the subject's breathing when the subject is performing cardiopulmonary function activities other than breathing (changes in body movement, coughing, sneezing, yawning, hiccups, talking, etc.).

[0033] In this way, the microphone element, acceleration sensor, humidity sensor, pressure sensor, or CO2 sensor each measures a detectable physical quantity, and the occurrence of various noise-type body movements that may occur in the subject can be detected by utilizing the measurement data. The noise detection sensor 120 can be composed of one or more of these sensors, either of the same type or different types.

[0034] The microcomputer 130 has the function of controlling the operation of each component of the respiratory rate measuring device 100. The microcomputer 130 also has the function of determining the respiratory rate of the subject based on the detection data from the CO2 sensor 110 and the noise detection sensor 120. Details regarding the functions of the microcomputer 130 will be described later.

[0035] Functional configuration of respiratory rate measuring device 100

[0036] Next, the functional configuration of a respiratory rate measuring device according to one embodiment of this disclosure will be described with reference to the drawings. Figure 2 is a block diagram illustrating the schematic functional configuration of a respiratory rate measuring device according to one embodiment of this disclosure.

[0037] As mentioned above, the respiratory rate measuring device 100 has a sensor body 105 equipped with multiple sensors. The multiple sensors are a CO2 sensor 110 and a noise detection sensor 120. The sensor body 105 is equipped with one CO2 sensor 110 and one noise detection sensor 120, but it may be equipped with two or more. For example, as the noise detection sensor 120, two or more noise detection sensors 120 may be provided to enable the detection of different types of 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, thereby removing noise data based on a wider variety of noise-type body movements and improving the accuracy of respiratory rate measurement.

[0038] As shown in Figure 2, the respiratory rate measuring device 100 can be configured such that the microcomputer 130 comprises 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 for sending and receiving data to and from the outside via the network 2 (see Figure 13). The communication method of the communication unit 132 can be wireless communication such as LTE (Long Term Evolution), Wi-Fi (registered trademark), or Bluetooth (registered trademark). The operation unit 133 consists of input buttons, a touch panel, etc., and has the function of inputting predetermined commands and data to the control unit 131. The display unit 134 has the function of outputting calculation results from the control unit 131 and input results from the operation unit 133 on a screen display, and is composed of, for example, a liquid crystal screen.

[0039] The control unit 131 has the 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 the function of appropriately storing necessary data in the RAM 136 when executing these various processes. As a result, the control operation by the control unit 131 enables access to the ROM 135 and RAM 136, display of data on the display unit 134, operation of the operation unit 133, and transmission and reception of various information via the network 2 using the communication unit 132 as an interface when communicating with the outside.

[0040] Furthermore, the control unit 131 may have the function of receiving detection data (also referred to as "measurement data" or "variation data" in this specification and the claims) from the CO2 sensor 110 and the noise detection sensor 120, determining the respiratory rate of the subject being measured based on the detection data, and transmitting the determination result to an external device. As shown in Figure 2, the control unit 131 comprises a receiving unit 131a, a determination unit 131b, and a transmitting unit 131c.

[0041] The receiving unit 131a has the function of controlling the reception of detection data from the CO2 sensor 110 and the noise detection sensor 120. The receiving unit 131a also has the function of controlling the reception of various data from external devices.

[0042] The determination unit 131b has the function of performing determination operations necessary when executing various operations of the respiratory rate measuring device 100. Specifically, the determination unit 131b has the function of determining whether or not various data are being sent and received with an external device via the communication unit 132 of the respiratory rate measuring device 100. In addition, the determination unit 131b has the function of performing calculation processing using detection data obtained from the CO2 sensor 110 and the noise detection sensor 120 to determine the respiratory rate of the subject.

[0043] Specifically, the determination unit 131b calculates the subject's respiratory rate and respiratory pattern based on the detection data from the CO2 sensor 110, using FFT analysis, wavelet analysis, AI, etc., to determine the respiratory rate. The determination unit 131b also has a function to determine the subject's respiratory rate by using CO2 concentration data generated by noise-type body movements from the fluctuating data detected by the CO2 sensor 110 as noise data and not counting it as the subject's respiratory rate. Details of how the determination unit 131b determines the subject's respiratory rate will be described later.

[0044] The transmitting unit 131c has a function to control the transmission of various data to external devices. In this embodiment, the transmitting unit 131c controls the transmission of detection data from the CO2 sensor 110 and detection data related to noise-type motion detected by the noise detection sensor 120 to, for example, the administrator terminal 30 (see Figure 13) or the server device 10 (see Figure 13). The transmitting unit 131c also controls the transmission of the determination result from the determination unit 131b to, for example, the administrator terminal 30 or the server device 10 (see Figure 13).

[0045] The transmitter 131c has the function of transmitting measurement data from the CO2 sensor 110 and detection data related to noise-type motion detected by the noise detection sensor 120 to an external device at predetermined intervals. This predetermined interval can be set, for example, at regular time intervals (e.g., every minute) or at time intervals of any length. Furthermore, the transmitter 131c may make the predetermined interval variable depending on the battery level. For example, it may transmit every minute when the battery level is above 50%, and every 10 minutes when it is 50% or less. The numerical value of the battery level and the transmission time can be set arbitrarily.

[0046] Furthermore, the transmitting unit 131c may store multiple detection data detected before transmitting the data, and transmit the stored multiple detection data all at once at predetermined intervals. This reduces battery consumption. The detection data transmitted by the transmitting unit 131c may be (1) actual measurement data measured by each detection sensor, (2) processed data obtained by performing calculations on 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 determination unit 131b, the remaining battery level, etc.

[0047] In this way, the respiratory rate measuring device 100 can determine the respiratory rate of a subject wearing the device based on the CO2 concentration fluctuation data detected by the CO2 sensor 110 and the noise-type body movement detection data detected by the noise detection sensor 120. The respiratory rate measuring device 100 can also send and receive respiratory rate data of the subject to the administrator terminal 30 (see Figure 13) and the server device 10. Details of how the respiratory rate of a subject is determined and their health status is managed using the respiratory rate measuring device 100 of this embodiment will be described later.

[0048] Flowchart for measuring respiratory rate using respiratory rate measuring device 100

[0049] Flowchart 1 (Figure 3)

[0050] Next, a method for measuring respiratory rate using a respiratory rate measuring device according to one embodiment of this disclosure will be described with reference to the drawings. Figure 3 is a flowchart showing the respiratory rate measurement operation using a respiratory rate measuring device according to one embodiment of this disclosure.

[0051] The respiratory rate measurement method using the respiratory rate measuring device 100 is executed by a program that operates the computer included in System 1 (see Figure 13) using the respiratory rate measuring device 100. The program that executes the respiratory rate measurement method using the respiratory rate measuring device 100 is a program that causes one or more processors (computer devices) connected to the network to perform the measurement of the subject's respiratory rate. The program that performs the respiratory rate measurement method in this embodiment causes one or more processors (computer devices) connected to the network to execute the operation flow shown in Figure 3.

