JP2007125337A - Method and apparatus for measuring mental healthiness - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method and an apparatus for measuring mental healthiness to be used for a daily life. <P>SOLUTION: A mental healthiness measuring apparatus includes a biological signal detecting means with a biological signal detecting part arranged under the body of a subject in a lateral position; a heartbeat signal extracting means for extracting a heartbeat signal from a biological signal which is detected by the biological signal detecting means; and a beartbeat strength calculating means for calculating the strength of a heartbeat signal. The heartbeat strength signal is calculated based on the detected heartbeat signal, the distribution value of data within a fixed time in the calculated heartbeat strength signal is calculated, and then, the mental healthiness is obtained based on the change tendency of the distribution value concerning the mental healthiness measuring method. Besides, the distribution value of the data within the fixed time in the calculated heartbeat strength signal is calculated so as to obtain a sleep feeling evaluation value through the use of the average value of the plurality of distribution values calculated at each prescribed time during sleeping and the distribution value of the plurality of distribution values. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a method and apparatus for measuring a mental health level indicating a good degree of mental state and a feeling of sleep.

  As society becomes more complex and sophisticated, insomnia has increased dramatically due to the stress caused by trying to cope with the situation. At present, it is said that about 20-30% of the people are prone to insomnia and insomnia, and they are susceptible to stress such as shift work due to changes in social structure and intensifying competition in economic activities. Work conditions will increase and insomnia will increase more and more.

  Sleep is said to be a barometer of health, and if you can wake up comfortably with a good sleep, you will feel refreshed when you wake up. On the other hand, if you have insomnia or insomnia, or if you are forced to sleep with a reversed day / night life due to late-night work, the mood after waking up is often poor. That is, regardless of whether they are conscious or unconscious, the state of sleep affects the mood and behavior at the time of subsequent awakening, which in turn determines the quality of activity after awakening.

  Sleep is a factor that has an important influence on our physical and mental activities, and if we can get good sleep, we can guarantee that our daily activities are physically and mentally healthy. If you can have a comfortable sleep, you will be mentally stable, and if you are mentally stable, you can have a comfortable sleep. That is, if it is possible to know the quality of sleep from the biological signal information at the time of sleep of the subject, it becomes possible to grasp whether the sleep is comfortable, that is, the feeling of sleep, and the mental health level In other words, it is thought that mental health can be grasped.

  A method usually used for analyzing the sleep state is a method of recording the sleep state by the PSG method and obtaining the sleep feeling (sleep quality) by obtaining the transition of the sleep stage of the subject from the measurement result. In this method, it is determined whether the result of recording the transition of the sleep stage is sufficient sleep based on the ratio of the deep sleep stage among the sleep stages.

  When the subject who has recorded the sleep state by the PSG method is awakened and asked about the awakening mood after sleeping, the sleep feeling determination based on the transition of the sleep stage may differ from the content of the subject's answer. For example, in the case of an elderly person or the like, there are many examples in which a subject reports that awakening is refreshing even in sleep when a deep non-REM sleep stage hardly appears. Thus, when it is going to determine a sleep feeling using the sleep stage by PSG method, there exists a problem that it does not correspond with a test subject's bodily sensation in many cases.

  Furthermore, in the method for obtaining the sleep feeling of the subject by the PSG method, it is necessary to collect measurement data by attaching an electrode to the subject's head, and it is difficult to use it on a daily basis. Since the equipment is expensive, it is not practical for the subject to use it regularly in hospital life or at home.

  On the other hand, a method of grasping the sleep feeling of the subject at the time of sleep by taking a topograph of the electroencephalogram and using emotion analysis to analyze the mood state of the electroencephalogram from this data is also disclosed. It takes time to analyze the data, and is unsuitable for capturing the sleep state of the subject at bedtime, and is not practical for use in hospital life or at home.

  Sleep is thought to be greatly influenced by autonomic nerve activity in the brainstem. However, since the above-mentioned method by the PSG method records brain wave data of neural activity of the cerebral cortex, the sleep depth determination obtained by the above-mentioned PSG method strongly reflects the neural activity of the cerebral cortex. Therefore, it is not appropriate to obtain a feeling of sleep indicating the quality of sleep or a mental health level indicating a mental health level.

  In view of the above problems, the present invention can perform sleep feeling evaluation and mental health measurement in accordance with the activity of autonomic nerves in the brainstem, and reduce physical and mental burdens when used in daily life. It is an object of the present invention to provide a mental health measurement method and a mental health measurement device that are not incurred.

