JP6649060B2 - Mental and physical condition diagnosis support device and biological information management system - Google Patents

Description

  The present invention relates to a psychosomatic condition diagnosis support device that supports diagnosis of a subject's psychosomatic condition using biological information, and a biometric information management system including the psychosomatic condition diagnostic support device.

  Today, it is called a stressed society.In such a situation, many people suffer from autonomic nervousness due to various stresses, causing indeterminate complaints that are difficult to identify the cause. It makes it difficult to maintain daily life. Along with that, it has become a great obstacle to corporate activities and daily family life, and the problem is becoming more acute.

  In order to deal with such a situation, legislation is being developed, and stress checks are becoming more important than ever. At present, an inquiry by a doctor is employed as a main method of stress check. For example, Patent Literature 1 discloses an apparatus for examining the degree of stress.

  The biological information acquisition device disclosed in Patent Literature 1 acquires fluctuations in beat intervals from body movements including beating vibrations of a subject using a vibration sensor attached to a chair, and obtains the stress level or the stress level of the subject. Calculate autonomic nervous activity.

JP 2015-66337 A

  It is not clear what stress is. For this reason, research / apparatus for measuring heart rate variability and pulse variability to evaluate autonomic nervous activity has been proposed again in the past 20 years, but has not been effective. For example, the biological information acquisition device disclosed in Patent Literature 1 calculates a ratio (LF / HF) between a low-frequency component LF and a high-frequency component HF of fluctuation of a beat interval, and compares this ratio with a reference value. Thus, the degree of stress is determined. However, such a method is not an effective evaluation method.

  The present invention has been made in view of the circumstances described above, and an object of the present invention is to provide a psychosomatic condition diagnosis support device that assists in detecting a stress state of a subject with higher accuracy, and a psychosomatic condition diagnosis support device. An object of the present invention is to provide a biological information management system including a device.

  For example, in occupations such as medical care, nursing care, childcare, and early childhood education, the number of retired people due to stress is large, and clinical psychologists and others intervene, but the actual results have not been improved. In view of such circumstances, the present inventors have clarified what stress is, and established an evaluation method through examination to solve a specific problem of reducing the number of retired people due to stress in a certain workplace. . There are two types of stress. These are stresses caused by daily interpersonal, social, and physical stimuli, and stresses associated with a decrease in the health of autonomic nervous activity caused by accumulation under certain conditions. The latter leads to depression and cardiovascular disease. On the other hand, stress such as retirement due to stress occurring in the workplace is the former. The conventional stress check using a medical questionnaire covers only the latter.

  Daily stress appears in the value of the sympathetic nervous activity obtained as the ratio (LF / HF) between the low-frequency component LF and the high-frequency component HF of fluctuations in heart rate variability (pulse variability), but this value changes every moment. Things. For this reason, it is not always possible to perform the measurement as in Patent Document 1 described above, but it is necessary to measure at the moment when stress is felt. The inventors have developed a possible device. The present inventors have found the present invention as a result of measuring biological information including sympathetic nervous activity for a large number of subjects and intensively examining them.

In order to achieve the above object, according to one aspect of the present invention, there is provided (1) a biological information input unit to which biological information of a subject detected in a time series is input; A state detection unit that detects the stress state of the subject based on the biological information, and a display unit that displays the stress state of the subject detected by the state detection unit, the biological information The input unit receives the biological information including heart movement information corresponding to the movement of the subject's heart, and the state detection unit determines from the heart movement information an RR interval that is a contraction interval of the subject's heart. Calculating the standard deviation of the RR interval in the coefficient calculation period by the RR interval variation coefficient calculated by dividing by the average value of the RR interval in the coefficient calculation period , to detect the stress state of the subject , The state detection unit is configured to calculate the coefficient The sympathetic nerve information indicating the activity state of the sympathetic nerve of the subject during the outgoing period is further calculated, and the display unit calculates the sympathetic nerve information corresponding to each of the coefficient calculating periods in the plotting period including the plurality of coefficient calculating periods. The autonomous nerve activity plot diagram in which a plurality of points having the RR interval variation coefficient and the sympathetic nerve information as coordinates are plotted on a two-dimensional plane is displayed, and the display unit displays a plurality of life times of the subject. A psychosomatic condition diagnosis support device characterized by displaying a plurality of autonomic nervous activity plot diagrams in each of a plurality of plot periods corresponding to a band .

According to the present invention, by using the RR interval variation coefficient, it is possible to detect the stress state including the activity state of the entire autonomic nerve, so that the stress state of the subject can be detected more accurately.
In addition, by using the sympathetic nerve information in addition to the RR interval variation coefficient, the stress state can be detected with higher accuracy and can be visually displayed.
In addition, it is possible to detect a stress state for each life time zone, and it is possible to detect a stress state that more reflects the life activity of the subject.

  In the present invention, (2) the biological information in a state where the subject is artificially stressed over the coefficient calculation period is input to the biological information input unit, and the state detection unit includes: The stress state of the subject may be detected by comparing the RR interval variation coefficient during a coefficient calculation period with a first stress state determination reference value. In this way, for example, the stress state in the life activity of the subject is approximately reproduced by artificially applying stress in a relatively short time such as 2 minutes, and the stress state is detected in such a state. By detecting the stress state using the obtained biological information, the stress state can be detected more accurately in a short time.

  In the present invention, (3) the state detection unit compares the maximum value of the plurality of RR interval variation coefficients with a first stress state determination reference value in a state determination period including the plurality of coefficient calculation periods. The stress state of the examiner may be detected. In this way, for example, by detecting a stress state using biological information detected over a relatively long time such as one day, the living activity of the subject can be more accurately detected in such biological information. , The stress state can be detected more accurately.

  In the present invention, (4) the subject's stress self-evaluation value is further input to the biological information input unit, and the state detection unit sets a plurality of the stress self-evaluation values in a state determination period including a plurality of the coefficient calculation periods. The stress state of the subject is detected by comparing a maximum value of the RR interval variation coefficient with a first stress state determination reference value and comparing the stress self-evaluation value with a second stress state determination reference value. You may. With this configuration, the stress state can be detected with higher accuracy by using the stress self-evaluation value in addition to the maximum value of the RR interval variation coefficient.

  In the present invention, (5) the display unit may display a stress diagnostic plot in which points having coordinates of the stress self-evaluation value and the maximum value of the RR interval variation coefficient are plotted on a two-dimensional plane. Good. By doing so, the stress state can be visually grasped.

  In the present invention, (6) the display unit passes the first stress state determination reference value on a coordinate axis of a maximum value of the RR interval variation coefficient and is parallel to the coordinate axis of the stress self-evaluation value; And at least one of a second reference line passing through the second stress state determination reference value on the coordinate axis of the stress self-evaluation value and parallel to the coordinate axis of the maximum value of the RR interval variation coefficient is superimposed on the stress diagnosis plot. May be displayed. By doing so, a point on the plot can be visually compared with at least one of the first reference line and the second reference line, and the stress state can be grasped more visually. In particular, by displaying both the first reference line and the second reference line, the stress state can be more visually displayed depending on where the plurality of quadrants defined by the first reference line and the second reference line are included. I can understand.

  In the present invention, (7) the first stress state determination reference value is preferably 0.04. Since the first stress state determination reference value is obtained from the RR interval variation coefficient detected in a plurality of subjects whose stress states are known, the stress state can be detected with higher accuracy.

  In the present invention, (8) the state detection unit may detect the diabetic state of the subject by comparing the RR interval variation coefficient in the coefficient calculation period with a diabetic state determination reference value. In this way, the diabetic state can be detected in addition to the stress state.

  In the present invention, (9) the state detection unit may also detect the diabetic state of the subject by comparing a maximum value of the plurality of RR interval variation coefficients during the state determination period with a diabetic state determination reference value. It may be. For example, by detecting a diabetic state using biological information detected over a relatively long time such as one day, such biological information more accurately reflects the life activity of the subject, The diabetic state can be detected with higher accuracy.

  In the present invention, it is preferable that (10) the diabetic state determination reference value is 0.022. Since the diabetic condition determination reference value is obtained from the RR interval variation coefficients detected in a plurality of subjects whose diabetic condition is known, the diabetic condition can be detected with higher accuracy.