[0052] The measurement is started, for example, by pressing the measurement start button on the respiratory rate measuring device 100. First, the CO2 sensor 110 detects fluctuations in the CO2 concentration contained in the subject's exhaled breath (step S1). The data acquired here is fluctuation data of CO2 concentration measured from continuous exhaled breath over a predetermined measurement period. In this embodiment, the CO2 sensor 110 detects the equivalent CO2 concentration by calculating the equivalent CO2 concentration (eCO2 concentration) from the detected concentration values ​​of volatile organic compounds (VOCs) contained in the subject's exhaled breath. The detection data from the CO2 sensor 110 is transmitted to the microcomputer 130 (step S2).

[0053] When the CO2 concentration fluctuation data detected by the CO2 sensor 110 is transmitted to the microcomputer 130, the determination unit 131b monitors the data detected by the CO2 sensor 110 and estimates the respiratory rate from the waveform of the CO2 concentration fluctuation data (step S3).

[0054] Here, the waveform of the CO2 concentration fluctuation data (referred to as the CO2 concentration waveform in this specification and the claims) is a waveform in which the X axis represents time and the Y axis represents CO2 concentration. Typically, the peaks in CO2 concentration that appear in the CO2 concentration waveform at regular, constant intervals can be understood as one breath due to natural respiration. One breath is understood as a combination of one exhalation and one inhalation. The peaks in CO2 concentration are usually detected during exhalation. The number of breaths can be calculated by the following formula.

[0055] R = Nγ / T However, R is the respiratory rate [bpm], Nγ is the detected respiratory rate, and T is the measurement time [min.].

[0056] The natural breathing rate of healthy individuals, when breathing unconsciously, is said to be approximately 12 to 23 breaths per minute. Here, we will assume that the subject's natural breathing rate is 22.5 bpm. This respiratory rate can be set to any desired rate. The respiratory rate can be set according to the subject, for example. It can also be set according to the subject's gender, physique, health condition, etc.

[0057] If we assume a respiratory rate of 22.5 bpm, then by frequency-converting the fluctuation data of the CO2 concentration waveform during natural breathing, we can generate frequency data, and the main frequency component will be 0.375 Hz (= 22.5 bpm). Therefore, the peak in CO2 concentration measured at 0.375 Hz can be estimated to be the time when breathing occurred and can be counted as a respiratory rate. However, it is rare for the human body to breathe at perfectly precise time intervals during natural breathing.

[0058] Therefore, it is more accurate to understand the frequency components of the CO2 concentration waveform, which should be understood as a natural respiration, not as a single specific frequency component, but as a frequency band. Here, as an example, we can set a frequency band with a low-frequency component of 0.275 Hz and a high-frequency component of 0.475 Hz (bandpass filtering). The number of peaks in the CO2 concentration waveform within that frequency band is then useful for counting the number of breaths due to natural respiration.

[0059] Furthermore, setting such frequency bands is also useful for more accurately counting the number of breaths during natural breathing. That is, natural breathing may include fluctuations in CO2 concentration caused by factors other than breathing. By setting the frequency bands as described above, it becomes possible to eliminate noise that appears as low-frequency components and noise that appears as high-frequency components, thereby measuring the number of breaths more accurately. Noise that appears as low-frequency components includes, for example, slow breathing such as multiple deep breaths. Noise that appears as high-frequency components includes, for example, rapid breathing such as hyperventilation. By eliminating these types of breathing, the number of breaths during natural breathing becomes more accurate.

[0060] By setting the frequency band as described above, the peak of CO2 concentration where the maximum value exceeds a predetermined threshold is counted as one breath. The reason for setting the maximum value threshold here is to filter the data by the CO2 concentration value (the "CO2 concentration value" includes the calculated value obtained by performing a predetermined calculation on that value) so that only the data that should be recognized as breath is included in the breath count data. This allows for more accurate measurement (estimation) of the breath rate. Assuming the aforementioned breath rate setting value is assumed, the threshold is set to, for example, 0.37 relative to the filter output normalized by the maximum CO2 concentration (output of the bandpass filter processing), as shown in Figure 4. However, the CO2 concentration threshold set here can be any value. The threshold can be set according to, for example, the subject. It can also be set according to the subject's gender, physique, health status, etc. When setting the threshold using the absolute value of CO2 concentration, for example, 60-70% of the peak value of the absolute value of CO2 concentration is set as the threshold.

[0061] Using the respiratory rate measurement method described above, the respiratory rate of the subject can be determined (estimated) from the CO2 concentration fluctuation data.

[0062] According to the inventors' experiments, when comparing the CO2 concentration fluctuation data measured while at rest during the measurement period with the CO2 concentration fluctuation data measured while turning over in bed to simulate body movement during the measurement period, it was confirmed that there was no significant difference in the accuracy of respiratory rate measurement when comparing the CO2 concentration waveform with the output waveform normalized to the maximum value after the aforementioned bandpass filtering process. In other words, it can be seen that the respiratory rate measuring device 100 and the respiratory rate measuring method described above are measurement methods that are less affected by changes in body movement.

[0063] The respiratory rate measurement can be completed by following the steps described above. For example, the measurement is terminated by pressing the measurement completion button on the respiratory rate measuring device 100. However, to ensure even greater accuracy, the following further processing may be performed.

[0064] In other words, it is determined whether or not noise-type body movements that cause fluctuations in CO2 concentration due to factors other than the subject's respiration are detected (Step S4).

[0065] The various sensors of the noise detection sensor 120 detect the following physical quantities and transmit the detected data to the microcomputer 130 (step S5). • Microphone element: Sounds emitted when the subject moves, coughs, yawns, talks, etc. • Accelerometer: Detects vibrations generated in response to changes in the subject's body movement, coughing, yawning, conversation, etc. • Humidity sensor: Measures the humidity of the breath exhaled by the subject when they cough, sneeze, yawn, talk, etc. • Pressure sensor: Measures the pressure of the subject's exhaled breath when they cough, sneeze, yawn, talk, etc.

[0066] When the microcomputer 130 receives detection data from the noise detection sensor 120, the determination unit 131b performs noise reduction (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 reduction differs depending on the configuration of the noise detection sensor 120.

[0067] In other words, when the noise detection sensor 120 is a microphone or an acceleration sensor, if a sound or vibration that constitutes noise-type body movement is detected, the noise is removed by not counting the respiratory waveform of the CO2 concentration data detected by the CO2 sensor during that period as part of the respiratory rate. The determination unit 131b then considers the fluctuation data of CO2 concentration detected by the CO2 sensor, excluding the period detected by the microphone or acceleration sensor, as respiration, and determines the respiratory rate using FFT analysis, wavelet analysis, AI, etc. Thus, when the noise detection sensor 120 is a microphone or an acceleration sensor, the determination unit 131b determines the respiratory rate of the subject by using the fluctuation data of CO2 concentration detected by the CO2 sensor 110 during the period in which noise-type body movement was detected by the noise detection sensor 120 as noise data that is not counted.

