JPH053920A - Biorhythm adjusting device - Google Patents

Abstract

PURPOSE:To effectively adjust the biorhythm by measuring the biorhythm curve of a subject, evaluating the same and giving the optimum stimulation to the subject according to the result. CONSTITUTION:A bilrhythm curve measured by a biorhythm curve measuring means 1 is evaluated by a biorhythm curve evaluating means 2, and according to the evaluation result, stimulation is given to a living body by a biorhythm adjusting means 3 to adjust the biorhythm. Thus, stimulation suitable to a biorhythm curve of an examined person ca be given.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a biorhythm adjusting device for adjusting a human biorhythm to a desired state.

[0002]

2. Description of the Related Art When various biological phenomena are expressed in time series, they often show periodicity. Moreover, many of them are considered to be self-excited vibrations, and are collectively called biorhythms. Biological rhythms are divided into several types according to their cycle, and they range from a long one year to a few seconds. Humans become more active in the light period and become active, and in the dark period become less alert and enter rest. This is due to the Circadian rhythm.
m: biological rhythm (biological rhythm) carved by a biological clock called a rhythm with a cycle of about 1 day.
Is one of.

Of the biological rhythms, the one most closely related to human life is the circadian rhythm having a cycle of about one day. Typical circadian rhythms in humans include temperature fluctuations, sleep-wake cycles, and hormone secretion fluctuations. In addition, physiological phenomena associated with human life, such as mental and physical activity, work and exercise ability, sensitivity to drugs, and functions of the autonomic system, can be considered to show circadian fluctuations.

At present, the theory that human circadian rhythm may be divided into two vibrating body groups, a group centering on the core body temperature rhythm and a group centering on the sleep-wake cycle, is predominant. It is said that the core body temperature rhythm is influenced by the light-dark cycle, and the sleep-wake cycle is influenced by the social entrainment factor.

Conventionally, US Pat. No. 4,858,609 discloses a technique for changing the phase and amplitude of circadian rhythm by using high illuminance light. For example, assuming that a deep body temperature rhythm measured under conditions without disturbance is irradiated with high illuminance light in the phase immediately before the lowest point, the phase of the biological rhythm will recede, and in the irradiation immediately after the lowest point, It is known that the phase of rhythm advances. It is also known that the amplitude of rhythm can be increased or decreased depending on the way of irradiating light.

On the other hand, for example, JP-A-61-262786
Japanese Patent Laid-Open No. 2-88995 and Japanese Patent Laid-Open No. 2-88995 disclose a technique of gradually raising the illuminance of the bedside a little before the wake-up time to create a state in which it is easy to wake up, and then applying a wakeful stimulus such as a sound to wake up. Has been done.

Further, Japanese Patent Application Laid-Open No. 2-115726 discloses a technique for measuring how much light oneself receives in his / her life.

[0008]

The above-mentioned US Pat. No. 4,
No. 858,609 is a technique related to "high-brightness photomask", and requires light irradiation at 7,500 to 12,000 lux for 5 to 6 hours. It may be necessary to illuminate for several hours to correct a large shift in rhythm such as shift work, elimination of jet lag, and measures against rhythm disorders, but even if you wear a mask of eyeglass type or stand type , It is hard to say that it is an everyday means. In order to make it a practical rhythm adjustment device, it is considered necessary to have means for adding rhythm to the rhythm, which can be used by people who are engaged in normal life. Also, even in shift work, if the rotation is short, a rapid rhythm shift is not necessary, and while refreshing your mind during work, you can immediately return to the normal 24-hour day-to-day social life. I have to think about what to do. It is also necessary to consider using stimuli other than light. Especially, in rhythm adjustment that does not require a large phase shift, it is considered that temperature stimulation and stimulation that raises the physical and mental activity are also effective. On the other hand, in the light alarm, the transition from sleep to awakening is considered to be smooth, but there is a problem that the illuminance of light is insufficient in terms of adjusting the rhythm after awakening. Moreover, the conventional technique has a problem that the information on the biorhythm is not effectively used. Further, in the conventional technology, physical quantities (ambient illuminance, outside temperature, etc.) and activities (wrist activity, etc.) that stimulate are measured in daily life,
There is also a problem that there is no means for feeding back the result and adjusting the amount and timing of stimulation, and environmental information is not used effectively.

The present invention has been made in view of the above points, and an object of the present invention is to measure a biological rhythm curve of a subject and evaluate the biological rhythm by applying an appropriate stimulus. It is to provide a biological rhythm adjustment device that can be adjusted mechanically.