  In order to achieve the above object, the method for measuring the mental health of the first solving means of the present invention detects a heartbeat signal from a subject at bedtime using a heartbeat signal detection means, and detects a heartbeat from the detected heartbeat signal. Calculating an intensity signal, calculating a variance value of data of the calculated heart rate intensity signal within a predetermined time, and obtaining a mental health level and a sleep feeling evaluation value from a tendency of fluctuation of the variance value during sleep. .

  The present inventor has confirmed that the fluctuation (dispersion) of the heartbeat signal intensity at bedtime becomes an index of psychological stability, that is, good mood after waking up. By a simple detection operation of detecting a signal, the mental health level and the sleep feeling evaluation value can be easily obtained.

  A second solving means of the present invention is a method for measuring the mental health level of the first solving means, wherein the fluctuation tendency of the variance value of the heart rate intensity signal is a variance value that is divided into a plurality of ranges in advance. It is indicated by the occurrence frequency in the category, and is characterized in that the mental health level is obtained using this value, and the mental health level can be easily determined from this data.

  The third solving means of the present invention is the mental health degree measuring method of the second solving means, wherein an evaluation score per unit time is obtained for each of the variance values divided into the plurality of ranges. It is characterized in that the total value of the evaluation points corresponding to the occurrence frequency of each category is used as the value of mental health level, and the mental health level can be clearly known by displaying with numerical information.

  A fourth solving means of the present invention is the mental health degree measuring method of the first solving means, wherein the variation tendency of the variance value of the heart rate intensity signal is calculated at a plurality of times calculated at predetermined times during sleep. It is indicated by at least one of an average value of the variance values or a variance value of the plurality of variance values, and a sleep feeling evaluation value is measured using these values.

  The fifth solving means of the present invention is a method for measuring the mental health level of the first solving means, wherein the biological signal is detected by the biological signal detecting means arranged under the body of the subject, and the detected biological signal is detected. A heartbeat signal detecting means for extracting a heartbeat signal from the heartbeat signal is used, and the heartbeat signal can be detected without physical restraint on the subject.

  A sixth solving means of the present invention is a method for measuring the mental health level of the fifth solving means, which comprises a differential pressure sensor and a biological signal detector, and is housed inside the biological signal detector. Biological signal detection means for detecting a biological signal by detecting a change in air pressure with a micro-differential pressure sensor is used, which is suitable for detecting a biological signal having a fine signal level.

  A seventh solving means of the present invention is a method for measuring the mental health level of the first solving means, wherein a sphygmomanometer is used which wears the heartbeat signal detecting means on a wrist or an upper arm.

  According to an eighth aspect of the present invention, there is provided a mental health measuring device comprising: a heartbeat signal detecting means for detecting a heartbeat signal from a subject at bedtime; a heartbeat intensity calculating means for calculating a heartbeat intensity signal from the detected heartbeat signal; And a mental health level calculating means for calculating a variance value of data within a predetermined time of the calculated heart rate intensity signal and obtaining a mental health level and a sleep feeling evaluation value from a variation tendency of the variance value. To do.

  A ninth solving means of the present invention is the mental health degree measuring apparatus according to the eighth solving means, wherein the variation tendency of the variance value of the heart rate intensity signal is a variance value that is divided into a plurality of ranges in advance. It is indicated by the frequency of occurrence in the category, and this value is used to determine the mental health level.

  A tenth solving means of the present invention is the mental health degree measuring apparatus according to the ninth solving means, wherein an evaluation score per unit time is obtained for each of the variance values divided into the plurality of ranges. The total value of evaluation points corresponding to the occurrence frequency of each category is defined as the value of mental health.

  The eleventh solving means of the present invention is the mental health degree measuring apparatus according to the eighth solving means, wherein the fluctuation tendency of the variance value of the heart rate intensity signal is calculated at a plurality of times calculated at predetermined times during sleep. It is indicated by at least one of an average value of the variance values or a variance value of the plurality of variance values, and a sleep feeling evaluation value is measured using these values.

  A twelfth solving means of the present invention is the mental health measuring apparatus according to the eighth solving means, wherein the heartbeat signal detecting means detects a biological signal by a biological signal detecting means arranged under the body of the subject. And a heartbeat signal is extracted from the detected biological signal.