[0068] On the other hand, when the noise detection sensor 120 is a humidity sensor or a pressure sensor, even if humidity or pressure, which constitute noise data, is detected, the fluctuation data of CO2 concentration detected by the CO2 sensor 110 is initially considered as the respiratory waveform used to measure the respiratory rate, and the respiratory rate is measured. Then, the waveform pattern of the detection data from the humidity sensor or pressure sensor is checked, and the respiratory rate is estimated from that waveform pattern using FFT analysis, wavelet analysis, adaptive filtering, AI, etc. Thus, when the noise detection sensor 120 is a humidity sensor or a pressure sensor, the determination unit 131b determines the respiratory rate by estimation based on the analysis results of the waveform pattern of the fluctuation data of CO2 concentration detected by the CO2 sensor 110 and the waveform pattern of the detection data related to noise-type body movement detected by the noise detection sensor 120.

[0069] If no noise-type body movement of the subject is detected in step S4, the determination unit 131b determines the respiratory rate as the respiratory rate based on the CO2 concentration fluctuation data detected by the CO2 sensor 110 in step S3.

[0070] In this embodiment, the respiratory rate of the subject is estimated from the detection data of the CO2 sensor 110. When noise-type body movements of the subject that occur during the measurement period of the CO2 sensor 110 are detected, the CO2 concentration data generated by the noise-type body movements from the detection data of the CO2 sensor 110 is used as noise data and not counted as respiratory rate to determine the final respiratory rate of the subject P. Therefore, even if noise-type body movements occur due to changes in the subject P's body movements or other cardiopulmonary functions such as coughing, sneezing, yawning, or talking, the subject's respiratory rate is determined after noise reduction associated with the noise-type body movements, thereby reducing the influence of noise-type body movements and enabling accurate determination of the respiratory rate.

[0071] Second flow (Figure 5)

[0072] The method for measuring respiratory rate using the respiratory rate measuring device 100 according to this embodiment is not limited to the flowchart shown in Figure 3, but can be performed, for example, as shown in the flowchart in Figure 5.

[0073] Measurement is initiated, for example, by pressing the start button on the respiratory rate measuring device 100 ("START" in Figure 5). Simultaneously with the start of measurement, a timer that measures the measurement time is activated, and the CO2 sensor 110 detects fluctuations in the CO2 concentration contained in the subject's exhaled breath (step S11). The CO2 concentration fluctuation data detected by the CO2 sensor 110 is continuously transmitted to the microcomputer 130 (step S12).

[0074] The determination unit 131b of the microcomputer 130 continuously detects whether the received CO2 concentration fluctuation data contains data indicating noise-type body movement (step S13). If the determination unit 131b determines that there is no detection of noise-type body movement, it determines the respiratory rate from the fluctuation data of the CO2 sensor 110 (step S14). Here, "determining the respiratory rate" means being able to count one or more breaths.

[0075] On the other hand, if noise-type body movement of the subject is detected in step S13, the process returns to step S11 and repeats the steps described above. The measurement of respiratory rate based on CO2 concentration fluctuation data continues until the respiratory rate can be determined based on fluctuation data without detection of noise-type body movement. Note that when noise-type body movement of the subject is detected in step S14 and the process returns to step S1, the timer may be reset.

[0076] In step S14, after determining the respiratory rate from the fluctuation data of the CO2 sensor 110, a decision is then made as to whether or not to continue measuring the respiratory rate (step S15). The criteria for deciding whether or not to continue the measurement (measurement termination criteria) can be set in various ways, and the following are some examples. • When a "specific number of breaths" is reached (for example, 100 breaths) • When a "specific measurement time" is reached (e.g., 1 minute, 1 hour, 1 day, 1 week, unlimited) • When a "specific action" is performed on the respiratory rate measuring device 100 (for example, when the measurement end button on the respiratory rate measuring device 100 is pressed, or when the respiratory rate measuring device 100 is powered off, etc.)

[0077] If the measurement termination criterion is reached in step S15, the respiratory rate measurement is terminated ("END" in Figure 5). If the measurement termination criterion is not reached in step S15, the process returns to step S11 and the previous steps are repeated. The measurement is repeated until the measurement termination criterion is reached in step S15.

[0078] As described above, in the embodiment shown in Figure 5, the determination unit 131b determines the respiratory rate by counting the number of peaks in the fluctuation data of CO2 concentration detected by the CO2 sensor, only when no noise-type body movement occurs. Therefore, since there is no need to perform FFT analysis or wavelet analysis on the detection data related to noise-type body movement, or to remove noise, the respiratory rate of the subject can be easily measured with fewer steps.

[0079] Furthermore, various respiratory rates can be measured depending on the measurement termination criteria set in step S15. For example, if "specific measurement time" is selected as the measurement termination criterion and set to "1 minute," it is possible to measure the respiratory rate per minute under normal breathing conditions. This is considered an appropriate measurement for understanding respiratory rate from a clinical standpoint, and is suitable for more accurately determining the respiratory rate per minute in emergency situations, disaster sites, and evacuation centers during disasters where equipment is inadequate.

[0080] Furthermore, by selecting a "specific action" and setting it to "when the measurement end button on the respiratory rate measuring device 100 is pressed," continuous respiratory rate measurement is possible. This is suitable, for example, for continuously measuring the respiratory rate of patients in hospitals or those receiving home care, in order to detect signs of changes in their condition.

[0081] Next, an example of the respiratory rate determination operation (step S14) in the flowchart for measuring respiratory rate using the respiratory rate measuring device shown in Figure 5 will be explained with reference to Figures 6 and 7.

[0082] Here, we will explain two methods for measuring respiratory rate. One method, as shown in Figure 6, is to measure the number of breaths occurring from the present moment, using the present moment as the reference point. The other method, as shown in Figure 7, is to measure the number of breaths retrospectively, using the present moment as the reference point. Furthermore, for the sake of explanation, we will use the example of measuring the number of breaths over a 60-second (1-minute) period during normal breathing.

[0083] Example of measuring the first respiratory rate (Figure 6)

[0084] The origin "0" at the left end of the number lines in Figures 6A, 6B, and 6C represents the start of measurement. As shown in Figure 6A, if no noise-type body movements such as coughing, yawning, or talking are detected in the subject, the respiratory rate measured during the first 60-second measurement period T1 is determined to be the subject's respiratory rate. The same procedure is then followed to measure the subject's respiratory rate during the next 60-second measurement period T2.

