A system for measuring health status through respiration, and a program for the system for measuring health status through respiration.

Abstract

To provide a health condition measuring system by respiration by which a respiratory condition of a driver is monitored, and compared to an average value and a standard deviation of time series data on the respiration of the driver acquired beforehand; the driver's drowsiness, fatigue, etc. are determined from the result of the comparison of the standard deviation, and the driver is urged to take precautions; objective judgement materials on health conditions are established for enabling the driver to perform safe driving both physically and mentally; and an unhappy accident that involves a third party is prevented from occurring.SOLUTION: A health condition measuring system by respiration includes a driver's terminal 11, the Internet N interposed between a manager's terminal 31 and the driver's terminal 11, and the manager's terminal 31. A respiratory condition of the driver M is monitored and compared to an average value and a standard deviation of time series data on the respiration of the driver M acquired beforehand. Stress, drowsiness, fatigue, etc. of the driver M are determined from the result of the comparison of the standard deviation, and the driver M is urged to take precautions according to the result of the determination.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a health condition measurement system by respiration and a program for the health condition measurement system by respiration. Specifically, for example, with the aging of society, the retirement of professional drivers such as taxi drivers is increasing, the labor shortage in the industry is becoming more serious, and the risk of accidents during driving for the elderly, including professional drivers, is increasing. Against this background, especially by measuring the respiration of professional drivers such as taxi drivers during driving, the physical and mental conditions of the driver can be grasped in real time, an objective judgment material for a healthy state in which safe driving can be performed both physically and mentally can be established, and an unfortunate automobile accident involving a third party can be prevented. The present invention relates to a health condition measurement system by respiration and a program for the health condition measurement system by respiration.

Background Art

[0002] The medical basis of the health condition measurement system by respiration of the present invention is based on the health management method (Homma Method) developed by Dr. Ikio Homma, a world authority on brain physiology and respiratory physiology, who is the inventor of the present invention. Through the long-term research of the inventor of the present application, it has been clarified that respiration also changes due to the emotions of human joys, sorrows, and pleasures and changes in physical conditions, and it is based on the foundation that measuring respiration during driving is an effective means for judging the physical and mental health status of the driver in real time.

[0003] Currently, sensors for monitoring human health conditions have been developed and put into practical use. As an example, by simply attaching a sensor to the chest of a human body (subject), the PO2 (blood oxygen saturation), breath sound, respiratory rate, heart rate, and heat of the human body can be measured, so that symptoms of pneumonia can be detected early.

[0004] Therefore, it can be considered that in the future, a system will appear that can grasp the physical and mental state by attaching it to the human body and can judge the grasped state by AI.

[0005] However, while it has been possible to understand the physical condition of the subject, in reality, there are no established diagnostic criteria or medical law restrictions regarding the respiration of the subject.

[0006] Patent Document 1 discloses a respiratory monitoring system that the present applicant previously proposed and for which a utility model registration was obtained.

[0007] The respiratory monitoring system according to Patent Document 1 includes: a respiratory detection means for detecting the subject's normal breathing and breathing during stress / anxiety; a respiratory rate calculation means for calculating the normal respiratory rate and the increased respiratory rate during stress / anxiety based on the normal breathing and breathing during stress / anxiety; a storage means for storing the normal respiratory rate; a means for estimating the generation of emotions associated with the increased respiratory rate during stress / anxiety; a respiratory rate induction information generation means that refers to the storage means in accordance with the estimation of the subject's emotional generation and guides the subject's respiratory rate during stress / anxiety back to the normal respiratory rate; and an information terminal that displays the normal respiratory rate and the increased respiratory rate during stress / anxiety calculated by the respiratory rate calculation means, and outputs respiratory rate induction information generated by the respiratory rate induction information generation means. The system is configured to guide and restore the subject's increased respiratory rate during stress / anxiety back to the normal respiratory rate, allowing for an objective assessment of the subject's health status while understanding the subject's physical and mental condition.

[0008] However, in the case of the respiratory monitoring system described in Patent Document 1, the system attempts to objectively assess the subject's health status while understanding their physical and mental condition by guiding and restoring the increased respiratory rate to a normal respiratory rate based on the estimation of the subject's emotional generation associated with increased respiration during stress and anxiety. Providing established diagnostic criteria for the respiration of the human body, which is the subject of this study, has not always been easy. [Prior art documents] [Patent Documents]

[0009] [Patent Document 1] Registered Utility Model No. 3232012 Gazette [Overview of the Initiative] [Problems that the invention aims to solve]