  The thirteenth solving means of the present invention is a mental health measuring device according to the twelfth solving means, wherein the biological signal detecting means comprises a slight differential pressure sensor and a biological signal detecting section, and the biological signal detecting section. A biological signal is detected by detecting a change in the pressure of the air contained in the inside with a slight differential pressure sensor.

  A fourteenth solving means of the present invention is the mental health measuring device according to the eighth solving means, wherein the heartbeat signal detecting means is a pulse meter attached to the wrist or the upper arm. .

As described above, the method and apparatus for measuring the mental health of the present invention is a method for determining the heartbeat signal intensity of the subject and determining the mental health from the variation (dispersion) of the intensity. The intensity is obtained by capturing the intensity of vibration of the aortic valve of the heart with air vibration and filtering. The variation of the measured heartbeat signal intensity is known to be proportional to blood pressure. Moreover, the knowledge which has the relation which is substantially proportional to the test subject's sympathetic nerve component calculated | required from the rr space | interval of the electrocardiograph is acquired. For this reason, it is possible to grasp | ascertain the test subject's sleep state exactly. As a result, it is possible to accurately predict the mood (mental health) and the feeling of sleep after waking up. A heartbeat signal is usually obtained from an electrocardiograph, but since this electrical signal is a command signal to the heart, a change in heartbeat intensity is very small. Therefore, it is not related to the autonomic component. Although it is possible with the pulse of the wrist (radial artery), since the distance from the heart is far away, the N / S is poor and there is a problem in stability measurement.
In this method, not the heart rate intensity but the variation in the heart rate intensity is obtained because the heart rate intensity due to sleeping (upward, sideways, etc.) greatly changes when measuring during sleep. This is because if the variation in heart rate is used, it can be processed in a unified manner regardless of the sleeping posture. This allows continuous measurement.

  The mental health measurement method and apparatus of the present invention do not require large-scale measurement equipment like the conventional PSG method, and can be measured non-invasively, so that it can be easily used in daily life. It is suitable for the health management of subjects to be performed continuously.

  The method and apparatus for measuring mental health according to the present invention evaluates the degree of sleep from a heartbeat signal, and the conventional PSG method uses a deep non-REM sleep stage like that of an elderly person. It is possible to evaluate the feeling of sleep even when sleep is such that almost no is observed.

  Fig.1 (a) is a block diagram which shows the process of the Example which implements the health degree measurement of this invention, FIG.1 (b) is a partial sectional view seen from the arrow direction in Fig.1 (a). It is. The biological signal detection means 1 shown in FIG. 1 is a non-invasive sensor that detects a minute biological signal of a subject, and is detected by the biological detection means 1 in the signal amplification shaping means 2 so that it can be processed in a later processing step. A heartbeat signal is extracted by amplifying the signal and removing unnecessary signals such as respiration by a band pass filter or the like.

  The biological signal detection means 1 includes a pressure detection tube 1a and a pressure sensor slight differential pressure sensor 1b, and constitutes a non-invasive biological signal detection means. The minute differential pressure sensor 1b is a sensor that detects minute pressure fluctuations. In this embodiment, a low-frequency condenser microphone type is used, but the present invention is not limited to this, and an appropriate resolution and dynamic range are provided. What is necessary is just to have.

  The low-frequency condenser microphone used in this example is replaced with a general acoustic microphone that does not consider the low-frequency area. This is a significant improvement and is suitable for detecting minute pressure fluctuations in the pressure detection tube 1b. In addition, it is excellent for measuring minute differential pressure, has a resolution of 0.2 Pa and a dynamic range of about 50 Pa, and is several times the performance of a fine differential pressure sensor using a ceramic that is normally used. It is suitable for detecting a minute pressure applied to the pressure detection tube 1a through a biological signal passing through the body surface. The frequency characteristic shows an almost flat output value between 0.1 Hz and 20 Hz, and is suitable for detecting minute biological signals such as heartbeat and respiration rate.

  As the pressure detection tube 1a, a tube having an appropriate elasticity is used so that the internal pressure varies in accordance with the pressure variation range of the biological signal. Further, in order to transmit the pressure change to the fine differential pressure sensor 1b at an appropriate response speed, it is necessary to appropriately select the volume of the hollow portion of the tube. When the pressure detection tube 1a cannot satisfy the appropriate elasticity and the volume of the hollow portion at the same time, the hollow portion of the pressure detection tube 1a is loaded with a core wire having an appropriate thickness over the entire length of the tube so that the volume of the hollow portion is appropriately set. Can take.