In the present invention, (11) in the autonomic nervous activity plot diagram, the display section may display the point where the RR interval variation coefficient is equal to or less than a threshold value and the point where the RR interval variation coefficient is greater than the threshold value. May be displayed in different colors.
Further, the display unit displays, in the autonomic nervous activity plot diagram, the point where the RR interval variation coefficient is equal to or less than a threshold value in a light color, and displays the point where the RR interval variation coefficient is greater than the threshold value. It may be displayed in a dark color.
Preferably, the threshold value is 0.05.

  In the present invention, (12) the display unit may display the plurality of autonomic nervous activity plot diagrams in each of the plurality of plot periods corresponding to the plurality of living time zones of the subject. By doing so, it is possible to detect a stress state for each life time zone, and it is possible to detect a stress state that more reflects the life activity of the subject.

  In order to achieve the above object, another embodiment of the present invention provides (13) a biological information input unit into which biological information of a subject detected in time series is input, and an input to the biological information input unit. A state detection unit that detects the stress state of the subject based on the biological information that has been obtained, and a display unit that displays the stress state of the subject detected by the state detection unit, The biological information input unit receives the biological information including heart movement information according to the movement of the subject's heart, and the state detection unit calculates a contraction interval of the subject's heart from the heart movement information. An RR interval is calculated, and using the RR interval in the coefficient calculation period, sympathetic nerve information indicating the activity state of the sympathetic nerve of the subject and parasympathetic nerve information indicating the activity state of the parasympathetic nerve are calculated. A professional including a plurality of coefficient calculation periods Displaying an autonomic nervous balance plot in which a plurality of points having coordinates based on the parasympathetic nerve information and the sympathetic nerve information calculated corresponding to each of the coefficient calculation periods in a period are plotted on a two-dimensional plane. It is a psychosomatic condition diagnosis support device characterized by the following.

  According to the present invention, by using the sympathetic nerve information and the parasympathetic nerve information, it is possible to detect the stress state including the activity state of the entire autonomic nerve, so that the stress state of the subject can be more accurately detected. Can be.

  In the present invention, (14) the state detection unit may detect the stress state of the subject using an area of a plot shape including a plurality of points of the autonomic nerve balance plot. In this way, a stress state can be detected from the activity state of the entire autonomic nerve.

  In the present invention, (15) the state detection unit may detect the stress state of the subject using a size in a coordinate axis direction of a plot shape including a plurality of points of the autonomic nerve balance plot diagram. Good. In this manner, the stress state can be detected from the individual activity states of the sympathetic nerve or the parasympathetic nerve and the balance between these activity states.

  In the present invention, (16) the state detecting unit detects the stress state of the subject using a distance between a coordinate axis and a plot shape including a plurality of points of the autonomic nerve balance plot. Is also good. In this way, the stress state can be detected from the offset state of the activity states of the sympathetic nerve and the parasympathetic nerve.

  In the present invention, (17) the state detection unit may detect the stress state of the subject using smoothness of a periphery of a plot shape including a plurality of points of the autonomic nervous balance plot chart. . By doing so, it is possible to detect the stress state from the degree of disturbance of the autonomic nervous system.

  In the present invention, (18) the display unit may display the plurality of autonomic nervous balance plots in each of the plurality of plot periods corresponding to the plurality of living time zones of the subject. By doing so, it is possible to detect a stress state for each life time zone, and it is possible to detect a stress state that more reflects the life activity of the subject.

  According to the present invention, (19) the plurality of living time zones may be a staying time, a pre-working time, a working time, and a post-working time. By doing so, it is possible to detect the respective stress states of living activities at home and living activities at work.

  In order to achieve the above object, another embodiment of the present invention provides (20) a biological information input unit into which biological information of a subject detected in time series is input, and an input to the biological information input unit. A state detection unit that detects the stress state of the subject based on the biological information that has been obtained, and a display unit that displays the stress state of the subject detected by the state detection unit, The biological information input unit receives the biological information including heart movement information according to the movement of the subject's heart, and the state detection unit calculates a contraction interval of the subject's heart from the heart movement information. Calculating an RR interval, calculating sympathetic nerve information indicating an activity state of the sympathetic nerve of the subject using the RR interval in the activity state detection period, and a state determination period including a plurality of the activity state detection periods The respective active state detection periods in A psychosomatic state diagnosis support apparatus characterized by detecting a stress condition using the maximum value and the third quartile of the plurality of the sympathetic information calculated in response to.

  ADVANTAGE OF THE INVENTION According to this invention, stress is calculated | required using the maximum value of several sympathetic nerve information calculated corresponding to each active state detection period in the state determination period including several active state detection periods, and a 3rd quartile. Detect state. This makes it possible to more accurately detect the stress state of the subject.

  In the present invention, (21) the state detection unit determines that the subject is under stress when the maximum value of the plurality of sympathetic nerve information is 25 or more and the third quartile is 5 or more. It is preferable to determine. By doing so, the stress state can be detected more effectively.

  Another aspect of the present invention includes (22) the above-mentioned physical and mental condition diagnosis support device and a biological information detecting device, wherein the biological information detecting device detects biological information including the heart movement information of the subject. A portable biological information detection device main body that can be attached to the body of the subject, and the biological information detected by the biological information detection device main body is input to the biological information input unit. The biological information management system is characterized by the following.

  According to the present invention, since the biological information detected by the main body of the portable biological information detection device that can be worn on the body of the subject is used, the biological information can be detected in daily living activities. It is possible to detect a stress state in daily life activities by using various biological information.

  According to the present invention, a stress state is detected using an RR interval variation coefficient calculated from an RR interval of a subject, sympathetic nerve information indicating an activity state of a sympathetic nerve or parasympathetic nerve information indicating an activity state of a parasympathetic nerve. Therefore, the stress state of the subject can be detected with higher accuracy.

It is a block diagram showing the example of composition of the living body information management system concerning a 1st embodiment of the present invention. FIG. 2 is a block diagram illustrating a configuration example of the biological information detection device in FIG. 1. FIG. 3 is a block diagram illustrating a configuration example of a control unit included in the biological information detection device main body of FIG. 2. 4 is a flowchart illustrating an operation example of a control unit in FIG. 3. It is an image figure showing an example of an electrocardiogram waveform. FIG. 7 is an image diagram showing an example of a basic electrocardiographic waveform and an abnormal waveform of one heartbeat. It is a graph which shows the example of a time change of the fluctuation amount of RR interval. FIG. 2 is a diagram showing a display example 1 (stress state detection result) on a display unit of the mental and physical condition diagnosis support device in FIG. 1. FIG. 2 is a diagram illustrating a display example 2 (stress diagnosis plot diagram) on a display unit of the mental and physical condition diagnosis support device in FIG. 1. FIG. 3 is a diagram showing a display example 3A (autonomous nerve activity plot diagram No. 1) on the display unit of the psychosomatic state diagnosis support device in FIG. FIG. 3 is a diagram showing a display example 3B (autonomous nerve activity plot diagram No. 2) on the display unit of the psychosomatic state diagnosis support device in FIG. 1. FIG. 3 is a diagram showing a display example 3C (autonomous nerve activity plot diagram No. 3) on the display unit of the psychosomatic state diagnosis support device in FIG. FIG. 4 is a diagram showing a display example 4A (autonomous nerve balance plot diagram No. 1) on the display unit of the psychosomatic state diagnosis support device in FIG. 1. FIG. 4 is a diagram illustrating a display example 4B (autonomous nerve balance plot diagram, part 2—normal person) on the display unit of the mental and physical condition diagnosis support device in FIG. 1. FIG. 4 is a diagram showing a display example 4C (autonomous nerve balance plot diagram, 3rd-middle person) on the display unit of the mental and physical condition diagnosis support device in FIG. 1. FIG. 4 is a diagram illustrating a display example 4D (autonomous nerve balance plot diagram, part 4 abnormal person) of the display unit of the mental and physical condition diagnosis support device in FIG. 1. FIG. 4 is a diagram showing a display example 4E (autonomous nerve balance plot diagram, area of 5-plot shape) by the display unit of the mental and physical condition diagnosis support device in FIG. 1. FIG. 6 is a diagram illustrating a display example 4F (autonomous nerve balance plot diagram, 6-size of the plot shape in the coordinate axis direction) on the display unit of the psychosomatic state diagnosis support device in FIG. 1. FIG. 6 is a diagram showing a display example 4G (autonomous nerve balance plot diagram 7-distance between plot shape and coordinate axis) by the display unit of the psychosomatic state diagnosis support device in FIG. 1. FIG. 6 is a diagram illustrating a display example 4H (autonomous nerve balance plot diagram, 8-smoothness of the periphery of the plot shape) by the display unit of the psychosomatic state diagnosis support device in FIG. 1. It is the figure which plotted the maximum value and the 3rd quartile of the sympathetic nerve information at work among a plurality of subjects. It is the figure which plotted the minimum value and the 1st quartile of the sympathetic nerve information of several test subjects at bedtime. It is a block diagram showing the example of composition of the living body information management system concerning a 2nd embodiment of the present invention. In the present invention, it is an image figure showing an example which attaches a living body information detecting device main part to a plurality of places of a subject's body.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