[0085] On the other hand, if noise-type body movement with a noise generation time n(s) (for example, 15 seconds) is detected within one minute of starting the measurement, as shown in Figure 6B, the respiratory rate is measured for 60 seconds from the end of the noise-type body movement generation interval Tn. If no noise-type body movement is detected during that time, the respiratory rate measured during the 60-second measurement period T1 from the end of the noise-type body movement is determined to be the subject's respiratory rate. This measurement method allows for the measurement of respiratory rate during a continuous 1-minute period of normal breathing without interruption. Furthermore, since the interval during which noise-type body movement occurs can be identified, it is possible to confirm what happened to the patient at that time.

[0086] Furthermore, if noise-type body movement with a noise generation time n(s) (for example, 15 seconds) is detected within 1 minute of starting the measurement, the subject's respiratory rate may be determined from the respiratory rate measurement data for the time period of 60 seconds plus 15 seconds, which is the noise generation time n(s) at which the noise-type body movement was detected, as shown in Figure 6C. In this case, the time T1 from the start of the measurement until the occurrence of noise-type body movement is determined. a The time T1 is the time from when the noise-type body movement ends until the respiratory rate measurement is completed. b The sum of these values ​​equals T1, or 1 minute (60 seconds). This measurement method measures the respiratory rate for 1 minute after removing the detection interval for noise-type body movements.

[0087] Example of measuring the second respiratory rate (Figure 7)

[0088] The origin "0" at the right end of the number lines in Figures 7A, 7B, and 7C represents the present moment. In this example, the present moment is used as the reference time for measuring respiratory rate, and the respiratory rate is measured by retrospectively examining past respiratory rate measurement data from the present moment. For example, if the respiratory rate measurement data for the past minute (60 seconds) from the present moment is examined and no noise-type body movements such as coughing, yawning, or talking are detected during the measurement period, then, as shown in Figure 7A, the respiratory rate measured in the past measurement period T1 (the first 60 seconds from the reference time) is determined to be the subject's respiratory rate.

[0089] On the other hand, if noise-type body movement with a noise duration n(s) (for example, 15 seconds) is detected within the first minute from the present time, as shown in Figure 7B, the respiratory rate is measured for the past 60 seconds from the time the noise-type body movement detection ended. If no noise-type body movement is detected during that time, the respiratory rate measured during the 60-second measurement period T1 from the time the noise-type body movement ended is determined to be the subject's respiratory rate. This measurement method allows for the measurement of respiratory rate during a continuous 1-minute period of normal breathing without interruption. Furthermore, since the interval in which noise-type body movement occurred can be identified, it is possible to confirm what happened to the patient at that time.

[0090] Furthermore, if noise-type body movement with a noise generation time n(s) (for example, 15 seconds) is detected within the first minute from the present time, the subject's respiratory rate may be determined from the respiratory rate measurement data from the past time period, including the 15 seconds that constitute the noise generation time n(s) at which the noise-type body movement was detected, as shown in Figure 7C. In this case, the time T1 from the start of measurement until the occurrence of noise-type body movement is determined. a The time T1 is the time from when the noise-type body movement ends until the respiratory rate measurement is completed. b The sum of these two points equals one minute (60 seconds). This measurement method measures the respiratory rate for one minute after removing the detection interval for noise-type body movements.

[0091] In this embodiment, the respiratory rate can be easily determined by counting the number of breaths during a predetermined time period (60 seconds) in the future or past from the current time, which is the measurement reference time. Specifically, the determination unit 131b can accurately determine the respiratory rate by counting the number of peaks in the fluctuation data of the CO2 concentration detected by the CO2 sensor 110, only when there is no noise-type body movement occurring within a predetermined time period in the future or past from the measurement reference time.

[0092] Noise detection sensor 120 is CO 2 Example of respiratory rate measurement when used as a sensor (Figure 8)

[0093] The method for measuring respiratory rate by the respiratory rate measuring device 100 when the noise detection sensor 120 is a CO2 sensor for noise detection will be explained with reference to Figure 8.

[0094] In this embodiment, as shown in Figure 8, the CO2 sensor 110 and the noise detection sensor 120, which is a CO2 sensor, each acquire CO2 concentration fluctuation data. When a microphone element or the like is used as the noise detection sensor 120, noise-type fluctuations are detected in the CO2 concentration fluctuation data detected by the CO2 sensor 110 using a different physical quantity. On the other hand, the example in Figure 8 is an example in which noise-type fluctuations are 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.

[0095] The data processing unit 137 has a function to cancel out artifacts contained in the detection data of both sensors 110 and 120. For this purpose, the data processing unit 137 can store statistical properties such as the mean value and variance of each artifact, and the correlation value between the artifacts of both sensors, as data. Using this data, the data processing unit 137 cancels out the artifacts contained in the detection data of the CO2 sensor 110, obtains clean CO2 concentration fluctuation data for measuring the respiratory rate, and outputs it to the determination unit 131b. In this case, the data processing unit 137 can be configured with an adaptive filter or AI that cancels out the artifacts of both sensors. A bandpass filter may also be provided between both sensors 110 and 120 and the data processing unit 137 to extract frequency components for measuring the respiratory rate from the detection data.

[0096] Here, the artifact is a change in CO2 that fluctuates due to factors other than respiration. Specifically, the CO2 concentration fluctuation data that forms the basis of the respiratory rate measurement data includes artifact A, which is CO2 that fluctuates due to factors other than respiration, and the detection data of the noise detection sensor 120 includes artifact B, which is CO2 that fluctuates due to factors other than respiration. This artifact B is data as noise-type body motion. Artifacts A and B may be CO2 detected by the same factor other than respiration, or CO2 detected by different factors. Artifacts A and B are dependent on the placement locations of sensors 110 and 120. If artifacts A and B are CO2 detected based on different factors, these artifacts A and B will have a high correlation if the placement locations of sensors 110 and 120 are close to each other. Therefore, based on the correlation between artifacts A and B contained in the detection data of these sensors 110 and 120, the data processing unit 137 removes artifact A, which is a change in CO2 that fluctuates due to factors other than respiration, from the detection data of the CO2 sensor 110, thereby enabling it to transmit data on the actual fluctuation of CO2 concentration contained in the subject's respiration to the determination unit 131b. On the other hand, if artifacts A and B are CO2 detected based on the same factor, the data processing unit 137 can be made to function as a differential amplifier to remove artifact A contained in the detection data of the CO2 sensor 110. The determination unit 131b then calculates the subject's respiratory rate based on this fluctuation data.

[0097] In this embodiment, the determination unit 131b determines the subject's respiratory rate based on the actual CO2 concentration fluctuation data of the CO2 sensor 110, obtained by canceling out artifacts contained in the detection data of both sensors 110 and 120 in the data processing unit 137. Specifically, the data processing unit 137 performs data processing to cancel out artifact A contained in the detection data of the CO2 sensor 110, which is a CO2 sensor for respiratory rate measurement, using an adaptive filter or AI, based on the data of artifact B contained in the fluctuation data of the CO2 concentration of the external environment detected by the noise detection sensor 120, and then extracts the actual CO2 concentration fluctuation data to be used to measure the subject's respiratory rate. Then, the determination unit 131b determines the subject's respiratory rate 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 the fluctuation data of the CO2 concentration of the external environment, the subject's respiratory rate can be accurately determined by performing data processing to cancel out artifacts contained in the detection data of both sensors 110 and 120.