  The pressure detection tube 1a is arranged on a hard sheet 8 laid on the bed 7, and a cushion sheet 9 having elasticity is laid on the pressure detection tube 1a, and the subject lies on the pressure detection tube 1a. . In addition, the pressure detection tube 1a may be configured to stabilize the position of the pressure detection tube 1a by being incorporated in the cushion sheet 9 or the like.

  In the present embodiment, two sets of pressure detection tubes 1a are provided, one of which detects a biological signal of a part of the subject's chest and the other of which detects a part of the subject's buttocks, so that the subject's sleeping posture Regardless of the configuration, the biometric signal is detected. However, the pressure detection tube 1a may be arranged only in one of the chest region and the buttocks region.

  The biological signal detected by the biological signal detection means 1 is a signal in which various vibrations emitted from a human body are mixed, and includes a heartbeat signal, a respiratory signal, a wake-up signal, and the like. The above heart rate signal includes a change in pressure (ie, blood pressure) based on the heart's pump function as vibration and is included in the biological signal, and is recognized as a heart rate signal by extracting it.

  The automatic gain control means 3 is a so-called AGC circuit that automatically performs gain control so that the output of the signal amplification shaping means 2 falls within a predetermined signal level range. The gain value (coefficient) at this time is used as the signal strength. Output to the arithmetic means 4. For gain control, for example, the gain is set so that the amplitude of the output signal decreases when the peak value of the signal exceeds the upper threshold, and the gain is increased when the peak value falls below the lower threshold. is doing.

  The heart rate intensity calculation means 4 calculates the signal intensity from the gain control coefficient applied to the biological signal in the automatic gain control means 3. The gain value obtained from the above AGC circuit is set to be small when the signal size is large and large when the signal size is small. It is preferable to set a function indicating the signal intensity so as to be inversely proportional to the gain value.

  The mental health degree calculating means 5 is a calculating means for obtaining a mental health degree and a sleep feeling evaluation value of the subject who is sleeping from the fluctuation tendency of the dispersion value of the heart rate intensity. First, a dispersion value (standard deviation) of 60-second data of the heart rate intensity obtained by the heart rate intensity calculating means 4 is obtained. The heart rate intensity data is measured every second, and the data for 60 seconds, that is, the variance value of 60 heart rate intensity data, is determined from that point. As a result, time-series data at intervals of 1 second of variation (dispersion value) in heart rate intensity is obtained. The mental health level and the sleep feeling evaluation value are obtained by obtaining the trend (variation tendency) of the time series data of the variance value as a specific index value.

  For the index value of the mental health level, the occurrence frequency (occurrence time) for each category is obtained for the variance value categories that have been segmented in advance using time-series data of heart rate intensity variations (variance values). Furthermore, the index value of the mental health level is calculated by adding the evaluation points obtained from the accumulated time data for each category and the evaluation value given in advance to each category.

  On the other hand, as an index value of sleep feeling, an average value of time series data of heartbeat intensity variation (dispersion value) is obtained, and the value of this average value is used as an index value of sleep feeling.

  The data storage / output means 6 is a means for outputting or storing data such as the above time-series data, cumulative time data for each category, mental health index value and sleep feeling index value to the output device.

  Although an example in which a hollow tube is used as the biological signal detection means has been described, the air mat shown in FIG. 2 may be used as the detection means. Here, the biological signal detection means 10a is an air mat in which air is enclosed, and an air tube 10b is connected to one end of the air signal detection means 10a, and is connected to the fine differential pressure sensor 10c. The same differential pressure sensor as that described in the case of the biological signal detecting means using a hollow tube can be used.

  Next, a procedure for obtaining the mental health level and the sleep feeling evaluation value will be described. A heartbeat signal is detected by removing unnecessary signals such as respiration in the signal amplification shaping means 2 from the biological signal detected by the biological detection means 1 with a band-pass filter or the like. The peak value of the detected heartbeat signal is controlled by controlling the gain by automatic gain control means (AGC). The heart rate intensity calculating means 4 calculates a heart rate signal using the gain value of the automatic gain control means (AGC) at this time.