(1st Embodiment)
Hereinafter, a biological information management system according to the first embodiment of the present invention will be described.

  The biological information management system is a system that manages a stress state of a subject, and includes a biological information detection device 1 and a mental and physical condition diagnosis support device 30 as shown in FIG.

  First, the configuration and operation of the biological information detection device 1 will be described.

  FIG. 2 is a block diagram illustrating a configuration example of the biological information detection device 1.

  The biological information detecting device 1 has a portable biological information detecting device main body 10 and a mounting table 20. The biological information detecting device main body 10 is mounted on the body of the subject, and is preferably mounted on the chest. The biological information detecting device main body 10 has a biological information detecting unit 100, and the biological information detecting unit 100 has a body temperature sensor 110, an acceleration sensor 120, and an electrocardiographic signal sensor 130.

  The body temperature sensor 110 measures the skin temperature of the subject and outputs body temperature data T at predetermined intervals. The acceleration sensor 120 detects a three-dimensional movement of the subject, and outputs acceleration data α = (αx, αy, αz) in the X, Y, and Z directions at predetermined intervals. Here, αx is acceleration in the X direction, αy is acceleration in the Y direction, and αz is acceleration in the Z direction.

  The electrocardiographic signal sensor 130 has two electrodes, and in order to detect a subject's electrocardiographic signal, each electrode is brought into contact with the subject's body to measure a potential (potential signal), The difference between the two measured potentials is output as electrocardiogram signal data E at predetermined intervals. The number of electrodes may be three or more. In this case, the calculated potential difference is plural. Since the measured potential signal is weak and is amplified by an amplifier or the like inside the electrocardiographic signal sensor 130, it is easily affected by noise. Therefore, in order to reduce the influence of noise and improve the S / N ratio, electrodes, amplifiers, and the like are arranged close to each other. The wiring length between the electrode and the first-stage amplifier is preferably 2 cm or less. The electrocardiogram signal data E is a potential signal corresponding to the movement of the subject's heart, that is, corresponds to heart movement information. Instead of the electrocardiogram signal data E, for example, pulse data detected by a pulse sensor using near infrared rays may be used. In this case, the pulse data corresponds to the heart movement information.

  The interval at which the body temperature data T is output, the interval at which the acceleration data α is output, and the interval at which the electrocardiogram signal data E are output may be the same value or different values. For example, since the skin temperature usually has a small fluctuation, the interval at which the body temperature data T is output may be set longer. As a result, the amount of data to be obtained can be reduced. Further, the interval at which the body temperature data T is output, the interval at which the acceleration data α is output, and the interval at which the electrocardiogram signal data E is output may be changed instead of a fixed value. When it is assumed that the value fluctuates immediately after exercise or the like, by making adjustments such as shortening the output interval, it is possible to obtain appropriate biological information according to the physical condition.

  The body temperature data T, the acceleration data α, and the electrocardiogram signal data E (collectively referred to as biological information data BD) output from the biological information detecting unit 100 are input to the control unit 140. The control unit 140 stores the input body temperature data T, acceleration data α, and electrocardiogram signal data E in an area in the memory 150 set in advance for each data. Note that the method of storing the biological information data BD in the memory 150 is not limited to the method of storing the data in an area set in advance for each data. Instead of setting an area, an identifier for distinguishing each data is stored in the body temperature data T. , Acceleration data α and electrocardiogram signal data E, and storing them together with their identifiers in the memory 150.

  When the setting is such that the biological information is transmitted to the outside when detecting the biological information (hereinafter, referred to as a simultaneous transmission setting), the control unit 140 outputs the biological information data BD to the transmitting unit 160. The transmitting unit 160 converts the input biological information data BD into a format that can be received by the mental and physical condition diagnosis support device 30, and wirelessly transmits the format as the biological information signal BS1. As a wireless transmission method, a Wi-Fi method, a Bluetooth (registered trademark) method, or the like is used. Note that a configuration in which the biological information is always transmitted to the outside when the biological information detecting device main body 10 detects the biological information may be adopted. In this configuration, the memory 150 may be omitted.

  Note that the time during which the biological information detection unit 100 measures the biological information may be changeable for each of the body temperature sensor 110, the acceleration sensor 120, and the electrocardiogram signal sensor 130. This makes it possible to flexibly take measures such as shortening the measurement time of biological information requiring a large amount of power for detection, and increasing the measurement time when the physical condition is poor.

  Here, the operation at the time of charging the biological information detecting device main body 10 will be described.

  As shown in FIG. 2, the biological information detecting device main body 10 has a charge input unit 170, and the mounting table 20 has a charge output unit 200. When the biological information detecting device main body 10 is placed on the mounting table 20 and the charging input unit 170 and the charging output unit 200 are brought close to each other, the power required by the biological information detecting device main body 10 uses a method using electromagnetic induction (electromagnetic induction). Method). That is, the charge input unit 170 and the charge output unit 200 each have a coil, and when a current flows through the coil of the charge output unit 200, a magnetic flux is generated, and the magnetic flux is induced by the magnetic flux. Electric current flows and charging is performed. Note that, as the non-contact charging method, a resonance method or the like may be used instead of the electromagnetic induction method. As a power source to be charged in the biological information detecting device main body 10, a secondary battery such as a nickel cadmium battery or a lithium ion battery, a super capacitor (electric double layer capacitor), or the like is used.

  The mounting table 20 also has a communication unit 210 that receives a biological information signal wirelessly transmitted from the transmitting unit 160 of the biological information detection device main body 10 and wirelessly transmits the biological information signal to the outside, and the biological information detection device main body 10 is charged. At this time, a biological information signal is received from the transmitting unit 160 and wirelessly transmitted to the outside.

  That is, when charging is started by electromagnetic induction, the charging input unit 170 outputs a charging start signal CS to the control unit 140, and the control unit 140 receives the biological information stored in the memory 150 when the charging start signal CS is input. The data BD is output to the transmission unit 160. The transmitting unit 160 converts the input biometric information data BD into a format that can be received by the communication unit 210, and wirelessly transmits the format as the biometric information signal BS2. The communication unit 210 receives the biological information signal BS2, converts it into a format that can be received by the mental and physical condition diagnosis support device 30, and wirelessly transmits the received information as the biological information signal BS3. At this time, as a wireless transmission method used by the transmission unit 160 and the communication unit 210, a WiFi (Wi-Fi) method, a Bluetooth (registered trademark) method, or the like is used to convert the signal into the biological information signal BS2. May be the same as or different from the method used to convert the information into the biological information signals BS1 and BS3. However, when the biological information signal BS2 is wirelessly transmitted, the transmitting unit 160 and the communication unit 210 are close to each other, so that the power consumption can be suppressed by using the short-range communication method.

  As described above, the battery is charged by the non-contact charging method, and the transmission and reception of the biological information at the time of charging is performed wirelessly, so that an input / output terminal for external connection becomes unnecessary, and the waterproof property can be improved.