[0098] Application examples of the respiratory rate measuring device 100

[0099] Next, examples of applications of the respiratory rate measuring device 100 of this embodiment will be described with reference to the drawings. Figure 9 is an explanatory diagram showing one aspect of the respiratory rate measuring device 100 according to this embodiment, and Figures 10, 11, and 12 are explanatory diagrams showing other aspects of the respiratory rate measuring device 100 according to this embodiment.

[0100] The respiratory rate measurement device 100 uses a low-power, high-sampling-grade equivalent carbon dioxide sensor as its CO2 sensor 110, taking into account the miniaturization and real-time capabilities of the device. To continuously measure fluctuations in the concentration of CO2 in the exhaled breath of the subject P, the respiratory rate measurement device 100 uses a wearable sensor, the CO2 sensor 110, which can be attached to an appliance around the subject P's oral cavity.

[0101] For example, as shown in Figure 9, the respiratory rate measuring device 100 has a sensor body 105 attached via a mounting member 150 to the inside of a sanitary mask M1, which is a "device" or "head device" worn by the subject P. By attaching the sensor body 105, including the CO2 sensor 110, to the inside of the sanitary mask M1 in this way, the measurement data of the CO2 concentration in the subject P's exhaled breath, measured by the CO2 sensor 110, is transmitted to the microcomputer 130. The microcomputer 130 then performs a determination process of the subject P's respiratory rate based on the detection data from the CO2 sensor 110 and the detection data from the noise detection sensor 120.

[0102] Furthermore, as shown in Figure 10, the respiratory rate measuring device 100 can also be used by attaching the sensor body 105 to the inside of a medical oxygen mask M2, which is a "device" or "head device" worn by the subject P in a medical setting, using the mounting member 150. In this way, by attaching the sensor body 105 to the inside of the oxygen mask M2 that covers the oral cavity of the patient P, the CO2 concentration in the subject P's exhaled breath can be measured by the CO2 sensor 110. Accordingly, the microcomputer 130 performs a determination process of the subject P's respiratory rate based on the measurement data from the CO2 sensor 110 and the detection data detected by the noise detection sensor 120.

[0103] Furthermore, as shown in Figure 11A, the respiratory rate measuring device 101 may have a mounting member for attaching the sensor body 105, which includes a CO2 sensor 110 and a noise detection sensor 120, that is a hook 151 that can be locked onto the tube M3a. By making the mounting member for attaching the sensor body 105 a hook 151, the sensor body 105 can be attached to the tube M3a near the nasal cavity of the heated humidifier (example product name: "Nasal High Flow") M3 using the hook 151, as shown in Figure 11B. Therefore, by measuring the CO2 concentration in the exhaled breath near the nasal cavity of the subject P with the CO2 sensor 110, the microcomputer 130 similarly performs the process of determining the respiratory rate of the subject P.

[0104] Furthermore, as shown in Figure 12A, the respiratory rate measuring device 102 can have a mounting member for attaching the sensor body 105 that is a necklace member 152, which is a "device" or "body device" that is worn around the neck of the subject P. The necklace member 152 may be configured to have multiple sensor bodies 105 attached at predetermined intervals. By configuring the respiratory rate measuring device 102 in this way, as shown in Figure 12B, the CO2 sensor 110 of the sensor body 105 can measure the concentration of CO2 in the exhaled breath of the subject P during natural breathing, whether the subject P is lying down, as shown in Figure 12C, whether the subject P is standing and facing forward, or as shown in Figure 12D, whether the subject P is standing and facing sideways. Similarly, the microcomputer 130 can perform the process of determining the respiratory rate of the subject P.

[0105] Thus, the respiratory rate measuring devices 100, 101, and 102 use a small equivalent carbon dioxide sensor as the CO2 sensor 110, which continuously measures fluctuations in the CO2 concentration contained in the subject P's exhaled breath. Therefore, by easily attaching it to various tools and devices that cover the area around the subject P's mouth, it is possible to accurately detect fluctuations in CO2 concentration with low power consumption and a high sampling grade.

[0106] Functional configuration of a system using a respiratory rate measurement device

[0107] Next, the functional configuration of System 1 using the respiratory rate measuring device will be explained with reference to the drawings. Figure 13 is a block diagram showing the functional configuration of a system according to one embodiment of this disclosure. In Figure 13, only the server device 10, data storage unit 20, administrator terminal 30, and respiratory rate measuring device 100 provided in System 1 are shown, and the function of each component is explained in detail.

[0108] In System 1 of this embodiment, the server device 10 is connected to the data storage unit 20, administrator terminal 30, subject terminal 40, and respiratory rate measuring device 100 via the network 2. As a result, the server device 10 manages a database of fluctuation data of CO2 concentration in exhaled breath received from the respiratory rate measuring device 100 worn by the subject P, and detection data related to noise-type body movements that cause fluctuations in CO2 concentration other than the subject's breathing, in the data storage unit 20, while also enabling administrators using the administrator terminal 30 to manage the health status of each subject.

[0109] As shown in Figure 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 is configured as a "respiratory rate management server" having multiple functional units when the control unit 14 executes a "program," and the multiple functional units perform information processing.

[0110] The communication unit 11 functions as an interface for sending and receiving data to and from the outside via the network 2. In this embodiment, the communication unit 11 is configured to acquire fluctuation data of CO2 concentration contained in the subject's exhaled breath and detection data related to the subject's noise-type body movements.

[0111] The operation unit 12 has the function of inputting predetermined commands to the control unit 14, which is a data input device such as a keyboard, mouse, or touch panel, and operating the server device 10 as appropriate. The display unit 13 has the function of outputting calculation results from 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, an LCD screen. In addition, the display unit 13 is capable of displaying graphs of fluctuations in the concentration of CO2 contained in the exhaled breath of a subject wearing the respiratory rate measuring device 100, as well as trends in noise data.

[0112] The control unit 14 has the function of controlling the operation of each component of the server device 10 by having one or more processors execute various programs stored in the ROM 15. The control unit 14 also has the function of appropriately storing necessary data in the RAM 16 when executing these various processes. As a result, the control operation by the control unit 14 enables access to the ROM 15, RAM 16, and data storage unit 20, screen display operation of data on the display unit 13, operation operation of the operation unit 12, and transmission and reception of various information via the network 2 using the communication unit 11 as an interface when communicating with the outside.