[0010]

In order to solve the above-mentioned problems, the biological rhythm adjusting device according to the present invention, as shown in FIG. 1, measures a biological rhythm curve for measuring a biological rhythm curve. From the means 1, the biorhythm curve evaluation means 2 for evaluating the measured biorhythm curve, and the biorhythm adjustment means 3 for stimulating the living body according to the evaluation result of the biorhythm curve to adjust the biorhythm. It is characterized by being configured. The stimulus given to the living body preferably includes at least optical stimulus.

[0011]

In the present invention, the biorhythm curve measuring means 1
The biorhythm curve is measured by, and the measured biorhythm curve is evaluated by the biorhythm curve evaluation means 2,
According to the evaluation result, the biological rhythm adjusting means 3 stimulates the living body to adjust the biological rhythm.
The biorhythm can be adjusted according to the condition of the subject.

[0012]

FIG. 2 shows the construction of the biorhythm curve measuring means 1 used in the present invention. The biorhythm curve measuring means 1 includes a main sensor section 12 and a sub sensor section 13 as the detecting means 11. The main sensor unit 12 is for measuring core body temperature, and the main measurement item is rectal temperature. A general method for measuring rectal temperature is to insert a probe with a thermistor embedded at the tip from the anus for 10 cm or more, and fix it with tape to prevent it from coming off. A device for calculating a temperature from a resistance value of a thermistor and storing it in a memory is commercially available as a portable thermometer. However, if it is difficult to measure the rectal temperature, the eardrum temperature or the trunk central temperature is measured as an alternative measurement item. In addition, the sub sensor unit 13
It is for disturbance measurement, and its main measurement items are ambient temperature and illuminance.
And the amount of physical activity. The timing of the deep body temperature measurement and the disturbance measurement by the detection means 11 is determined by the timer means 14. By allowing the timer time of the timer means 14 to be arbitrarily set, variable sampling can be performed. As a result, the sampling cycle can be shortened in the portion where the body temperature fluctuation is large, and the sampling cycle can be lengthened in the portion where the body temperature fluctuation is small, so that efficient measurement data can be collected.

The measurement data of the main sensor section 12 and the sub sensor section 13 of the detection means 11 are stored in the storage means 15 in time series. The above-mentioned measurement interval by the timer means 14 is preferably in the range of 1 minute to 5 minutes. The average value may be calculated and the average value may be stored in time series.

Next, the correction means 16 complements the missing data of the deep body temperature measurement data obtained by the main sensor portion 12 of the measurement data stored in the storage means 15 in time series, and the sub sensor portion 13 makes up the missing value. The body temperature rhythm curve is extracted by correcting the influence of disturbance elements based on the disturbance measurement data and further removing high frequency noise with a low frequency pass filter. The estimating unit 17 has a curve fitting unit that uses a periodic function curve that approximates the body temperature rhythm, a unit that estimates the valleys and peaks of the rhythm curve from the front and rear point sequences, and the like.

The rhythm curve output means 18 is means for displaying the waveform of the rhythm curve, and is composed of, for example, an LCD display with a graphic function. The characteristic parameter output means 19 determines the cycle of the body temperature rhythm curve.
It is for calculating and outputting parameters of the periodic function such as phase and amplitude, and other characteristics of the rhythm curve. Here, other characteristics of the rhythm curve include, for example, a duty ratio, a spectrum, a rising slope, a falling slope, the number of maximum values, and the number of minimum values.

FIG. 3 shows an example of long-term measurement of rectal temperature. The rectal temperature was sampled every minute for about 34 hours. The body temperature was low during bedtime and increased during activity. A slight rise in body temperature can be seen when waking up midway.
Moreover, masking of body temperature rhythm was observed due to the influence of daily life, and the rise in body temperature due to going out or using a shower was particularly remarkable. In this measurement example, the subject is walking in a town with an outside temperature of 30 ° C. or higher from 12:00 to 14:00, and a remarkable rise in body temperature is seen. Noise is observed when going out at 12:00. Further, the body temperature fluctuation during bedtime does not always become monophasic, and the body temperature fluctuation shows a biphasic condition in which there are two minimal values during the second night from bedtime to wakeup.

Next, the detailed structure of the correction means 16 will be described with reference to FIG. As shown in FIG. 3, when an actual measurement example of the rectal temperature is viewed, there are influences of the behavior and the outside temperature, and measurement noise is also observed. First, the noise removing means 61 removes as noise the isolated point sequence that is 0.1 ° C. or more apart from the surrounding point sequence. This utilizes the property that the core body temperature does not change rapidly. Next, missing value complementing means 62
Then, the part that cannot be measured after being removed as noise is supplemented with a straight line. As the complementing method, spline complementing may be used instead of straight line complementing.