[0010] The present invention was developed in view of the above-mentioned circumstances in the conventional era, and provides a respiratory health status measurement system and a program for said respiratory health status measurement system that accurately monitors the respiratory state of a subject with a relatively simple configuration, compares it with the mean and standard deviation of time-series data of the subject's respiration that has been acquired in advance, determines the subject's stress, drowsiness, fatigue, etc. based on the standard deviation comparison result, and is configured to warn the subject in advance, thereby establishing objective criteria for determining the health status necessary for safe driving both physically and mentally, and preventing unfortunate automobile accidents that involve third parties. [Means for solving the problem]

[0011] The present invention provides a respiratory health status measurement system that is attached to a driver and monitors their respiratory state to detect respiratory time-series data; an existing time-series data storage unit that stores the mean and standard deviation of the driver's respiratory time-series data measured in advance; a program memory that stores a program that performs preprocessing consisting of outlier removal processing, moving average calculation processing for noise reduction, and graphing processing on the respiratory time-series data detected by the respiratory time-series data detection unit and the driver's respiratory time-series data measured in advance, and analysis processing consisting of comparison and determination with the mean and standard deviation of the preprocessed respiratory time-series data; an alert generation unit that issues an alert according to the comparison and determination result; and a communication interface that communicates with the administrator terminal described later via the Internet. The main features of this system are that it comprises a driver terminal, an internet connection interposed between the administrator terminal and the driver terminal, an existing time-series data storage unit that stores the average value and standard deviation of time-series data of respiration for any number of subjects measured in advance, a program memory that stores a program that performs preprocessing consisting of outlier removal processing, moving average calculation processing for noise reduction, and graphing processing for the time-series data of respiration of any number of drivers measured in advance and respiration time-series data transmitted from each driver terminal, and analysis processing consisting of comparison and judgment with the average value and standard deviation of the preprocessed respiration time-series data, an alert information transmission unit that generates alert information according to the comparison and judgment result and sends it to the driver terminal, and a communication interface that communicates with the driver terminal via the internet. [Effects of the Invention]

[0013] Claim 1 According to the invention, It becomes possible to accurately grasp the driver's condition while driving and take measures to resolve related problems, thereby preventing accidents from occurring. Furthermore, it becomes possible to realize a health status measurement system based on respiration that enables the establishment of established diagnostic criteria for human respiration. By accurately understanding the driver's condition while driving from the perspectives of stress, drowsiness, and fatigue, and taking measures to resolve related problems, it becomes possible to prevent accidents from occurring. Furthermore, it is possible to realize and provide a health status measurement system based on respiration that enables the establishment of established diagnostic criteria for human respiration.

[0014] Claim 2 According to the described invention, Claim 1 a health state measurement system similar to the described invention can be realized and provided.

[0016] Claim 3 According to the invention of Claim 1 or 2 in the invention of , since the alert generation unit is configured to issue an alert by vibration sound, characters, voice, buzzer sound, chime sound, etc., a respiration-based health state measurement system that can recognize alerts in various manners can be realized and provided.

[0017] Claim 4 According to the invention of Claim 1 or 2 in the invention of , since the driver terminal has a configuration combining a smart watch and a smart phone, a respiration-based health state measurement system using existing devices can be easily realized and provided.

[0018] [[ID=2(1]] Claim 5 According to the invention of Claim 1 or 2 in the invention of , since the respiration time-series data detection unit has a configuration of any one of a ring shape, a bracelet shape, a shape attachable to the driver's chest, and a sheet shape installed on the seat surface where the driver sits, a respiration-based health state measurement system using existing devices can be easily realized and provided.

Brief Description of Drawings

[0021] [Figure 1] FIG. 1 is a block diagram showing the overall configuration of a respiration-based health state measurement system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram showing the configuration of a crew side terminal in a respiration-based health state measurement system according to this embodiment. [Figure 3] FIG. 3 is a block diagram showing the configuration of a management entity side terminal in a respiration-based health state measurement system according to this embodiment. [Figure 4] FIG. 4 is a diagram showing the outlier removal process of time-series data by an analysis application program used in a respiration-based health state measurement system according to this embodiment. [Figure 5] Figure 5 is a waveform diagram after moving average processing of time series data by an analysis application program used in the health state measurement system based on respiration according to this embodiment. [Figure 6] Figure 6 is a waveform diagram of time series data graphed by an analysis application program used in the health state measurement system based on respiration according to this embodiment. [Figure 7] Figure 7 is an image diagram when an alert is issued by an analysis application program used in the health state measurement system based on respiration according to this embodiment. [Figure 8] Figure 8 is a diagram showing the analysis data of crew member F on December 2 analyzed by an analysis application program used in the health state measurement system based on respiration according to this embodiment. [Figure 9] Figure 9 is a diagram showing the analysis data of crew member B on December 4 analyzed by an analysis application program used in the health state measurement system based on respiration according to this embodiment. [Figure 10] Figure 10 is a diagram showing the analysis data of crew member F on November 9 analyzed by an analysis application program used in the health state measurement system based on respiration according to this embodiment. [Figure 11] Figure 11 is a diagram showing the analysis data of crew member D on November 10 analyzed by an analysis application program used in the health state measurement system based on respiration according to this embodiment.