[0113] As shown in Figure 13, the control unit 14 comprises a receiving unit 14a, a determination unit 14b, a transmitting unit 14c, and a generation unit 14d. The receiving unit 14a has the function of controlling the reception of various data from the data storage unit 20, the administrator terminal 30, and the respiratory rate measuring device 100 via the communication unit 11. The receiving unit 14a is controlled to receive data on fluctuations in the CO2 concentration contained in the exhaled breath of the subject P, which is transmitted from the respiratory rate measuring device 100 to the server device 10 at predetermined intervals, and detection data on the subject's noise-type body movements.

[0114] The determination unit 14b has the function of performing determination operations necessary when executing various operations of the server device 10. For example, the determination unit 14b determines whether or not various data has been sent and received between the administrator terminal 30 and the respiratory rate measuring device 100 via the communication unit 11 of the server device 10. In this embodiment, the determination unit 14b has the function of determining the respiratory rate of the subject P based on fluctuation data of CO2 concentration contained in the subject P's exhaled breath measured by the CO2 sensor 110 of the respiratory rate measuring device 100 and detection data related to noise-type body movement detected by the noise detection sensor 120.

[0115] The transmitting unit 14c has the function of controlling the transmission of various data to the data storage unit 20, the administrator terminal 30, and the respiratory rate measuring device 100 via the communication unit 11. The transmitting unit 14c also has the function of transmitting the judgment result from the judgment unit 14b to the administrator terminal 30.

[0116] The generation unit 14d has the function of processing various data and generating data. For example, the generation unit 14d can generate display data. As display data, for example, it can list a graph of the trend of fluctuation data of CO2 concentration in the subject's exhaled breath detected by the respiratory rate measuring device 100, and a graph of the trend of fluctuations of detection data related to noise-type body movement of the subject detected by the noise detection sensor 120. The display data generated by the generation unit 14d can be transmitted to an external device such as an administrator terminal 30 via the communication unit 11. The external device can then display this display data on a display unit such as a display screen.

[0117] The data storage unit 20 is an external storage device capable of storing various types of data. In this embodiment, the data storage unit 20 functions as a database that stores, for each subject, detection data including fluctuation data of the CO2 concentration contained in the exhaled breath of subject P measured by the CO2 sensor 110 of the respiratory rate measuring device 100, and detection data related to noise-type body movements detected by the noise detection sensor 120. Furthermore, the data storage unit 20 is updated whenever the detection data from the CO2 sensor 110 and the detection data related to noise-type body movements are updated.

[0118] The administrator terminal 30 is a terminal device used by the administrator and, as shown in Figure 13, is equipped with a communication unit 31, an operation unit 32, a display unit 33, a control unit 34, and a storage unit 35, so that it can perform necessary operations such as sending and receiving various information and calculation processing. By accessing the server device 10, the administrator terminal 30 can display data related to detection data, such as fluctuation data of CO2 concentration in the exhaled breath of a subject P wearing the respiratory rate measuring device 100, and graphs of the trend of fluctuation data, on the display unit 33.

[0119] In this embodiment, System 1 consists of a server device 10 connected to a data storage unit 20, an administrator terminal 30, and a respiratory rate measuring device 100 via a network 2. The server device 10 determines the respiratory rate of each subject based on detection data received from multiple subjects and detection data related to noise-type body movements, and controls the execution of a health management application service that manages the health status of each subject. As a result, the server device 10 can comprehensively manage the physical condition of subjects wearing the respiratory rate measuring device 100 that are the target of health management.

[0120] The server device 10 of System 1 may be implemented by software or by hardware. If implemented by software, the control unit 14, which acts as the CPU, can implement various functions by executing a program that operates System 1. The program of this embodiment may be stored in the ROM 15 built into the server device 10, or it may be stored in a computer-readable non-temporary recording medium.

[0121] Furthermore, the server device 10 of System 1 may read a program stored in an external storage device, and this may be implemented through so-called cloud computing. In this case, the CO2 concentration fluctuation data obtained from the CO2 sensor 110 of the respiratory rate measuring device 100 and the detection data related to noise-type body movement 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.

[0122] Operation and Effects of the Embodiment

[0123] Next, the operation and effects of the respiratory rate measuring device 100 and system 1 according to this embodiment will be described.

[0124] (1) Regarding the fluctuations in CO2 concentration in the subject's exhaled breath detected by the CO2 sensor at rest, as shown in Figure 14A, and the fluctuations in the same CO2 concentration during body movement, as shown in Figure 14B, the peak of CO2 concentration can be detected in the same manner in both cases. In contrast, regarding the fluctuations in the subject's acceleration detected by the acceleration sensor, at rest, as shown in Figure 15A, the peak of acceleration fluctuation associated with breathing can be detected, whereas during body movement, as shown in Figure 15B, there is variability in how the peak of acceleration fluctuation appears. For this reason, during body movement, the fluctuations in the subject's acceleration detected by the acceleration sensor are significantly different from those at rest, and therefore, the peak of CO2 concentration cannot be detected in the same manner as at rest.

[0125] Therefore, the inventors diligently investigated how to measure respiratory rate without being affected by changes in body movement. They focused on fluctuations in the CO2 concentration in the subject's exhaled breath and discovered the possibility of continuous monitoring of respiratory status by monitoring changes in CO2 concentration using a small wearable sensor.

[0126] (2) The inventors diligently studied to solve the aforementioned problems and found that the value estimated from the number of times the output data obtained by processing the measurement data related to fluctuations in CO2 concentration of an equivalent carbon dioxide type CO2 sensor with a bandpass filter exceeds a predetermined threshold correlates with the actual respiratory rate of the subject. For this reason, in this embodiment, an equivalent carbon dioxide type CO2 sensor 110 is used as a small wearable sensor. By counting the number of times 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 respiratory rate of the subject can be easily and accurately estimated.

[0127] (3) The respiratory rate measuring device 100 can determine the respiratory waveform pattern of the subject by monitoring the fluctuation data of CO2 concentration contained in the subject's exhaled breath. Therefore, it is possible to grasp not only the subject's respiratory rate but also biological information related to respiration such as the depth (amplitude) of breathing and the respiratory interval, so that the subject's health status and disease status can be understood from the subject's respiratory waveform pattern.

[0128] For example, if we assume that the normal respiratory waveform pattern shown in Figure 16A is 16-20 breaths / minute, then detecting the respiratory waveform pattern of 25 breaths / minute or more, as shown in Figure 16B, may suggest a correlation with the subject's fever or agitation.

[0129] 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, it may suggest a correlation with anemia or hyperthyroidism in the subject.

[0130] As shown in Figure 16D, 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 small and the depth of breathing is shallow, it may suggest a connection to respiratory muscle paralysis or sedative / morphine intoxication in the subject.

[0131] As shown in Figure 16E, detecting a respiratory waveform pattern of 9 breaths / minute or less (slow breathing) may suggest a correlation with increased intracranial pressure or bronchial obstruction in the subject.