Next, the disturbance influence correction means 63 eliminates the influence of the disturbance element on the measurement data of the deep body temperature based on the disturbance measurement data by the auxiliary sensor means 13. For example, when the outside air temperature rises, the measurement data of the core body temperature is corrected downward. Further, when the ambient illuminance increases, it can be determined that the user has gone out, so the measurement data of the core body temperature is corrected downward. In addition, if activity increases,
As the core body temperature is expected to increase due to activity, the core body temperature measurement data is revised downward. However, the correction based on the amount of activity is performed for the section where the core body temperature is considered to be affected by the amount of activity, that is, the time zone in which the person is awake. Also, the correction based on the outside temperature (including the temperature inside the bed) is
In particular, it is performed during a time period when it is considered to be affected by a rapid change in the outside temperature, and is usually performed during the awakening period and the sleeping period. Finally, the low-pass filter 64 removes high-frequency noise from the measurement data after correcting the influence of disturbance, and outputs a rhythm curve of deep body temperature as illustrated in FIG. With this rhythm curve, a temporary rise in body temperature due to going out from 12:00 to 14:00 and a shower at 21:00 in the measurement example shown in FIG. 3 is removed, and a very smooth rhythm curve having a cycle of about one day is obtained. Has been.
As for the body temperature fluctuation during sleep, the features of the monophasic body temperature fluctuation of the first night and the biphasic body temperature fluctuation of the second night are faithfully extracted.

Next, the estimating means 17 estimates the true rhythm curve of deep body temperature from the rhythm curve of deep body temperature obtained by the correcting means 16. For example, it is possible to perform curve fitting to the reference curve by least-squares approximation. As the reference curve, a function such as the following expression can be used as a modified trigonometric function. f (x) = A · {1- (1-cos (2π (x-c) / L) / 4) ² } where A is the amplitude and L is the period of 24 hours.
As another reference curve, as shown in FIG. 6, a rectangular wave having a cycle of 24 hours and a duty ratio of 1: 2 or a curve obtained by rounding the corners may be used. This utilizes the fact that the ratio of bedtime and wakefulness is approximately 1: 2.
Alternatively, as shown in FIG. 7, a triangular wave having a period of 24 hours or a curved curve with its corners rounded may be used.
In addition, it is also possible to use reference data created by adding and averaging data of several cycles of an individual, but it goes without saying that this differs depending on the subject.

Next, a method of estimating the true rhythm curve by a method other than curve fitting to the reference curve will be described. For example, a method of obtaining a coefficient of an equation that fits the measurement data by using a differential equation expressing the non-linear vibration (Vanderpole type, Volterra type, etc.) can be considered. Alternatively, there is a method of estimating a curve near the lowest point or the highest point from the data time series of the rising and falling portions of the output curve of the correction means 16 or predicting a curve between the points from the front and back, for example, a linear AR. A model or a linear ARMA model may be used. Further, the output of the low frequency pass filter 64 of the correction means 16 can be used as it is as an estimation curve. In this case, particularly when determining the lowest point of the deep body temperature during sleep, the number of valleys is not limited to one, but the minimum value among the minimum values may be taken.

Since the eardrum temperature changes in the same manner as the rectal temperature, if the rectal temperature is difficult to measure, even if the deep body temperature is measured by an earphone type eardrum temperature sensor as shown in FIG. good. The earphone type eardrum temperature sensor can be configured using an infrared radiation thermometer or a thermistor. Also, if a capsule thermometer is put into practical use,
It becomes easy to non-invasively measure the core body temperature of the trunk. In addition, a device capable of measuring the core body temperature from the surface of the skin by the convection heat exchange method may be used. With this device,
The larger the diameter of the sensor, the deeper the body temperature can be measured, and it is possible to measure the body temperature at a depth of about 10 mm from the skin surface. However, in this method, the sensor needs to heat the skin, and when used for a long time like rhythm measurement, there is a risk of low-temperature burns, and care must be taken when handling.

Next, the structure of the biorhythm curve evaluation means 2 used in the present invention is shown in FIG. In the figure, reference numeral 21 is a rhythm curve input means for inputting biorhythm curve data measured based on measurement data of deep body temperature and electrocardiographic measurement data. Reference numeral 22 is a characteristic parameter input means for inputting characteristic parameters of the biorhythm curve. The characteristic parameters include, for example, the three elements of the cycle, amplitude, and phase of the biorhythm curve, the duty ratio, the spectrum, the rising / falling slope, the number of minimum values, and the number of maximum values. Reference numeral 23 is a determination means, and each input means 21,
The biorhythm curve is evaluated based on the input result of 22. The evaluation result is output by the output unit 24 to the adjustment target setting unit 32 described later. There are two types of evaluation methods, a statistical waveform analysis method and a pattern matching method.