  The procedure for calculating the mental health level and the sleep feeling evaluation value in the mental health level calculating means 5 will be described with reference to the flowchart of FIG. The mental health level calculating means 5 first takes in the heart rate intensity signal calculated by the heart rate intensity calculating means 4 and calculates the dispersion value (standard deviation) of the heart rate intensity data for 60 seconds going back from each time point. Thus, time-series data of heart rate intensity as shown in FIG. 4 is obtained. FIG. 4 shows the transition of the sympathetic nerve component for comparison, and it can be seen that the transition of the variance value (standard deviation) of the heart rate intensity and the transition of the sympathetic nerve component take a similar movement. That is, since the mental state is considered to be relaxed as the value of the sympathetic nerve component is small, it is thought that the mental value is more stable as the variance value (standard deviation) of the heart rate intensity is small. Incidentally, the unit of the standard deviation of the heart rate intensity in FIG. 4 is a percentage based on the standard deviation of the maximum possible heart rate intensity.

  Next, the mental health level calculating means 5 calculates the mental health level and the sleep feeling evaluation value using the time series data of the dispersion value of the heart rate intensity.

  In order to obtain the index value of the mental health level, the occurrence frequency (occurrence time) for each variance value category is calculated by dividing into a plurality of categories using time series data of heart rate intensity variance. FIG. 5 shows the results. The variance value categories are expressed as a percentage of the maximum variance value (standard deviation value) that appears in the subject. The graph is divided into five categories of 4%, 4 to 5%, 5 to 6%, and 6% or more, and the bar graph indicates how much the variance value (standard deviation) corresponding to this category appears.

  In addition, the variance value category of heart rate intensity can eliminate the influence of individual differences by determining the boundary value of the category using the average value and standard deviation (variance value) of the time series data. For example, normalization is performed by using the average value of the time series data, a value that is larger by the standard deviation from the average value, a value that is twice the standard deviation than the average value, or a value that is smaller by the standard deviation of the average value. It is possible to eliminate the influence of individual differences. The data division of the variance value of the heart rate shown in FIG. 4 is determined by normalization in this way.

  As can be seen from FIG. 4, the smaller the heart rate variance value, the deeper the sleep, the more stable the mental state. Therefore, when the heart rate dispersion value is 3% or less, it is mentally stable. Therefore, it can be considered that sleep is not well sleep with shallow sleep as the dispersion value increases.

Considering the above contents, an index value indicating the mental health level is obtained by the following formula (A).
S = α · t ₁ + β · t ₂ + γ · t ₃ + δ · t ₄ + ε · t ₅ (A)
Here, t ₁ , t ₂ , t ₃ , t ₄ , and t ₅ are variances corresponding to categories of variance values of 3% or less, 3 to 4%, 4 to 5%, 5 to 6%, 6% or more, respectively. The total time that the value occurred. Further, α, β, γ, δ, and ε are respectively corresponding weighting factors, and are determined so as to become larger as the variance value is smaller. In the case shown in FIG. 6, the mental health index is calculated by setting α = 10, β = 4, y = 1, δ = 0.3, and ε = 0.

  FIG. 6 is a graph in which the mental health index value (score display) obtained by the formula (A) and the mental health perceived by the subject are recorded for one month. The mental health index value (score display) and the mental health perceived by the subject tend to be almost similar, and if the mental health index value (score display) is high, the subject is aware You can say that your mental health is good. On the other hand, there are several cases where the mental health index value (score display) and the evaluation of the mental health perceived by the subject do not coincide with each other. For example, the mental health on March 26 in FIG. The self-determination of the subject is highly evaluated. The actual subject on this day is in a state of lack of sleep due to work all night, but as a result of concentrating on the work, the subject's mood is elevated and the evaluation of the self-judgment mental health is high. However, although the mental health level after the next day shows a high value, the evaluation of the subject's self-judgment mental health level is low. From this, it is expected that the mental health level (feeling) felt by the subject will decrease over the next several days if the value of the mental health level becomes low.