Embodiments for Carrying Out the Invention

[0022] The present invention aims to provide a respiratory health status measurement system that accurately monitors a driver's respiratory state, compares it with the mean and standard deviation of previously acquired time-series respiratory data of the subject, determines the subject's stress, drowsiness, fatigue, etc. based on the standard deviation comparison result, and warns the driver in advance, thereby establishing objective criteria for determining the driver's physical and mental health condition that enables safe driving, and preventing unfortunate accidents involving third parties. The system comprises a respiratory time-series data detection unit attached to the driver to monitor the driver's respiratory state and detect respiratory time-series data; an existing time-series data storage unit that stores the mean and standard deviation of the driver's respiratory time-series data measured in advance; a program memory that stores an analysis program that performs preprocessing consisting of outlier removal processing, moving average calculation processing for noise reduction, and graphing processing on the respiratory time-series data detected by the respiratory time-series data detection unit and the driver's respiratory time-series data measured in advance, and analysis processing consisting of comparison and judgment with the mean and standard deviation of the preprocessed respiratory time-series data; and an analysis program that stores an analysis program that performs analysis according to the comparison and judgment result. Each driver terminal is equipped with an alert generation unit that issues an alert, a data display unit, a data manipulation processing unit, and a communication interface that communicates with the administrator terminal described below via the Internet; the Internet is interposed between the administrator terminal and the driver terminals; an existing time-series data storage unit that stores the average value and standard deviation of time-series data of respiration for any number of drivers measured in advance; outlier removal processing and moving average calculation processing for noise reduction applied to the time-series data of respiration for any number of drivers measured in advance, and the respiration time-series data transmitted from each driver terminal. The system comprises a program memory storing a program that performs preprocessing consisting of graphing, and analysis processing consisting of comparison and determination of the mean and standard deviation of the preprocessed respiration time-series data; a business information storage unit that stores business information for any number of drivers; an alert information transmission unit that generates and sends alert information according to the comparison and determination results; a data display unit; a data manipulation processing unit; an analysis processing result storage unit that stores the analysis processing results; and a communication interface that communicates with the driver terminal via the internet. The administrator terminal is equipped with the following:This was achieved by receiving pre-processed respiratory time-series data transmitted from a specific driver's terminal, adding the corresponding subject's work information read from the work information storage unit to the respiratory time-series data, and then transmitting it to the driver's terminal. [Examples]

[0023] The following describes in detail an embodiment of the health status measurement system 1 by respiration according to the present invention, with reference to the drawings.

[0024] As shown in Figure 1, the respiratory health status measurement system 1 according to this embodiment includes a driver terminal 11, an administrator terminal 31, and an internet connection N interposed between the administrator terminal 31 and the driver terminal 11.

[0025] The devices in the driver terminal 11 are primarily wearable devices such as smartwatches and smartphones.

[0026] To elaborate further, the driver terminal 11, which is assigned to each driver, is composed of, for example, a combination of a smartwatch and a smartphone. The smartwatch is attached to the driver M, for example, on their wrist, and is equipped with a respiratory time-series data detection unit 12 that monitors their breathing state and detects respiratory time-series data. The smartphone is equipped with an existing time-series data storage unit 13 that stores the average value and standard deviation of the driver M's respiratory time-series data measured in advance, and the respiratory time-series data detected by the respiratory time-series data detection unit 11, as well as the driver's respiratory time-series data measured in advance. The system includes a program memory 14 that stores a program (preprocessing program and analysis program) which performs preprocessing consisting of outlier removal processing, moving average calculation processing for noise reduction, and graphing processing, as well as analysis processing consisting of comparison and determination of the mean and standard deviation of the preprocessed respiration time series data; an alert generation unit 15 including a vibration source, speaker, etc. that issues alerts according to the pre-comparison determination result; a data display unit 16; a data manipulation processing unit 17; a communication interface 18 that communicates with an administrator terminal 31 via the Internet N; and a control unit 19.

[0027] Furthermore, communication between the smartwatch and the smartphone is carried out using wireless communication standards such as Bluetooth® or Wi-Fi.

[0028] Furthermore, the respiratory time-series data detection unit may be anything other than a smartphone, such as a ring-shaped device, a bracelet-shaped device, a device that can be attached to the driver's chest, or a sheet-shaped device that can be placed on the seat where the driver sits.