  Note that the communication unit 210 of the mounting table 20 may transmit the biological information signal BS3 to the outside by wired communication. Further, a configuration in which the biological information detecting device main body 10 includes a charging terminal for supplying power to the charging input unit 170 may be employed. For example, a USB connector may be used for the charging terminal, and a USB cable may be used. It may be rechargeable. In this case, the mounting table 20 is omitted. The charging mechanism may be omitted by operating the biological information detecting device main body 10 with a primary battery (a coin-type battery or the like).

  In the present embodiment, the transmission unit 160 of the biological information detecting device main body 10, the communication unit 210 of the mounting table 20, and the biological information input unit 300 of the sleep state detecting device 30 described later transmit and receive a biological information signal by wireless communication with each other. However, the present invention is not limited to this. For example, the biological information stored in the memory 150 using the USB interface may be transmitted and received between the transmitting unit 160 of the biological information detecting device body 10 and the biological information inputting unit 300 of the sleep state detecting device 30 by wired communication. The communication method (wired / wireless, communication protocol, etc.) between the respective functional units is arbitrary as long as the object of the present invention is not violated.

  FIG. 3 is a block diagram illustrating a configuration example of the control unit 140, and FIG. 4 is a flowchart illustrating an operation example of the control unit 140.

  As shown in FIG. 3, the control unit 140 includes a data processing unit 141, a mode setting unit 142, a switching unit 143, and a data reading unit 144. The data processing unit 141 reads the biological information data BD (body temperature data T, acceleration data α, and electrocardiographic signal data E) output from the biological information detecting unit 100, and outputs the read data to the memory 150 and the switching unit 143. The mode setting unit 142 inputs a charging start signal CS output from the charging input unit 170 when charging of the biological information detecting device main body 10 is started. The mode setting unit 142 determines the output mode of the biological information data BD based on the presence / absence of the input of the charging start signal CS and the ON / OFF information of the simultaneous transmission setting, and outputs the output mode as the mode signal MS. That is, when the charge start signal CS is input, the memory data output mode is set. When the simultaneous transmission setting is ON without the input of the charge start signal CS, the mode is set to the “simultaneous transmission mode”. When the simultaneous transmission setting is OFF, the mode is set to “no output mode”. The mode signal MS is input to the switching unit 143. The data readout unit 144 also receives the charge start signal CS, and upon receiving the charge start signal CS, reads out the biological information data BD stored in the memory 150 and outputs it to the switching unit 143.

  An operation example of the control unit 140 will be described with reference to the flowchart of FIG.

  The data processing unit 141 reads the biological information data BD output from the biological information detecting unit 100 (Step S1). The read biological information data BD is stored in the memory 150 (step S2), and is simultaneously input to the contact 143a of the switching unit 143.

  If the mode signal MS output from the mode setting unit 142 is the “simultaneous transmission mode”, the switching unit 143 connects to the contact 143a, and the biological information data BD is output to the transmission unit 160 (Step S3). If the mode signal MS is in the “non-output mode”, the switching unit 143 is not connected to either of the contacts, and the biological information data BD is not output. If the mode signal MS is “memory data output mode”, the switching unit 143 connects to the contact 143b. At this time, when the charging start signal CS is input to the data reading unit 144, the data reading unit 144 reads the biological information data BD stored in the memory 150 (step S4) and outputs the biological information data BD to the contact 143b of the switching unit 143. Then, the biological information data BD stored in the memory 150 is output to the transmitting unit 160 (Step S5).

  It is preferable that the biological information detecting device main body 10 can detect biological information (biological information data BD) for at least 24 hours, for example, in order to detect biological information that more accurately reflects the life activity of the subject.

  Next, the configuration and operation of the mental and physical condition diagnosis support device 30 will be described.

  As shown in FIG. 1, the mental and physical condition diagnosis support device 30 includes a biological information input unit 300, a memory 310, a state detection unit 320, and a display unit 330.

  The biological information input unit 300 receives the biological information signal BS1 transmitted from the transmitting unit 160 of the biological information detecting device main body 10 and the biological information signal BS3 transmitted from the communication unit 210 of the mounting table 20, and outputs the biological information data BD The format is restored and stored in the memory 310. As for the method of storing the data in the memory 310, similarly to the method of storing the data in the memory 150, the data is also distinguished by a method of storing the temperature data T, the acceleration data α, and the electrocardiogram signal data E in a preset area. A method of adding an identifier to each data and storing the data together with the identifier may be used. When the biological information detecting device main body 10 adopts a configuration in which the biological information is always transmitted to the outside when detecting the biological information, the biological information input unit 300 is transmitted from the transmitting unit 160 of the biological information detecting device main body 10. Only the biological information signal BS1 received is obtained.

  The biological information input unit 300 receives a stress self-evaluation value transmitted from an information terminal such as a smartphone, a tablet terminal, or a personal computer. The stress self-evaluation value is, for example, a numerical value indicating the self stress state calculated by the subject answering the questionnaire. As an example, the information terminal displays, as an inquiry sheet, questions such as "I haven't been feeling well recently" or "I have no clear cause but I am anxious". The subject selects the answer to each question item from “well applicable”, “appreciately applicable”, “somewhat applicable”, and “not applicable” and inputs the information to the information terminal. The information terminal collects the scores set in these answers, calculates a stress self-evaluation value, and transmits the stress self-evaluation value to the biological information input unit 300 by, for example, wireless communication. The medical questionnaire may be a form in which the questionnaire is described on paper, or a configuration may be adopted in which the answers are totaled manually, the totalized points are input to the information terminal, and transmitted to the biological information input unit 300. .

  When the detection of the subject's biometric information by the biometric information detection device 1 is completed and all the obtained biometric information data BD are stored in the memory 310, the state detection unit 320 outputs the biometric information data BD stored in the memory 310. Are read, and the analysis data AS relating to the stress state of the subject is calculated using them, that is, the stress state of the subject is detected. The information calculated as the analysis data AS includes abnormal waveform information, heart rate, instantaneous heart rate, RR interval standard deviation, RR interval average value, RR interval variation coefficient (also referred to as “autonomic nervous activity”), and sympathy. Nervous information, parasympathetic nerve information, posture information, entry time, exit time, and body temperature.

  Hereinafter, each information will be described.

  The electrocardiographic signal data E in the biological information data BD read from the memory 310 forms an electrocardiographic waveform as shown in FIG. With respect to this electrocardiographic waveform, the basic waveform for one beat of the heartbeat is a waveform as shown in FIG. 6A, and the peaks and valleys of the waveform are indicated by P as shown in FIG. They are called waves, Q waves, R waves, S waves and T waves. When a portion having a shape greatly different from the basic waveform is found in the electrocardiogram waveform formed from the electrocardiogram signal data E, the determination result indicating that there is an abnormal waveform is provided together with information (time and the like) of the found portion. Abnormal waveform information. If there is no location that is significantly different from the basic waveform, the result of determination that there is no abnormal waveform is used as abnormal waveform information. As a waveform greatly different from the basic waveform, for example, as shown in FIG. 6B, a T-wave overlaps with an R-wave and disappears. Such a waveform can be found by extracting a P wave, a Q wave, an R wave, an S wave, and a T wave from an electrocardiographic waveform and detecting the presence or absence of a T wave.

  An R wave is extracted from an electrocardiographic waveform, and the number of R waves extracted every minute is used as a heart rate, and the interval (RR interval) between two adjacent R waves is calculated, and the reciprocal of the RR interval is calculated. The instantaneous heart rate. When the movement of the autonomic nervous system instantaneously changes, the instantaneous heart rate changes immediately. Therefore, by calculating the instantaneous heart rate, the movement of the autonomic nerve can be analyzed. The heart rate and the instantaneous heart rate are time-series information (information in which data calculated at regular time intervals are arranged).