On the other hand, as the sleep feeling evaluation value, an average value is obtained from time-series data of heartbeat intensity dispersion, and the average value is used as an index of sleep feeling. FIG. 7 is a graph showing the transition of the dispersion value of the heart rate intensity signal. FIG. 7 (a) shows the transition of the dispersion value of the heart rate intensity signal of a healthy subject in the 20s, and FIG. 7 (b) shows the transition of the dispersion value of the heart rate signal of a healthy subject of the 80s. FIG. 7 (c) shows the transition of the variance value of the heart rate intensity signal of the subject who developed dementia in the 80s. The average value of all the variance value data in the graph is A ₀ shown in FIG. 7, and the σ is the variance value (standard deviation) of the variance value. As can be seen from FIG. 7, the dispersion value of the heart rate intensity signal is almost constant in the younger group, whereas the elderly have many times when the variance value of the heart rate intensity signal takes a large value. Mean value A ₀ of the variance of the heart rate intensity signal resulting young shows a low tendency than the mean value A ₀ of the elderly. Further, the variance value of the variance value of the heart rate intensity signal shows the same tendency.

An elderly subject with dementia has a higher average value A ₀ of the heart rate intensity signal variance and its variance value σ even higher than those of the same generation of elderly people.

  The feeling of sleep is considered to be influenced by the function of the autonomic nervous system, and it can be determined that the quality of sleep is better as the dispersion of heart rate intensity deeply related to the movement of the autonomic nerve is lower. As can be seen from the experimental results in FIG. 7, this value varies among individuals. In general, this value is higher for the elderly and younger people are lower. This result is consistent with the fact that deep non-REM sleep is rarely seen in the elderly, and is effective in evaluating the feeling of sleep.

  As described above, the present invention presents a method for deriving an index value indicating a mental health level and a feeling of sleep from data on a dispersion value of heart rate intensity, and individual differences in the feeling of sleep are clarified by a sleep feeling evaluation value. In addition, it is possible to know mental stability including the degree of sleep quality by considering the mental health level.

  That is, when the mental health index value obtained by the mental health measurement method and apparatus of the present invention is equal to or greater than a predetermined value, it is determined that the mental health is stable including the degree of sleep quality. Is done. On the other hand, since the quality of sleep can be determined from the sleep feeling evaluation value, it is possible to use these index values as a measure for the health management of the subject. Further, as shown in FIG. 6, the mental health index value (score display) is expected to affect the mental health level felt by the subject for the next several days. It can be used as a leading indicator for managing living conditions.

  In the description of the present embodiment, as a method for detecting a heartbeat signal, a method for extracting a heartbeat signal from a biological signal obtained by a biological signal detection unit laid under the body of the subject has been described. Any detection means can be used as long as it can continuously obtain a heartbeat signal or a signal equivalent to the heartbeat signal. For example, if it is a heart rate meter, a pulse meter, or a pulse meter of the type worn on the body and can continuously record data, it can be used as the biological signal detecting means of the present invention.

  The method usually used for analyzing the sleep state is a method of recording the sleep state by the PSG method and obtaining the sleep quality of the subject from the measurement result to know the sleep quality. When the stage appears for an appropriate time, it is determined that sufficient sleep has been obtained. However, when this method is applied to an elderly person, the judgment may be different depending on the actual feeling of the subject and the method based on the transition of the sleep stage obtained by the PSG method. This causes a problem that it cannot be used. Furthermore, even with a method using the PSG method or a method using an electroencephalogram topograph, it is necessary to collect measurement data by attaching electrodes to the subject's head, and the subject cannot be used in daily life or at home. There is also.

  The method and apparatus for measuring the mental health of the present invention is a method for determining the heartbeat signal intensity of a subject and determining the index value of the mental health and sleep feeling from the intensity variation (variance). Is closely related to the movement of the subject's sympathetic nerve, so that the subject's sleep state can be accurately grasped. Furthermore, since it can measure non-invasively, it can be used easily in daily life.

  The mental health degree including the degree of sleep quality is judged from the mental health index value obtained by the mental health degree measuring method and apparatus of the present invention. On the other hand, since the quality of sleep can be determined from the sleep feeling index values obtained by the sleep feeling evaluation method, it is possible to use these index values as a measure for the health management of the subject, It can be used as a leading indicator for managing the health and living conditions of a child.

  From this, it can be used as a means of daily sleep management for people who have insomnia or insomnia, and it can be applied to sleep management in a 24-hour workplace to improve work efficiency and mentally. Since it is possible to prevent accidents due to poor health, it greatly contributes to health management at the workplace. Furthermore, it is useful for elderly people's health management by applying it to the elderly, and by using it in nursing homes or care houses, it is possible to collect data on a daily basis for sudden physical condition etc. Therefore, it will contribute to the health management of the elderly.