[0029] The administrator terminal 31 includes an existing time-series data storage unit 32 that stores the mean and standard deviation of time-series data of each driver's respiration measured in advance, a program memory 33 that stores a program (pre-processing program and analysis program) that performs pre-processing consisting of outlier removal processing, moving average calculation processing for noise reduction, and graphing processing on the time-series data of the arbitrary number of drivers' respiration measured in advance and the respiration time-series data transmitted from each driver terminal 11, and analysis processing consisting of comparison and determination with the mean and standard deviation of the pre-processed respiration time-series data, and stores work information for each of the arbitrary number of drivers M. The system comprises a business information storage unit 34, an alert information transmission unit 35 that generates and transmits alert information according to the comparison judgment result, a data display unit 36, a data manipulation processing unit 37, an analysis processing result storage unit 38 that stores the analysis processing result, a communication interface 39 that communicates with the driver terminal 11 via the Internet N, and a control unit 40. The administrator terminal 31 is configured to receive pre-processed respiratory time-series data transmitted from a specific driver terminal 11, add the business information of the corresponding driver M read from the business information storage unit 34 to the respiratory time-series data, and transmit it to the driver terminal 11.

[0030] The aforementioned Internet N utilizes a commonly used communication network.

[0031] In this embodiment, program memories 14 and 33 containing programs for analysis processing are provided in both the driver terminal and the administrator terminal, but the analysis processing may be performed only in the driver terminal.

[0032] Furthermore, regarding the generation of alert information, both the driver terminal and the administrator terminal are equipped with an alert generation unit 15 and an alert information transmission unit 35, but these may also be configured to generate alert information only on the driver terminal.

[0033] Furthermore, in this embodiment, the health status measurement system based on respiration is configured using a driver terminal and an administrator terminal, but it is also possible to configure the system using only the driver terminal. In that case, it is also possible to send the alert information generated by the alert information generation unit to a pre-configured other terminal (for example, a terminal of the taxi company where the driver works, a terminal of the driver's family, etc.).

[0034] Furthermore, if the terminal on the management side is replaced with, for example, a smartphone of the driver's family member, and information is received in real time, it can also be used as a driver monitoring function between the family and the driver.

[0035] Next, we will explain the purpose of the experiments conducted in relation to the embodiments of the present invention.

[0036] 1. Objective of the experiment a; In this experiment, the aim is to understand the physical and mental condition of professional drivers in real time by measuring their breathing while driving, and to establish objective criteria for determining a healthy state of mind that allows for safe driving, transcending conventional age-based criteria.

[0037] As a result, this will help prevent unfortunate car accidents that involve third parties.

[0038] b; Respiratory measurements in the experiment aim to understand the psychological stress, drowsiness, fatigue, and other physical and mental conditions of the subject (driver) while driving, and to encourage measures to resolve any issues that may pose a risk of leading to health problems.

[0039] Measuring respiratory rate is a relatively new concept, and although its definition of abnormal values ​​has been scientifically elucidated as the HOMMA METHOD, unlike vital signs such as heart rate and blood pressure, there are no established diagnostic criteria or legal restrictions under medical law.

[0040] c;Therefore, at this stage, we believe that the most effective way to quickly resolve the challenges facing the freight and passenger transport industry is to introduce a system that manages mental and physical health conditions such as psychological stress, drowsiness, and fatigue through respiratory measurement, which is not intended for diagnosis and is not subject to medical or medical legal regulations. In the future, we plan to fully implement this system as a core platform for health management and operational management of professional drivers, which has high expandability and potential for development, enabling the detection of signs of heart disease and brain disease from simultaneously measured heart rate, blood pressure, etc.

[0041] 2. Challenges facing the customer transportation industry The increasing number of professional drivers retiring due to an aging population is further exacerbating the labor shortage in the industry.

[0042] Furthermore, the risk of accidents involving elderly drivers, including professional drivers, is increasing.

[0043] 3. Medical evidence supporting the effectiveness of respiratory measurement (Homma Method) and its application to solving industry challenges.

[0044] a; Through the long-term research of Dr. Ikuo Honma (Professor Emeritus, Showa University School of Medicine / Former President, Tokyo Ariake Medical University), a world authority on neurophysiology and respiratory physiology, it has been revealed that breathing also changes in response to changes in human emotions such as joy, anger, sadness, and pleasure, as well as changes in physical condition.

[0045] Therefore, considering that measuring breathing while driving is an effective means of assessing the driver's physical and mental state in real time, we will conduct experiments with taxi drivers and, in the near future, lead to full-scale operation as a core platform for health management and operational management for all professional drivers involved in the passenger and freight transport industry.

[0046] b; The purpose of measuring respiration in this experiment is not to diagnose illnesses or symptoms in subjects while driving, but rather to understand the psychological stress, sleepiness, and physical stress of subjects while driving, and to encourage measures to resolve such problems in advance.

[0047] Therefore, the aim is to prevent accidents by issuing warnings in response to changes in respiratory rate caused by stress or drowsiness while driving, and by encouraging appropriate breaks to alleviate drowsiness and stress.