  The standard deviation of the RR interval and the average value of the RR interval are calculated every predetermined coefficient calculation period (for example, 2 minutes), and the standard deviation of the RR interval is divided by the average value of the RR interval to obtain an RR interval variation coefficient (Coefficient of Variation). of RR-interval: CVRR). The degree of health of autonomic nervous activity can be evaluated by using the RR interval variation coefficient (CVRR), but simply using this coefficient multiplied the accuracy. This is because the coefficient is calculated using the biological information measured in a short time without limiting the measurement state of the biological information. The present inventors have repeatedly performed a long time measurement on a large number of subjects, and the RR interval variation coefficient also changes every moment. Even if the median in a certain period is used as a parameter, Finding that it is reduced by drowsiness, etc., and further dividing the whole awakening time into multiple areas, finding the median of each, and determining the maximum value as a parameter, it can be determined more accurately than the conventional medical questionnaire I found it. The present inventors further perform a large number of measurements and perform a two-dimensional plot with the score of the determination from the medical questionnaire, so that the threshold value for determining whether the autonomic nervous activity is healthy or not is 0.04. Was found.

  The RR interval variation coefficient (CVRR) has been used as a means for judging a diabetic state and as a screening means for other autonomic nerve-related diseases, in addition to the degree of health of the autonomic nervous activity. This coefficient is calculated using biological information measured in a short time without limiting the measurement situation, and lacks accuracy for the reasons described above. More accurate screening can be achieved using our technique.

  The RR interval is used to calculate the sympathetic nerve information and the parasympathetic nerve information. Normally, the RR interval fluctuates periodically, and the pattern of this fluctuation involves a function related to the function of autonomic nerves (Sympathetic Nervous System: SNS, parasympathetic nerve (Para-SNS: PSNS)). Since there is knowledge, information on the autonomic nerve can be obtained by analyzing the fluctuation of the RR interval. If the difference ΔRR of the RR interval is plotted with time as the horizontal axis, the waveform becomes, for example, a waveform as shown in FIG. 7 (a time-varying waveform of the fluctuation amount of the RR interval). By calculating the frequency components of the above, sympathetic nerve information and parasympathetic nerve information, which are information on the autonomic nerve, are calculated. The sympathetic nerve information is an index indicating the activity state of the subject's sympathetic nerve, and the parasympathetic nerve information is an index indicating the activity state of the parasympathetic nerve of the subject. For example, a low frequency component LF of 0.04 Hz or more and less than 0.15 Hz is defined as a low frequency component LF, and a frequency component of 0.15 Hz or more and less than 0.4 Hz is defined as a high frequency component HF. ), The low-frequency component LF is used as the parasympathetic nerve information, and the ratio of the low-frequency component LF to the high-frequency component HF (LF / HF) is used as the sympathetic nerve information. This calculation is based on the fact that it is generally said that the sympathetic nerve promotes the heart beat and the parasympathetic nerve suppresses the heart beat. The sympathetic nerve information and the parasympathetic nerve information are time-series information.

  The posture information includes acceleration data α = (αx, αy, αz) in the biological information data BD read from the memory 310 and velocity data V = (Vx, Vy, Vz) calculated by integrating the acceleration data α. ). Here, Vx is the speed in the X direction, Vy is the speed in the Y direction, and Vz is the speed in the Z direction, and is calculated by integrating αx, αy, and αz, respectively.

  The posture information indicates that the subject's posture is standing (standing, sitting), supine (facing), prone (prone), right lying (right side down) and left lying down (left side down) Is determined based on the speed data V and the acceleration data α. That is, when the height direction of the body in the lying position (sleeping state) is the X direction, and the height direction of the body in the standing position (standing state) is the Z direction, the acceleration in the Z direction increases and A change from standing to supine or from supine to standing is detected by the occurrence of speed, and in the supine position, the presence of an increase in acceleration in the Y and Z directions and the speed generation time indicate the supine, prone, or right recumbency. Or, a change to the left lateral position is detected. The posture information is time-series information.

  The entry time is a time at which it is detected from the posture information that a change from the standing position to the lying position (sleeping state) has been made. The leaving time is a time at which a change from the standing position to the lying position (sleeping state) is detected based on the posture information. The period during which the subject is leaving the bed is a period from the time of leaving the bed to the time of entering the next bed.

  In the present embodiment, since the posture of the subject is automatically detected using the acceleration data α detected by the acceleration sensor 120, each time is detected using one clock built in the biological information detecting device main body 10. can do. Therefore, for example, the elapsed time between the times can be detected more accurately than in a configuration in which each time is detected by a plurality of clocks, such as when the bedroom turn-off time is used as the entry time.

  As for the body temperature, the body temperature data T in the biological information data BD read from the memory 310 is used as it is.

  In addition, as the information calculated as the analysis data AS, information other than the above may be added even to a part of the above as long as the object of the present invention is not violated. May be calculated.

  The calculated analysis data AS is output to the display unit 330. The display unit 330 displays the input analysis data AS on a display or the like in various modes.

  FIG. 8 shows a display example 1 by the display unit 330. FIG. 8 is an example of a diagram displaying a stress state detection result.

  In this display example 1, the subject is artificially stressed over the coefficient calculation period (two minutes), the RR interval variation coefficient in the coefficient calculation period is calculated, and the RR interval variation coefficient is determined as the stress state determination. 3 shows a result of comparison with a first stress state determination reference value used for the determination of a diabetic state and a first stress state determination reference value used for determining a diabetic state.

  Specifically, the subject wears the biological information detecting device main body 10, shows a seven-digit number to the subject for 5 seconds, and inputs the same to the personal computer in the reverse order in the next 15 seconds or writes it on paper. The operation is repeated over the coefficient calculation period. Then, the biological information measured during the coefficient calculation period is input to the mental and physical condition diagnosis support device to calculate an RR interval variation coefficient, and is compared with the first stress state determination reference value and the diabetes state determination reference value. In the present embodiment, the first stress state determination reference value is 0.04, and the diabetes state determination reference value is 0.022. These values are obtained from RR interval variation coefficients detected in a plurality of subjects whose stress states are known. These values are preferable as the respective criterion values, but other values may be used.

  As shown in FIGS. 8A to 8C, the stress state detection results are displayed beside the RR interval variation coefficient. Specifically, when the RR interval variation coefficient (autonomic nervous activity) is larger than 0.04, a detection result indicating "no stress" is displayed (FIG. 8A), and the detection result is larger than 0.022 and 0.1. If it is less than 04, the detection result of "strong stress state" is displayed (FIG. 8B), and if it is less than 0.022, the detection result of "diabetic state" is displayed (FIG. 8C )).

  Alternatively, for example, the RR interval variation coefficient (autonomic nervous activity degree) is calculated for each coefficient calculation period (for example, 2 minutes) over the state determination period, with 24 hours when the subject spends normal living activities as the state determination period. And comparing the maximum value of the RR interval variation coefficient in each of a plurality of life time zones of the subject (to be described later, the time spent in bed, the time before going to work, the time spent at work and the time after leaving work) with the first stress state determination reference value. By doing so, the stress state may be detected for each life time zone. The state determination period need not be 24 hours, and may be, for example, a period during which the user is not sleeping (a period during which the user leaves the bed), and may be arbitrarily set according to the subject. Alternatively, as the maximum value of the RR interval variation coefficient, the median value of the RR interval variation coefficient in each of a plurality of living time zones is calculated, and the maximum value of the plurality of median values is adopted as the first value. It may be configured to compare with a stress state determination reference value.

  FIG. 9 shows a display example 2 of the display unit 330. FIG. 9 is an example of a stress diagnosis plot.

  The stress diagnosis plot diagram uses the subject's stress self-evaluation value (questionnaire score) and the maximum value of the RR interval variation coefficient during a state determination period (for example, 24 hours) including a plurality of coefficient calculation periods (for example, 2 minutes). Then, points having coordinates of the subject's stress self-evaluation value (horizontal axis) and the maximum value of the RR interval variation coefficient (vertical axis) are plotted on a two-dimensional plane. In FIG. 9, biological information and stress self-evaluation values of a plurality of subjects different from each other are input to the psychosomatic condition diagnosis support device 30, and a plurality of points corresponding to each subject are plotted. is there. The higher the stress self-evaluation value, the stronger the stress state.

  In the stress diagnosis plot shown in FIG. 9, a first reference line indicating a first stress state determination reference value used for determining the maximum value of the RR interval variation coefficient, and a second stress state determination reference used for determining the stress self-evaluation value. A second reference line indicating the value is drawn. The first reference line passes the first stress state determination reference value on the vertical axis and is parallel to the horizontal axis, and the second reference line passes the second stress state determination reference value on the horizontal axis and corresponds to the vertical axis. Parallel. It is preferable that at least one of the first reference line and the second reference line is displayed, and it is more preferable that both are displayed.