  It is a block diagram which shows the work flow of the mental health degree measuring method of this invention.   It is a top view which shows another biological signal detection means.   It is a flowchart which shows the procedure which calculates mental health and a sleep feeling evaluation value.   It is a graph of the time series data of the variance value of the heart rate signal intensity.   It is a graph which shows the occurrence frequency for every dispersion value division.   It is the graph which wrote together the mental health index value and the mental health perceived by the subject.   It is a graph which shows transition of the dispersion value of heart rate intensity.

Explanation of symbols

1 Living body detection means (pressure detection means)
DESCRIPTION OF SYMBOLS 1a Pressure detection means 1b Minute differential pressure sensor 2 Signal amplification shaping means 3 Automatic gain control (AGC) means 4 Heart rate intensity calculation means 5 Mental health calculation means 6 Data storage / output means 7 Bed 8 Hard sheet 9 Cushion sheet 10 Living body Detection means (pressure detection means)
10a Pressure detection means (air mat)
10b Air tube 10c Differential pressure sensor

Claims (14)

  A heartbeat signal is detected from a subject at bedtime using a heartbeat signal detection means, a heartbeat intensity signal is calculated from the detected heartbeat signal, a variance value of data within a predetermined time of the calculated heartbeat intensity signal is calculated, A mental health degree measuring method, wherein a mental health degree and a sleep feeling evaluation value are obtained from a variation tendency of the dispersion value in the inside.   The fluctuation tendency of the variance value of the heart rate intensity signal is indicated by an occurrence frequency in a category of variance values divided in advance into a plurality of ranges, and mental health is obtained using this value. 2. The method for measuring mental health according to 1.   An evaluation score per unit time is determined for each of the variance values divided into the plurality of ranges, and a total value of evaluation scores corresponding to the occurrence frequency of each division is used as a value of mental health. The method of measuring mental health according to claim 2, wherein   The variation tendency of the variance value of the heart rate intensity signal is indicated by at least one of an average value of the plurality of variance values or a plurality of variance values of the variance values calculated at a predetermined time during sleep. The method of measuring mental health according to claim 1, wherein a sleep feeling evaluation value is measured using the value.   The mental signal according to claim 1, wherein the heartbeat signal detection means detects a biological signal by a biological signal detection means arranged under the body of the subject, and extracts a heartbeat signal from the detected biological signal. Health measure method.   The biological signal detection means includes a fine differential pressure sensor and a biological signal detection unit, and detects a biological signal by detecting a change in pressure of air stored in the biological signal detection unit with the fine differential pressure sensor. The method for measuring mental health according to claim 5, wherein:   The method for measuring mental health according to claim 1, wherein the heartbeat signal detecting means is a pulse meter attached to a wrist or an upper arm.   Heart rate signal detecting means for detecting a heart rate signal from a subject at bedtime, heart rate intensity calculating means for calculating a heart rate intensity signal from the detected heart rate signal, and calculating a variance value of the calculated heart rate intensity signal within a certain time And a mental health level measuring device for calculating a mental health level and a sleep feeling evaluation value from a variation tendency of the variance value.   The fluctuation tendency of the variance value of the heart rate intensity signal is indicated by an occurrence frequency in a category of variance values divided in advance into a plurality of ranges, and mental health is obtained using this value. The mental health measuring device according to 8.   An evaluation score per unit time is determined for each of the variance values divided into the plurality of ranges, and a total value of evaluation scores corresponding to the occurrence frequency of each division is used as a value of mental health. The mental health measuring device according to claim 9, wherein the device is a mental health measuring device.   The variation tendency of the variance value of the heart rate intensity signal is indicated by at least one of an average value of the plurality of variance values or a plurality of variance values of the variance values calculated at a predetermined time during sleep. The mental health measurement device according to claim 8, wherein the sleep feeling evaluation value is measured using the value.   9. The mental signal according to claim 8, wherein the heartbeat signal detection means detects a biological signal by a biological signal detection means arranged under the body of the subject, and extracts a heartbeat signal from the detected biological signal. Health measuring device.   The biological signal detection means includes a fine differential pressure sensor and a biological signal detection unit, and detects a biological signal by detecting a change in pressure of air stored in the biological signal detection unit with the fine differential pressure sensor. The mental health measuring device according to claim 12, wherein the device is a mental health measuring device.   The mental health measuring device according to claim 8, wherein the heartbeat signal detecting means is a pulse meter attached to a wrist or an upper arm.

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