[0048] c; Measuring respiratory rate is a new concept, and unlike vital signs such as heart rate and blood pressure, there are no established diagnostic criteria or medical law restrictions regarding the setting of abnormal values.

[0049] Therefore, at this stage, we believe that the most effective way to quickly resolve the challenges facing the freight and passenger transport industry is to fully implement this system as a core platform for health management and operational management of professional drivers using respiratory measurement, which is not intended for diagnosis and is not subject to medical or legal regulations.

[0050] d; To further improve the accuracy of assessing the physical and mental state of professional drivers based on their respiratory changes while driving, we will add vital sign measurements such as heart rate and blood pressure to the respiratory measurement platform, as well as image recognition of the driver during driving using a dashcam, and verify the correlation / complementary effects with respiratory change data to develop a comprehensive system.

[0051] e; While predicting / diagnosing brain and heart diseases, which could be considered the ultimate goal of health measurement, is difficult under current medical laws, abnormal respiratory rates are actually caused not only by drowsiness, stress, and anxiety, but also by changes in all aspects of the circulatory and respiratory systems.

[0052] Therefore, with an eye on the deregulation of telemedicine, which is becoming a new social issue, we will develop a core platform that will help prevent traffic accidents caused by physical and mental abnormalities among professional drivers by promoting the widespread use of a mental and physical health management platform using respiratory measurement, accumulating operational experience through vital sign measurement and improved driver image accuracy using dashcams, and building up predictive results.

[0053] Next, I will explain the details of the experiment.

[0054] Participants and duration of the experiment; The experiment involved six taxi drivers working for a taxi company and was conducted over a period of approximately one month.

[0055] Prior to the experiment, a five-day preliminary experiment period was set aside to allow the participants to become familiar with operating the devices. However, one of the participants resigned during the preliminary experiment period, so another crew member was added to the measurement group.

[0056] Acquisition of respiratory rate data; In this experiment, respiratory rate was measured using a wearable device manufactured by Quantum Operation, Inc.

[0057] Data was recorded using the company's smartphone application software, which was synchronized with the wearable device.

[0058] Regarding methods for analyzing respiratory rate data; All analysis of the recorded data was performed using Microsoft Excel® spreadsheet software.

[0059] The data analysis procedure is described below, in the order of preprocessing followed by analysis.

[0060] Outlier removal (preprocessing); To remove outliers introduced due to body movement during measurement, the following equations 1 and 2 were used to identify them.

[0061] Here, y in the time series data n The difference Δy between the data at a given point in time and the data immediately before and after it. n If there are 10 or more times, y n The data from that point in time was treated as an outlier and excluded from the analysis.

[0062]

number

[0063]

number

[0064] Figure 4 shows an example of time-series data related to outlier removal in this case.

[0065] 3. Noise reduction (pre-processing) Noise reduction was performed to observe the time-series data from an overview perspective. Specifically, the following equation 3 was used for y n 3-point moving average of the data at each point in time (y n ) ― The result was calculated.

[0066]

number

[0067] Figure 5 shows an example of time series data after applying a three-point moving average in this case.

[0068] 4. Adding crew information In order to reflect the driver's daily reports and survey results in chronological data, the following items were copied into Excel (registered trademark) from the data shared by the taxi company. In this case, the items transcribed from the driver's log are items 1 to 6 below. 1. Driving hours 2. Number of rides 3. Travel time 4. Disembarkation time 5.Break start time 6. Stop time The items transcribed from the survey results are listed below as 1 and 2. 1.Answer items 2.Response time

[0069] 5. Graphing the data (preprocessing) The time-series data processed and the crew information data were output as line graphs, and changes in respiratory rate during the crew were observed.

[0070] An example of graphed time-series data is shown in Figure 6.

[0071] Interviews with crew members; Based on the graphs showing increases and decreases in respiratory rate, we interviewed the crew members about their behavior at those points.

[0072] 5. Data Analysis Results a; Number of data analysis cases The average number of days worked during the experiment was 11 days. Of the 44 data points output from the device, 22 had significantly insufficient data due to device malfunctions during operation, or the measurements themselves were not recorded for any reason. These data points were excluded from the analysis.

[0073] Table 1 below shows examples of the number of days worked by the subject, the number of data points to be measured, and the number of data points to be excluded from measurement.

[0074] [Table 1]

[0075] b; Characteristics of respiratory rate during duty The following characteristics were observed in the graph, which combined time-series data and information from the driver's log. • The average respiratory rate during the shift was 19.3 breaths / minute. The average respiratory rate during riding was 19.6 breaths / minute, and the average respiratory rate during breaks was 18.4 breaths / minute.

[0076] Table 2 below shows examples of the average respiratory rate during duty, average respiratory rate during boarding and rest periods, and average number of completed questionnaires for the subjects.