[0132] As shown in Figure 16F, detecting a respiratory waveform pattern in which both respiratory rate and respiratory depth are increased compared to normal may suggest a correlation between the subject's condition during exercise, high fever, or neurosis.

[0133] The respiratory rate measuring device 100 can detect respiratory waveform patterns. For example, if a Cheyne-Stokes type respiratory waveform pattern is detected, which repeats a periodic waveform in which the depth and number of breaths gradually increase and then gradually decrease until finally apnea, as shown in Figure 17A, it may suggest a relationship between the subject having a brain disease, uremia, heart disease, poisoning, or being in the terminal stage of various diseases.

[0134] As shown in Figure 17B, if a Biot-type respiratory waveform pattern is detected in which shallow breaths of the same depth continue for 4-5 times, followed by apnea, and this cycle repeats, it may suggest a relationship between the subject and conditions such as brain tumor, meningitis, or medullary injury.

[0135] As shown in Figure 17C, if extremely large, sustained respiration occurs and a Kussmaul-type respiratory waveform pattern with a periodic waveform accompanied by high noise is detected, it may suggest a relationship between the subject being in diabetic coma or uremic coma.

[0136] (4) Related technologies for monitoring respiratory status include, for example, thoracic impedance analysis in combination with ECG (Electrocardiogram), and analysis of pulse waves to determine respiratory rate. There are methods for measuring respiratory rate. However, methods using thoracic impedance analysis in conjunction with ECG, or methods analyzing pulse waves, are significantly affected by changes in body movement, and measuring respiratory rate requires the subject to be at rest. In addition, while capnometers that measure CO2 concentration in exhaled breath are widely used to monitor respiratory status in clinical settings, their lack of portability makes them difficult to apply to continuous monitoring of the elderly in places like evacuation centers.

[0137] Furthermore, when the respiratory rate measuring device 100 determines the respiratory rate from the detection data of the CO2 sensor 110, it applies a bandpass filter to the detection data of the CO2 sensor 110 in order to reduce the influence of CO2 concentration changes caused by factors other than respiration. However, when a subject breathes while coughing, yawning, or talking, the CO2 concentration changes caused by coughing, yawning, or talking may have frequency components close to those of respiration. Therefore, even if a bandpass filter is applied to the detection data of the CO2 sensor 110, breathing accompanied by coughing, yawning, or talking, which are noise-type body movements that interfere with accurately determining the subject's respiratory rate, are not removed, and the subject's respiratory rate may not be determined to an appropriate number.

[0138] Therefore, the respiratory rate measuring device 100 is equipped with a noise detection sensor 120 near the CO2 sensor 110 to detect noise-type body movements that cause fluctuations in CO2 concentration due to factors other than the subject's breathing. By providing the noise detection sensor 120 in this way, the respiratory rate measuring device 100 removes respiratory data associated with coughing, yawning, talking, etc., as noise data before determining the subject's respiratory rate. This removes the influence of cardiopulmonary functions other than breathing, such as coughing, yawning, and talking, in addition to changes in the subject's body movements, allowing for a more accurate determination of the subject's respiratory rate.

[0139] In particular, when the respiratory rate measuring device 100 uses a microphone or acceleration sensor as the noise detection sensor 120, it performs noise reduction on the CO2 concentration fluctuation data detected by the CO2 sensor 110, excluding the detection data for periods in which noise-type body movements are detected by the noise detection sensor 120, before determining the respiratory rate. By operating in this manner, the respiratory rate measuring device 100 can reduce false detections of the respiratory rate caused by cardiopulmonary functions other than breathing, such as coughing, yawning, and talking.

[0140] Furthermore, when a humidity sensor or pressure sensor is used as the noise detection sensor 120, the respiratory rate measuring device 100 determines the respiratory rate after estimation based on the analysis results of the waveform pattern of the measurement data from the CO2 sensor 110 and the waveform pattern of the detection data related to noise-type body movement detected by the noise detection sensor 120. By operating in this manner, the respiratory rate measuring device 100 can similarly reduce false detections of the respiratory rate due to the influence of cardiopulmonary functions other than breathing, such as coughing, yawning, and talking.

[0141] As described above, by applying the respiratory rate measuring device 100, system 1, and program of this embodiment, it becomes possible to accurately determine the respiratory rate of a subject without being affected by noise-type body movements such as changes in the subject's body movement or cardiopulmonary functions other than breathing, such as coughing, yawning, and talking. In particular, the respiratory rate measuring device 100 uses a small equivalent carbon dioxide type CO2 sensor as a means of detecting fluctuation data of CO2 concentration contained in the subject's exhaled breath. Therefore, the CO2 sensor can be easily attached to clothing such as sanitary masks and face shields that cover the area around the subject's mouth, or to various medical devices used around the subject's mouth, such as oxygen masks, making it possible to measure the subject's respiratory rate in a wearable and highly versatile manner.

[0142] (5) The respiratory rate measuring device 100 uses a small wearable sensor as a CO2 sensor 110 that detects fluctuations in the CO2 concentration in the subject's exhaled breath. For example, in order to respond to sudden changes in the condition of elderly people in evacuation shelters during disasters, the sensor body 105 including the CO2 sensor 110 can be attached to the sanitary mask or face shield of the elderly person who will be the subject, making it possible to easily determine the respiratory rate of the subject and manage the health status of each subject. In particular, even in evacuation shelters in sparsely populated areas where medical resources are insufficient, by using an easily attachable wearable sensor, a wide range of vital information related to respiration, such as the respiratory rate, breathing rhythm, depth, and breathing pattern of the subject, can be monitored remotely, making it possible to appropriately manage the health status of elderly people and other subjects.

[0143] Variation

[0144] The embodiments described above are illustrative examples of one aspect of the present disclosure. The embodiments may also be implemented as the following illustrative modifications.

[0145] In the above embodiment, a configuration was illustrated in which the respiratory rate measuring device 100 comprises a sensor body 105 and a microcomputer 130. However, a sensor module equipped with 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 one that integrates the microcomputer 130 for processing the measured data. In this case, the connecting wire 140 can be omitted.

[0146] In the above embodiment, a configuration in which the microcomputer 130 includes an operation unit 133 and a display unit 134 was illustrated. 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 configurations provided by, for example, a computer device such as a smartphone or tablet. This means that the microcomputer 130 does not necessarily have to be composed of a single hardware device. Therefore, the microcomputer 130 can be composed of one or more hardware devices.

[0147] 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 without substantially departing from the novelty and effects of the present disclosure. Accordingly, all such modifications are included within the scope of the present disclosure.