  The stress state can be more visually determined depending on where in the plurality of quadrants (I) to (IV) divided by the first reference line and the second reference line. When the plotted point is included in quadrant (I), it is determined that there is no stress because the RR interval variation coefficient is high and the stress self-evaluation value is low. When the plotted point is included in the quadrant (IV), the RR interval variation coefficient is low and the stress self-evaluation value is high, so that it is determined that some disease due to stress is occurring. If it is included in the quadrant (II) or the quadrant (III), it is determined that there is a possibility that modulation due to stress has occurred.

  In the present embodiment, the first stress state determination reference value is 0.04, and the second stress state determination reference value is 30. These values are found from RR interval variation coefficients and stress self-evaluation values detected in a plurality of subjects whose stress states are known. For the RR interval variation coefficient, specifically, the present inventors perform a large number of measurements and perform a two-dimensional plot with the score of the judgment from the questionnaire to determine whether the autonomic nervous activity is healthy or not. It has been found that it is appropriate that the first stress state determination reference value, which is the threshold value of the RR interval variation coefficient to be determined, is 0.04.

  Display examples 3A to 3C by the display unit 330 are shown in FIGS. 10 to 12 are examples of autonomic nerve activity plots (CVRR-SNS-Plot).

  The display unit 330 two-dimensionally displays a plurality of points having coordinates of the RR interval variation coefficient and the sympathetic nerve information calculated corresponding to each coefficient calculation period in a plot period including a plurality of coefficient calculation periods (for example, two minutes). An autonomic nerve activity plot plotted on a plane is displayed. Specifically, the display unit 330 displays a plurality of plot periods in each of a plurality of plot periods corresponding to a plurality of living time zones of the subject (to be described later, a resident time, a pre-work time, a resident time, and a post-work time). Display the autonomic nervous activity plot. 10 to 12 show autonomic nervous activity plot diagrams for each of a plurality of living time zones of the subject.

  Specifically, the life time of the subject is obtained by dividing 24 hours into four periods, that is, the time spent in the bed and the time before going to work, the time spent at work, and the time after leaving work as the period during which the patient leaves the bed. . In the present embodiment, the time in bed, the time before going to work, the time at work, and the time after leaving work are automatically grasped from the posture information described above. For example, the time in bed is from 23:00 to 6:00, Pre-fixed time may be set as 6:00 to 9:00, time at work from 9:00 to 18:00, time after leaving the work at 18:00 to 23:00, and the like.

  The inventors have found the following points. (1) When sympathetic nervous activity is large, people tend to think that they are under stress. Even in a positive case, sympathetic nervous activity increases. (2) For example, a person in a responsible position, such as a hospital director, a university professor, a kindergarten chief, or a nursery school facility manager, usually has large sympathetic nervous activity. Few people become unhealthy in autonomic nervous activity, and (3) autonomic nervous activity frequently changes as well as the magnitude of sympathetic nervous activity. The inventors have found that the relationship between the degree of autonomic nervous activity and sympathetic nervous activity is important from these points of interest, and came up with this autonomic nervous activity plot. In this plot, when the degree of autonomic nervous activity is high, the sympathetic nervous activity is high and the patient is in a positive mental state, and active stress is considered to be applied. Therefore, when the sympathetic nervous activity is large in this case, it is considered that passive stress is applied. It is considered that the latter, when there is a lot of passive stress, results in a mentally unhealthy state.

  The present inventors approached the reason that a person with a large daily stress does not necessarily impair the health of autonomic nervous activity, and a two-dimensional plot of CVRR and an index of sympathetic nervous activity for each coefficient calculation period (epoch). That is, the autonomic nerve activity plot was invented. People with unhealthy autonomic nervous activity often have high sympathetic nervous activity in the region where the RR interval variation coefficient is small, and those who remain healthy even when stress is large have a high sympathetic nervous activity in the region where the RR interval variation coefficient is large. Is increased, and it is found that it is appropriate to set the threshold value of the RR interval variation coefficient to 0.05 in this case.

  In the autonomic nervous activity plot, the autonomic nervous information is displayed in a light gray point when it is 0.05 or less in the passive stress area, and is displayed in a dark gray point when it is more than 0.05 in the active stress area. it's shown. The black dots are invalid data and are not used for detecting the stress state.

  FIG. 10 is a plot of a busy person who is in a responsible position. It can be seen that the ratio of passive stress is small before going to work, but is increased after joining or leaving the company. On the other hand, the point where the sympathetic nervous activity is large is seen only in the area of active stress, and it is expected that the subject does not have to worry about mental illness.

  FIG. 11 is a plot diagram of a depressed patient having a problem at home. It is considered that the sympathetic nervous activity is relatively large in the passive stress region before going to work and at work, and strong stress is applied.

  FIG. 12 is a plot of a patient with autonomic dysfunction, in which a point (abnormal data) in which the sympathetic nervous activity is extremely large in the passive stress area at the time of the company appears, and it is considered that a very strong stress is applied. Can be

  Thus, the stress state of the subject can be detected from the autonomic nerve activity plot.

  Display examples 4A to 4H by the display unit 330 are shown in FIGS. 13 to 20 are autonomic nerve balance plots (PSSNS-SNS-Plot).

  The display unit 330 displays a plurality of points having coordinates of parasympathetic nerve information and sympathetic nerve information calculated corresponding to each activity state detection period in a plot period including a plurality of activity state detection periods (epochs, for example, two minutes). Is displayed on a two-dimensional plane. More specifically, the display unit 330 displays a plurality of plotting periods corresponding to a plurality of living time zones of the subject (to be described later, an in-bed time, a pre-commission time, an in-work time, and a post-exit time). The autonomic nerve balance plot is displayed. 13 to 16 show autonomic nervous balance plots for each of a plurality of living time zones of the subject.

  The life time of the subject is, as in the autonomic nervous activity plots described above, 24 hours in bed (IV), and the time before leaving the office (I) and the time in office ( II) and time after withdrawal (III). FIG. 13 shows a display example 4A of a plurality of autonomic nerve balance plots. Also in the present embodiment, the time in bed, the time before going to work, the time at work, and the time after leaving work are automatically grasped from the posture information described above. For example, the time in bed is from 23:00 to 6:00. A fixed time may be set as each time, such as 6:00 to 9:00 before leaving the company, 9:00 to 18:00 at the company, and 18:00 to 23:00 after leaving the company.

  FIG. 14 shows an example (display example 4B) of an autonomic nervous balance plot of a person whose stress state is normal. During sleep (time in bed), the movement of the sympathetic nerve is small, and the movement of the parasympathetic nerve is large, indicating that the patient is sleeping well. From waking up to going to work (time before going to work), the movement of the sympathetic nerve gradually increases, and the movement of the parasympathetic nerve gradually decreases, indicating that the user is excited. In the company (working time), the movement of the sympathetic nerve is large, and the movement of the parasympathetic nerve is small, indicating that the activity is active. Then, from leaving the work to entering the bed (time after leaving the work), the movement of the sympathetic nerve gradually decreases, and the movement of the parasympathetic nerve gradually increases, indicating that the excitement has begun to calm down.

  FIG. 15 shows an example of an autonomic nervous balance plot of a person whose stress state is between a normal state and an abnormal state (display example 4C). Throughout the day, the sympathetic and parasympathetic movements are similar, meaning that the greater the sympathetic movement, the greater the parasympathetic movement, and the smaller the sympathetic movement, the smaller the parasympathetic movement. .

  FIG. 16 shows an example of an autonomic nervous balance plot of a person whose stress state is abnormal (display example 4D). During sleep (time in bed), the sympathetic nerve movement is large, and the parasympathetic nerve movement is small, indicating that the child is in an excited state even when he goes to bed. From waking to going to work (time before going to work), the movement of the sympathetic nerve gradually decreases, and the movement of the parasympathetic nerve gradually increases, indicating that the excitement is subsiding. At the company (working time), the movement of the sympathetic nerve is small, and the movement of the parasympathetic nerve is large, indicating that no feeling of working has occurred. Then, during leaving the work-entering the bed (time after leaving the work), the movement of the sympathetic nerve gradually increases, and the movement of the parasympathetic nerve gradually decreases, indicating that the user is getting excited.