[0077] [Table 2]

[0078] Furthermore, the following characteristics were observed as a result of interviews conducted using time-series data.

[0079] An increase in respiratory rate was observed when participants felt frustrated due to road conditions such as being caught in traffic jams. Increased respiratory rate was observed in situations such as taking a wrong turn or driving on unfamiliar roads. Increased respiratory rate was observed when the patient was experiencing stress or unpleasant situations, such as dealing with passengers.

[0080] These findings revealed that the crew's respiratory rate fluctuated during rest periods and when they felt irritated or anxious.

[0081] (Data analysis application program) To build a system that can quickly detect physical and mental abnormalities such as drowsiness, fatigue, anxiety, and stress in crew members, issue alerts in advance, and prompt appropriate measures such as breaks, we developed an analytical application program based on data obtained from experiments.

[0082] (Overview of the application program) The application program of this invention removes outliers and processes noise from CSV data, including respiratory rate, obtained from experiments, and then plots it as a line graph.

[0083] Furthermore, by setting arbitrary conditions on the plotted line graph, it is possible to display the range of a steady state in which no physical or mental abnormalities such as drowsiness or stress occur, as well as outlier values ​​that indicate the possibility of physical or mental abnormalities occurring.

[0084] (Analysis process: Setting of steady-state range and outliers) Based on the data obtained from the experiment, the range of the average value ± standard deviation for each individual driver was defined as the steady-state range, and values ​​exceeding this range were set as outliers.

[0085] The definition of this steady-state range uses the individual driver's mean ± standard deviation, rather than a fixed value. This is because the average respiratory rate varies from person to person and constantly fluctuates depending on an individual's physical condition and psychological state. Using a fixed value could lead to evaluation errors, such as consistently exceeding the steady-state range even when there is no influence from excessive anxiety, stress, or drowsiness.

[0086] Therefore, instead of using a fixed value, the average value ± standard deviation of the individual driver is used to set the steady-state range. Also, because it was considered that issuing alerts for every abnormal value outside the steady-state range would be excessively frequent, it was decided to treat values ​​where the three or four preceding plots containing the abnormal value show a continuous increase or decrease as the target value for an alert.

[0087] Figure 7 shows an example of how an alert is triggered when the respiratory rate increases.

[0088] Analysis results (analysis processing) in the application program An analysis was performed using an application program, and interviews were conducted with the crew based on the points at which anomalies were displayed. Details are provided below.

[0089] A: Day 20 after the start of the experiment: Analysis of crew member F Figure 8 shows the results of the analysis of crew member F using the application program.

[0090] Furthermore, we conducted interviews regarding the particularly increasing portion outside the steady-state range, and obtained the responses shown in Table 3. The results of these interviews are shown in Table 3.

[0091] [Table 3]

[0092] B: Day 22 after the start of the experiment: Analysis of crew member B; Figure 9 shows the results of the analysis of crew member B using the application program.

[0093] Furthermore, inquiries were conducted regarding the particularly increasing portion outside the steady-state range, and the responses shown in Table 4 were obtained.

[0094] [Table 4]

[0095] In all of the drivers mentioned above, there was a tendency for the moments when they experienced psychological changes such as irritation or anxiety at the point when the abnormal values ​​increased beyond the normal range to coincide. Furthermore, the moments when the values ​​decreased below the normal range were often observed during breaks, as confirmed in the driver's log.

[0096] Furthermore, although these are results from the preliminary experimental period, the following is a summary of the interviews conducted regarding the decrease in respiratory rate.

[0097] C: Preliminary experiment period, day 2: Analysis of crew member F Figure 10 shows the results of the analysis of crew member F using the application program.

[0098] Furthermore, an interview with crew member F yielded the following response, as shown in Table 5.

[0099] [Table 5]

[0100] D: Preliminary experiment period, day 3: Analysis of crew member D Figure 11 shows the results of the analysis of crew member D using the application program.

[0101] Furthermore, the interviews yielded the responses shown in Table 6.

[0102] [Table 6]

[0103] Based on these findings, it is possible to use the established steady-state range, abnormal values, and alert values ​​to detect crew anxiety, irritability, and tension in abnormal values ​​due to increased respiratory rate, and drowsiness or rest periods in abnormal values ​​due to decreased respiratory rate. Therefore, monitoring using this application is considered an effective method.

[0104] Further comments will be made regarding this embodiment.

[0105] This embodiment is a system that measures a taxi driver's breathing every two minutes using, for example, a smartwatch, and issues a warning when the driver is stressed or irritated (increased breathing rate) or drowsy (decreased breathing rate).