[0148] For example, any term that appears at least once in the specification or drawings alongside a broader or synonymous term may be replaced with that different term anywhere in the specification or drawings. Furthermore, the configuration and operation of the respiratory rate measuring device are not limited to those described in one embodiment of this disclosure, and various modifications are possible. [Explanation of symbols]

[0149] 1 System 2 Network 10 Server devices 11, 31 Communications Department 12, 32 Operation section 13, 33 Display section 14, 34 Control Unit 14a Receiver 14b Judgment part 14c Transmitter 14d Generator 15 ROM 16 RAM 20 Data storage unit 30 Administrator terminals 35 Storage section 100 Respiratory rate measuring device 105 Sensor body 110 CO2 sensor (first sensor device) 120 Noise detection sensor (second sensor device) 130 Microcomputers 131 Control Unit 131a Receiving unit 131b Judgment part 131c Transmitter 132 Communications Department 133 Operation section 134 Display section 135 ROM 136 RAM 137 Data Processing Unit 140 connecting wires 140a connecting wire 140b Connection Line 150 connecting members 151 Hook 152 Necklace components (wearable devices, body orthotics) M1 Sanitary Mask (Wearable Device, Head Orthopedic Device) M2 Oxygen Mask (Wearable Device, Head Orthopedic Device) M3 Heated Humidifier (Wearable Orthopedic Device, Head Orthopedic Device) M3a tubing

Claims

1. In a respiratory rate measuring device that measures respiratory rate, CO contained in the subject's exhaled breath ２ A first sensor device for acquiring concentration fluctuation data, Frequency data is generated by frequency-converting the aforementioned fluctuation data, the frequency components of the subject's natural breathing are identified in the aforementioned frequency data, and the CO corresponding to those components is determined. ２ The system includes a determination unit that determines the respiratory rate based on the number of concentration peaks, The determination unit determines the number of breaths by counting the peak of the CO2 concentration where the maximum value of the CO2 concentration exceeds a predetermined threshold as one breath. Respiratory rate measuring device.

2. The system includes a second sensor device that detects noise-type body movements of the subject that occur during the measurement period of the first sensor device, The determination unit determines the respiratory rate by excluding the portion of the fluctuation data that corresponds to the occurrence time of the noise-type body movement. The respiratory rate measuring device according to claim 1.

3. In a respiratory rate measuring device that measures respiratory rate, CO contained in the subject's exhaled breath ２ A first sensor device for acquiring concentration fluctuation data, A second sensor device for detecting noise-type body movements of the subject that occur during the measurement period of the first sensor device, The system includes a determination unit that determines the number of breaths by excluding the portion of the fluctuation data corresponding to the occurrence time of the noise-type body movement from the fluctuation data, and counting the peak of the absolute value of the CO2 concentration that exceeds a predetermined threshold as one breath. Respiratory rate measuring device.

4. The second sensor device is at least one of a microphone element, an acceleration sensor, or a pressure sensor. The respiratory rate measuring device according to claim 2 or 3.

5. Furthermore, the respiratory rate measuring device includes a communication unit that transmits the fluctuation data and the noise-type body movement detection data. The respiratory rate measuring device according to claim 2 or 3.

6. The aforementioned noise-type body movement is at least one of the following: a change in the subject's body movement or a cardiopulmonary function other than respiration of the subject. The respiratory rate measuring device according to claim 2 or 3.

7. The first sensor device is an equivalent carbon dioxide type CO2 sensor. ２ It is a sensor, The respiratory rate measuring device according to claim 1 or 3.

8. The first sensor device is a wearable sensor that can be attached to the subject. The respiratory rate measuring device according to claim 1 or 3.

9. Furthermore, the respiratory rate measuring device includes an attachment member that can be attached to at least one of the head or body orthoses worn by the subject. The respiratory rate measuring device according to claim 1 or 3.

10. Identifying the frequency components included in the range of 0.275 Hz to 0.475 Hz, The respiratory rate measuring device according to claim 1.

11. The first sensor device detects CO2 in the subject's exhaled breath. ２ To obtain data on the variation in concentration, The processor generates frequency data by frequency-converting the aforementioned fluctuation data, The processor identifies the frequency components of the subject's natural breathing from the frequency data, and the CO corresponding to those frequency components. ２ This includes determining the respiratory rate based on the number of concentration peaks, The processor determines the number of breaths by counting the peak of the CO2 concentration where the maximum value of the CO2 concentration exceeds a predetermined threshold as one breath. How to measure respiratory rate.

12. The second sensor device includes detecting noise-type body movements of the subject that occurred during the measurement period of the first sensor device, The processor determines the respiratory rate by excluding the portion of the variable data that corresponds to the occurrence time of the noise-type body movement. The respiratory rate measurement method according to claim 11.

13. A method for measuring respiratory rate, The first sensor device acquires data on fluctuations in the CO2 concentration contained in the subject's exhaled breath, The second sensor device detects the noise-type body movements of the subject that occurred during the measurement period of the first sensor device, The process includes determining the number of breaths by a processor, excluding the portion of the fluctuation data corresponding to the occurrence time of the noise-type body movement, and counting the peak of the CO2 concentration where the absolute peak value of the CO2 concentration exceeds a predetermined threshold as one breath. How to measure respiratory rate.

14. The first sensor device is an equivalent carbon dioxide type CO2 sensor. ２ It is a sensor, The respiratory rate measurement method according to claim 11 or 13.

15. Identifying the frequency components included in the range of 0.275 Hz to 0.475 Hz, The respiratory rate measurement method according to claim 11.

16. A program configured to run on at least one processor, Includes an instruction to perform the respiratory rate measurement method according to claim 11 or 13, program.

17. At least one processor, A system comprising a program that causes the aforementioned processor to function as at least a communication unit and a determination unit, The aforementioned communication unit contains CO2 contained in the subject's exhaled breath. ２ It is configured to acquire data on the variation in concentration, The determination unit generates frequency data obtained by frequency-converting the fluctuation data, identifies a frequency component during natural breathing of the subject in the frequency data, and based on the number of peaks of the CO ２ concentration corresponding to the frequency component, is configured to be able to determine the respiratory rate of the subject, The determination unit determines the number of breaths by counting the peak of the CO2 concentration where the maximum value of the CO2 concentration exceeds a predetermined threshold as one breath. system.

18. The communication unit is configured to acquire detection data of noise-type body movements of the subject, The determination unit determines the respiratory rate by excluding the portion of the fluctuation data that corresponds to the occurrence time of the noise-type body movement. The system according to claim 17.

19. At least one processor, A system comprising a program that causes the aforementioned processor to function as at least a communication unit and a determination unit, The communication unit is configured to acquire fluctuation data of the CO2 concentration contained in the subject's exhaled breath and detection data of noise-type body movements of the subject that occurred during the measurement of the fluctuation data. The determination unit determines the number of breaths of the subject by excluding the portion of the fluctuation data corresponding to the occurrence time of the noise-type body movement from the fluctuation data, and counting the peak of the absolute value of the CO2 concentration that exceeds a predetermined threshold as one breath. system.

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