  The stress state of the subject is detected using the area of the plot shape in the autonomic nerve balance plot, the size of the plot shape in the coordinate axis direction, the distance between the plot shape and the coordinate axis, and the smoothness of the periphery of the plot shape. The plot shape is a shape surrounding a plurality of points plotted on the autonomic nerve balance plot diagram. Of these multiple points, points that are extremely far from other points may not be included in the plot shape as invalid.

  In FIG. 17, the area of the plot shape is (1) large, (2) medium, and (3) small in order from the left (display example 4E). If the area of the plot shape is large, the subject is expected to be in a state where the autonomic nerves are relatively active and there is no stress, and if the area of the plot shape is small, the subject is in a state where the autonomic nerves are relatively inactive It is expected that there will be stress. The stress state may be detected by providing one or more stages of determination reference values for the area of the plot shape and comparing the determination reference value with the area of the plot shape.

  In FIG. 18, the size in the coordinate axis direction of the plot shape is (1) the size in the vertical axis direction is larger than the size in the horizontal axis direction, and (2) the size in the vertical axis direction and the horizontal axis size are almost The same (3) is that the size in the vertical axis direction is smaller than the size in the horizontal axis direction (display example 4F). If the size of the plot shape in the vertical direction is larger than the size in the horizontal direction, the subject is expected to have a sympathetic nerve superior to the parasympathetic nerve and a positive mental state without stress, When the size in the direction is smaller than the size in the horizontal axis direction, the subject is expected to have stress in a negative mental state because the parasympathetic nerve is superior to the sympathetic nerve. One or more levels of determination reference values are provided for the relative size of the plot shape in the vertical and horizontal directions or the absolute size in the vertical and horizontal directions. The stress state may be detected by comparing the plot size with the axial size of the plot shape.

  In FIG. 19, the distance between the plot shape and the coordinate axis is (1) both in contact with the vertical axis and the horizontal axis (the distance is almost 0), and (2) the distance from the vertical axis is the distance dp and the horizontal axis in order from the left. Are in contact, (3) are in contact with the vertical axis and are separated by a distance ds from the horizontal axis, and (4) are separated by a distance dp from the vertical axis and are separated by a distance ds from the horizontal axis. (Display example 4G). When the plot shape is away from the vertical axis, the subject determines that the parasympathetic nerve is active, and when the plot shape is away from the horizontal axis, the subject determines that the sympathetic nerve is active. However, depending on the subject, the distance between the plot shape and the coordinate axes may be far from usual, and the judgment is necessary based on the difference from the usual state.

  In FIG. 20, in the order from the left, the shape around the plot shape is (1) smooth and beautifully arranged without corners, (2) generally smooth but somewhat cornered, (3) many corners and severely disturbed (Display example 4H). If the periphery of the plot is smooth, the subject's autonomic nervous system is expected to be stable and stress-free, and if disturbed, the subject's autonomic nervous system is unstable and stressful. Is expected. A stress state is detected by providing one or a plurality of determination reference values for determining the smoothness of the shape of the periphery of the plot shape, and comparing this determination reference value with the smoothness of the shape of the periphery of the plot shape. Is also good.

  FIG. 21 is a diagram in which the maximum value and the third quartile of the sympathetic nerve information during work in a plurality of subjects are plotted, and FIG. 22 is the sympathetic nerve information during sleep in the plurality of subjects. FIG. 7 is a diagram in which the minimum value of the first quartile is plotted against the first quartile. The state detection unit 320 calculates the maximum value of the plurality of sympathetic nerve information and the plurality of sympathetic nerve information calculated corresponding to each activity state detection period in the state determination period (at work) including the plurality of activity state detection periods (for example, one minute). The stress state is detected using the third quartile of the sympathetic nerve information. Specifically, the maximum value of the plurality of pieces of sympathetic nerve information is equal to or more than the threshold value (preferably 25, more preferably and certainly 27), and the third quartile is the threshold value (preferably 5). At the time described above, it is determined that the subject is in a strong stress state (Large Stress Subject; LS subject). The display unit 330 displays the determination result.

  The present inventors calculated the distribution of the size of the sympathetic nerve information (indicator of sympathetic nerve activity) obtained from the measurement results of a large number of subjects for each of the activity state detection periods with respect to the predetermined state determination period by the quartile. The maximum value is 27 or more and the 75% value from the minimum value side (that is, the third quartile, in other words, the next quartile of the maximum value) is 5 or more. In some cases, the subject was found to be in great stress.

  Specifically, the present inventors calculated the sympathetic nerve information of a plurality of teachers at the kindergarten who are subjects during work (working time) and analyzed the plurality of sympathetic nerve information. The number of teachers who are subjects is 19, and the age is 40.7 ± 15.1. For some teachers, sympathetic nerve information is calculated a plurality of times at different opportunities, and the number of sympathetic nerve information to be analyzed is 30. FIG. 21 is a diagram plotting the maximum value and the third quartile of the sympathetic nerve information calculated for each teacher. In FIG. 21, the horizontal axis represents numbers assigned to a plurality of teachers, and the vertical axis represents the magnitude of sympathetic nerve information. For some teachers, a plurality of sympathetic nerve information calculated from biological information measured a plurality of times is plotted. Based on the plot of FIG. 21, the threshold value of the maximum value of the plurality of sympathetic nerve information of each subject is set to 25 (more certainly, 27), and the threshold value of the third quartile is set to 5. By doing so, it is possible to determine a person who is feeling great stress. In FIG. 21, the fourth, eighth, and tenth faculty members are determined to be those who are feeling great stress.

  In addition, the present inventors consider that sympathetic nerve information should show the lowest value during bedtime, and sympathetic information is used for discrimination of a subject (Remain Stress Subject; RS subject) in which stress remains (accumulates). Neural information was analyzed. As a result, when the minimum value of the sympathetic nerve information was larger than 0.8 and the first quartile was larger than 0.1, the subject found that stress remained.

  Specifically, sympathetic nerve information of a plurality of teachers at the kindergarten who were the same subjects as above while sleeping (during bed time) was calculated, and the plurality of sympathetic nerve information was analyzed. The number of subjects and the number of sympathetic nerve information to be analyzed are the same as described above. FIG. 22 is a diagram plotting the minimum value and the first quartile of the sympathetic nerve information calculated for each teacher. In FIG. 22, the horizontal axis represents numbers assigned to a plurality of teachers, and the vertical axis represents the magnitude of sympathetic nerve information. For some teachers, a plurality of sympathetic nerve information calculated from biological information measured a plurality of times is plotted. Based on the plot of FIG. 22, the minimum threshold value of the plurality of sympathetic nerve information of each subject is set to 0.8, and the threshold value of the first quartile is set to 0.1. Thus, it is possible to determine a person who remains with the stress. In FIG. 22, the fourth, fifth, and fourteen teachers are determined to be those who have remaining stress.

  The present inventors have reported on the relationship between sympathetic nerve information and stress [Stress of Kindergarten teachers: How we tried to detect and to reduce it by using a large amount of available e-gearing available as an alternative to the recent ECG report. / Shirouzu, Shigenori; Seno, Yumeka; Tobioka, Ken; Masaki, Takeo; Yasumatsu, Kiyotaka; Mishima, Norio; Sugano, in Hisanobu / Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE] Disclose.

  In the present embodiment, if accurate electrocardiographic signal data E is obtained, the device for detecting biological information is not limited to the biological information detecting device 1, and the length of the active state detection period (analysis epoch) is also one minute. Not limited to Each of the above thresholds may use a value other than the above. The state determination period may not be during work or sleeping, and may be, for example, a period during which the user is not sleeping (a period of leaving the bed) or 24 hours, and may be arbitrarily set according to the subject to be examined. It is.

  Further, by tracking the time change of the sympathetic nervous activity in this way, it is possible to identify the cause or partner that caused the stress, and it is also possible to issue a warning of stress or bullying by analyzing in real time. It is also possible to build up monitoring stress for workplace stress monitoring, watching over child bullying.