[0106] In other words, 1. Measure the average and standard deviation of each person's respiratory rate while awake beforehand. 2. The respiratory rate, measured every two minutes daily, is taken as a moving average over three to four breaths, and any readings outside the standard deviation are considered abnormal. 3. When an abnormal value is detected, the smartwatch vibrates or makes an audible alert to notify the driver that something is wrong. 4. The data recorded on the smartphone is sent to the taxi company, and the company will issue instructions such as allowing the driver to take a break.

[0107] In this test with taxi drivers, a smartwatch measures their breathing rhythm every two minutes and issues a warning if it deviates from a steady-state respiratory rate.

[0108] The steady state is defined as the standard deviation of the average respiratory rate measured in advance over a three-day period.

[0109] A respiratory rate above the standard deviation, i.e., a high respiratory rate, indicates a state of heightened stress, while a respiratory rate below the standard deviation, i.e., a low respiratory rate, indicates fatigue or drowsiness.

[0110] According to the respiratory health status measurement system 1 of this embodiment described above, it is possible to accurately grasp the psychological stress, sleepiness, and physical stress of the subject while driving, and take measures to resolve these issues. By issuing warnings in response to changes in respiratory rate due to stress and sleepiness, and by encouraging appropriate rest to alleviate sleepiness and stress, it is possible to prevent accidents from occurring.

[0111] Furthermore, according to the program for the health status measurement system 1 using respiration in this embodiment, the intended operation of the health status measurement system 1 can be reliably achieved by employing a pre-processing program that performs a series of processes and an analysis program that determines the level of stress and whether the subject is drowsy or tired.

[0112] In this demonstration experiment, data from half of the vehicles used during operation could be analyzed without missing values. The majority of the excluded data was due to insufficient data due to the device being removed or running out of battery, and this needs to be addressed in the future. In addition, approximately 20% of the data was not recorded at all, so a thorough review of data acquisition is necessary before conducting large-scale demonstration experiments in the future.

[0113] The application program in this invention enables real-time data processing, accuracy verification of anomaly value calculation, and real-time analysis of anomalies and alert values.

[0114] (Experimental results) This invention makes it possible to objectively evaluate the physical and mental state during respiratory measurement while driving, and in particular, it allows for evaluation of situations such as drowsiness and fatigue while driving, which are directly related to accidents, and anxiety and stress that can lead to dangerous driving.

[0115] This invention makes it possible to generate warnings, such as advance alerts to crew members, based on fluctuations in respiratory rate.

[0116] Furthermore, the present invention can solve the following objectives and problems. This enables easy and inexpensive measurement using smartwatches and smartphones, facilitating rapid adoption in the industry. While respiratory changes reflect the state of mind and body, this platform offers high scalability and versatility, enabling improved judgment accuracy through the combined use of other vital signs measurements and image recognition methods such as dashcams, as well as centralized management via connectivity to headquarters and business locations. As a core platform that allows "anyone, anywhere, anytime to easily manage their health," it is expected to penetrate beyond the freight and passenger transport industry into the construction and civil engineering sectors, and be integrated into social infrastructure as part of corporate health management, health management / promotion programs by local governments nationwide, and smart cities including telemedicine. • To address the labor shortage, the retirement age will be extended for older professional drivers who are deemed to be in good physical and mental health. To prevent traffic accidents caused by drivers experiencing physical or mental abnormalities while driving, such as drowsy driving, medical seizures, or extreme stress. • Development towards social infrastructure / smart cities • Increased healthy life expectancy and reduced healthcare costs for the elderly. • Reduction in the rate of mental illness among employees in companies, improvement in productivity, and enhancement of corporate value through the practice of health management. This system can measure the health status of drivers involved in all types of driving operations, not just taxi drivers, but also drivers of cargo vehicles, passenger cars, motorcycles, bicycles, heavy machinery, cranes, ships, aircraft, etc. [Industrial applicability]

[0117] The health status measurement system using respiration according to the present invention can prevent traffic accidents caused by mental and physical abnormalities of drivers while driving, such as drowsy driving, medical seizures, and extreme stress. It is suitable not only for professional drivers in the freight and passenger transport industry, but also for professional drivers in other industries, and even for general drivers in general. [Explanation of Symbols]

[0118] 1. Health status measurement system based on respiration 11. Driver terminal 12. Respiratory time-series data detection unit 13 Existing time-series data storage unit 14 Program Memory 15. Alert Generation Section 16. Data display section 17 Data Manipulation Processing Unit 18 Communication Interfaces 19 Control Unit 31 Administrator terminal 32 Existing time-series data storage unit 33 Program Memory 34 Business information storage unit 35 Alert Information Transmission Unit 36 Data display section 37 Data Manipulation Processing Unit 38 Analysis Processing Result Storage Unit 39 Communication Interface 40 Control Unit N Internet M Target Person