(2nd Embodiment)
FIG. 23 is a block diagram illustrating a configuration example (second embodiment) including a psychosomatic condition diagnosis support device 50 in which an accumulation unit is added to the first embodiment illustrated in FIG. 1. In the configuration of the first embodiment, a secular change such as a stress state can be investigated by adding an accumulation unit to accumulate the analysis data calculated by the psychosomatic state diagnosis support device. In the second embodiment, the same components as those in the first embodiment are denoted by the same reference numerals, and description thereof will be omitted.

  The storage unit 500 receives the analysis data AS output by the state detection unit 320, and stores the analysis data AS together with information (for example, date and the like) on the time at which the biological information data BD was acquired. The information on time is input from the outside, for example, by adding the biological information detecting device 1 to the biological information data BD and extracting the information from the analysis data AS by the state detection unit 320 or when the analysis data AS is stored. It is set by doing. Display unit 530 displays analysis data AS corresponding to the designated time.

  The storage unit 500 may store the biological information data BD stored in the memory 310. Accordingly, when a new analysis function is added to the state detection unit 320, the analysis of the past biological state can be performed by using the biological information data BD stored in the memory 310. Also, instead of adding the storage unit to the mental and physical condition diagnosis support device, it may be prepared separately from the mental and physical condition diagnosis support device. As a result, a large amount of data can be stored.

  In the above-described embodiments (first and second embodiments), three sensors of a body temperature sensor, an acceleration sensor, and an electrocardiogram signal sensor are used, but other sensors may be additionally used. . For example, an oxygen saturation sensor for measuring arterial blood oxygen saturation may be added and used for analyzing the biological condition of the subject. A photoelectric pulse wave sensor of one infrared color may be used.

  Further, the body of the biological information detecting device to be attached to the subject is not limited to one, but may be plural as shown in FIG. By acquiring biological information from a plurality of locations of the subject's body, it becomes possible to detect symptoms (for example, early detection of cerebral infarction or myocardial infarction) that are difficult to detect with only biological information from one location, It is possible to more precisely grasp the health state including the stress state of the subject and the abnormalities of the body. When using a plurality of biological information detecting device main bodies, for example, a unique number is assigned to the biological information detecting device main body so that the obtained biological information can be determined from which biological information detecting device main body. The unique number is added to the biological information signal transmitted by the biological information detecting device.

  Although the embodiment of the present invention has been described above, the present invention is not limited to these examples. A person skilled in the art may appropriately add, delete, or change the design of each of the above-described embodiments, or may appropriately combine the features of the embodiments, as long as they have the gist of the present invention. , Within the scope of the present invention.

Reference Signs List 1 biological information detecting device 10 biological information detecting device main body 20 mounting table 30, 50 psychosomatic condition diagnosis support device 100 biological information detecting unit 110 body temperature sensor 120 acceleration sensor 130 electrocardiographic signal sensor 140 control unit 141 data processing unit 142 mode setting unit 143 Switching section 143a, 143b Contact point 144 Data reading section 150 Memory 160 Transmitting section 170 Charging input section 200 Charging output section 210 Communication section 300 Biometric information input section 310 Memory 320 State detecting section 330, 530 Display section 500 Storage section E Electrocardiographic signal data T body temperature data V speed data AS analysis data BD biological information data BS1, BS2, BS3 biological information signal MS mode signal dp, ds distance LF low frequency component HF high frequency component CS charge start signal

Claims (15)

A biological information input unit into which biological information of the subject detected in time series is input,
A state detection unit that detects a stress state of the subject based on the biological information input to the biological information input unit,
A display unit that displays the stress state of the subject detected by the state detection unit,
In the biological information input unit, the biological information including heart movement information according to the movement of the subject's heart is input,
The state detection unit calculates an RR interval that is a contraction interval of the subject's heart from the heart movement information, and calculates a standard deviation of the RR interval in a coefficient calculation period by an average value of the RR intervals in the coefficient calculation period. Detecting the stress state of the subject using the RR interval variation coefficient calculated by dividing ,
The state detection unit further calculates sympathetic nerve information indicating an activity state of the sympathetic nerve of the subject during the coefficient calculation period,
The display unit displays a plurality of points having coordinates of the RR interval variation coefficient and the sympathetic nerve information calculated corresponding to each of the coefficient calculation periods in a plot period including the plurality of coefficient calculation periods on a two-dimensional plane. Display the autonomic nerve activity plot plotted above,
A psychosomatic condition diagnosis support device , wherein the display unit displays a plurality of autonomic nervous activity plot diagrams in each of a plurality of plot periods corresponding to a plurality of living time zones of the subject . In the biological information input unit, the biological information in a state where stress is artificially applied to the subject over the coefficient calculation period is input,
The psychosomatic state diagnosis support device according to claim 1, wherein the state detection unit detects the stress state of the subject by comparing the RR interval variation coefficient during the coefficient calculation period with a first stress state determination reference value. .   The state detector detects the stress state of the subject by comparing a maximum value of the plurality of RR interval variation coefficients with a first stress state determination reference value in a state determination period including the plurality of coefficient calculation periods. The mental and physical condition diagnosis support device according to claim 1. In the biological information input unit, a stress self-evaluation value of the subject is further input,
The state detector compares a maximum value of the plurality of RR interval variation coefficients with a first stress state determination reference value in a state determination period including a plurality of the coefficient calculation periods, and compares the stress self-evaluation value with a second stress state. The mental and physical condition diagnosis support apparatus according to claim 1, wherein the stress state of the subject is detected by comparing the stress state with a state determination reference value.   The mental and physical condition diagnosis support device according to claim 4, wherein the display unit displays a stress diagnosis plot diagram in which a point having coordinates of the maximum value of the stress self-evaluation value and the RR interval variation coefficient is plotted on a two-dimensional plane. .   A first reference line passing through the first stress state determination reference value on a coordinate axis of a maximum value of the RR interval variation coefficient and parallel to the coordinate axis of the stress self-evaluation value; and the stress self-evaluation value. The at least one of a second reference line passing through the second stress state determination reference value and being parallel to the coordinate axis of the maximum value of the RR interval variation coefficient is displayed on the stress diagnosis plot on the coordinate axis. The psychosomatic condition diagnosis support device according to the above.   The mental and physical condition diagnosis support device according to any one of claims 2 to 6, wherein the first stress state determination reference value is 0.04.   The mental and physical condition diagnosis support device according to claim 2, wherein the condition detection unit detects the diabetic condition of the subject by comparing the RR interval variation coefficient during the coefficient calculation period with a diabetic condition determination reference value.   The mental and physical condition according to claim 3, wherein the condition detecting unit also detects the diabetic condition of the subject by comparing a maximum value of the plurality of RR interval variation coefficients during the condition determination period with a diabetic condition determination reference value. Diagnosis support device.   The mental and physical condition diagnosis support device according to claim 8 or 9, wherein the diabetes condition determination reference value is 0.022.   The display unit displays, in the autonomic nervous activity plot, the point where the RR interval variation coefficient is equal to or less than a threshold and the point where the RR interval variation coefficient is greater than the threshold in different colors. A psychosomatic condition diagnosis support device according to any one of claims 1 to 10.   The display unit displays, in the autonomic nervous activity plot diagram, the point where the RR interval variation coefficient is equal to or less than a threshold value in a light color, and displays the point where the RR interval variation coefficient is greater than the threshold value in a dark color. The mental and physical condition diagnosis support device according to claim 11, wherein the device is displayed as:   The mental and physical condition diagnosis support device according to claim 11 or 12, wherein the threshold value is 0.05. The mental and physical condition diagnosis support device according to any one of claims 1 to 13, wherein the plurality of living time zones are a staying time, a time before going to work, a time at work, and a time after leaving work. A psychosomatic condition diagnosis support device according to any one of claims 1 to 14 ,
A biological information detection device,
The biological information detection device detects biological information including the heart movement information of the subject, having a portable biological information detection device main body that can be mounted on the body of the subject,
A biological information management system, wherein the biological information detected by the biological information detecting device main body is input to the biological information input unit.