Claims

1. This breathing-based health measurement system allows for real-time assessment of a driver's physical and mental condition by measuring their breathing while driving. It establishes objective criteria for determining a driver's physical and mental health, enabling safe driving and potentially preventing unfortunate accidents involving third parties. A respiratory time-series data detection unit is attached to the driver to monitor their breathing status and detect respiratory time-series data. An existing time-series data storage unit that stores the mean and standard deviation of the time-series data of the driver's respiration measured in advance, A program memory stores an analysis program that performs analysis processing consisting of preprocessing, which includes outlier removal processing, moving average calculation processing for noise reduction, and graphing processing, on the respiration time-series data detected by the respiration time-series data detection unit and the driver's respiration time-series data measured in advance, and comparative judgment processing, which determines the range of the mean ± standard deviation of the preprocessed respiration time-series data as the steady range and determines values ​​exceeding the steady range as abnormal values. An alert generation unit that issues an alert according to the comparison judgment result, Data display unit, Data manipulation processing unit, A communication interface that communicates with the administrator terminal described later via the internet, Each driver terminal has, The internet is interposed between the administrator terminal and the driver terminal, An existing time-series data storage unit that stores the mean and standard deviation of time-series data of respiration for each driver, which has been measured in advance for any number of drivers, A program memory storing a program that stores a program that performs preprocessing consisting of outlier removal processing, moving average calculation processing for noise reduction, and graphing processing for time-series data of a predetermined number of drivers' respirations measured in advance, and respiration time-series data transmitted from each driver's terminal, and analysis processing consisting of determining the range of the mean ± standard deviation of the preprocessed respiration time-series data as the steady range and determining values ​​exceeding the steady range as abnormal values. A business information storage unit that stores business information for any number of drivers, An alert information transmission unit generates and transmits alert information according to the comparison judgment result, Data display unit, Data manipulation processing unit, An analysis processing result storage unit that stores the analysis processing results, A communication interface that communicates with the aforementioned driver terminal via the Internet, An administrator terminal equipped with, It is equipped with, A health status measurement system using respiration, characterized in that when the administrator terminal receives pre-processed respiration time-series data transmitted from a specific driver terminal, it adds the corresponding driver's work information read from the work information storage unit to the respiration time-series data and transmits it to the driver terminal.

2. This breathing-based health measurement system allows for real-time assessment of a driver's physical and mental condition by measuring their breathing while driving. It establishes objective criteria for determining a driver's physical and mental health, enabling safe driving and potentially preventing unfortunate accidents involving third parties. A respiratory time-series data detection unit is attached to the driver to monitor their breathing status and detect respiratory time-series data. An existing time-series data storage unit that stores the mean and standard deviation of the time-series data of the driver's respiration measured in advance, A program memory stores an analysis program that performs analysis processing consisting of preprocessing, which includes outlier removal processing, moving average calculation processing for noise reduction, and graphing processing, on the respiration time-series data detected by the respiration time-series data detection unit and the driver's respiration time-series data measured in advance, and comparative judgment processing, which determines the range of the mean ± standard deviation of the preprocessed respiration time-series data as the steady range and determines values ​​exceeding the steady range as abnormal values. An alert generation unit that issues an alert according to the comparison judgment result, Data display unit, Data manipulation processing unit, A communication interface that communicates with the administrator terminal described later via the internet, Each driver terminal has, The internet is interposed between the administrator terminal and the driver terminal, An existing time-series data storage unit that stores the mean and standard deviation of time-series data of respiration for each driver, which has been measured in advance for any number of drivers, The driver respiratory time-series data storage unit stores the aforementioned time-series data of any number of drivers measured in advance, as well as respiratory time-series data transmitted from each driver terminal, analysis processing result information, and alert information. A business information storage unit that stores business information for any number of drivers, Data display unit, Data manipulation processing unit, An analysis processing result storage unit that stores the analysis processing results transmitted from each of the aforementioned driver terminals, A communication interface that communicates with the aforementioned driver terminal via the Internet, An administrator terminal equipped with, It is equipped with, A health status measurement system using respiration, characterized in that when the administrator terminal receives pre-processed respiration time-series data transmitted from a specific driver terminal, it adds the corresponding driver's work information read from the work information storage unit to the respiration time-series data and transmits it to the driver terminal.

3. The respiratory health status measurement system according to claim 1 or 2, characterized in that the alert generating unit issues an alert using vibration, sound, text, voice, buzzer, chime, etc.

4. The driver terminal is characterized by comprising a smartwatch and a smartphone, as described in claim 1 or 2, for the respiratory health status measurement system.

5. The respiratory health status measurement system according to claim 1 or 2, characterized in that the respiratory time-series data detection unit is in one of the following shapes: ring shape, bracelet shape, shape that can be attached to the driver's chest, or sheet shape that is placed on the seat where the driver sits.

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