First, the statistical waveform analysis method will be described. As a method of statistically analyzing the waveform of the biorhythm curve, (a) stability evaluation, (b) smoothness evaluation,
(C) Rising evaluation, (d) Rhythm three-element evaluation, etc. are considered. The respective contents will be described below.

(A) Stability evaluation To evaluate the stability of the biorhythm curve, the biorhythm curves may be overlapped over several cycles and the variation thereof may be calculated. For example, FIG. 10 shows the changes in the rectal temperature over a certain week, and FIG. 11 shows the changes in the rectal temperature during another week. In the example of FIG. 10, even if several days are overlapped, the difference due to the measurement date is small, but in the example of FIG. 11, the difference due to the measurement date is large. Therefore, it is possible to evaluate that the biorhythm curve in FIG. 10 is stable and the biorhythm curve in FIG. 11 is unstable. Also, if you take the variance according to the measurement date at the same time,
Quantitative evaluation of stability is possible. According to the experiments conducted by the present inventors, it can be evaluated that the biorhythm curve due to the deep body temperature (rectal temperature) can be evaluated to be stable when the variation due to the measurement date is about 0.2 ° C. at each time. There is. However, this is an example, and the evaluation criteria may differ depending on individual differences.

(B) Evaluation of smoothness In order to evaluate the smoothness of the biorhythm curve, frequency analysis is performed on the biorhythm curve, and how much high frequency component is included in the 24-hour component is calculated. Good. Then, the smaller the high-frequency component, the smoother the biorhythm curve can be evaluated. Since such an evaluation means obtains the ratio of the high frequency component to the component of the specific cycle (here, about 24 hours) as the S / N ratio, it is surely realized by using the known S / N ratio evaluation means. can do.

(C) Evaluation of rising edge To evaluate the rising edge of the biorhythm curve, the linear approximation of the rising portion of the biorhythm curve or the slope of the regression line may be obtained and the magnitude thereof may be quantitatively evaluated. In particular,
By quantitatively evaluating the slope of the rise of the biological rhythm curve after waking up, the smoothness of the transition from the sleep phase to the awakening phase can be quantitatively evaluated.
For example, FIG. 12 is a graph in which changes in rectal temperature are recorded for 72 hours, and in the figure, it can be determined that the curve with the slope A has a fast rise and a good wakefulness. Also, the slope B
In the curve of, the rising is slow and it can be evaluated that the person is awake. Similarly, the smoothness of the transition from the wakefulness phase to the sleep phase can be quantitatively evaluated by the falling slope of the biological rhythm curve before sleep.

(D) Evaluation of Three Elements of Rhythm The three elements of the biorhythm curve are period, amplitude and phase. In order to evaluate these, it is necessary to evaluate the subject's lifestyle. For example, it evaluates whether the cycle matches the cycle of social life, whether the amplitude is too small, or whether the phase matches the life pattern.

Next, the pattern matching method will be described. As a method of evaluating the biorhythm curve by the pattern matching method, (i) a method of evaluating a deviation from a template, and (ii) a method of classifying into a typical rhythm pattern and evaluating the rhythm curve are considered. The respective contents will be described below.

(I) Method for Evaluating Deviation from Template In this method, it is necessary to register a reference curve serving as a template in advance in accordance with the subject's lifestyle (working hours, etc.). For example, a biorhythm curve obtained by superimposing the deep body temperature curves on the measurement day when the subject feels comfortable is set as an ideal (desirable for the person) rhythm curve, and this rhythm curve is registered as a template. Then, the input biorhythm curve and its characteristic parameters are compared with the template, and the deviation is evaluated by the least square error or the like. The smaller this deviation is, the more the rhythm matches the person's life pattern. FIG. 13 shows an example of a deep body temperature template. In the figure, the point where the body temperature is the lowest is included during the sleep period, and the time period when the body temperature is high and the activity is high is included during the work period. In addition, if a standard curve is prepared in advance as a reference curve and this is transformed according to individual differences,
The template can be easily registered.

(Ii) Method of classifying into typical rhythm patterns and evaluating This method is particularly effective in evaluating biological rhythms during sleep. It is expected that there will be less stimulation from the outside world during sleep, and it is likely that the original function of the biological rhythm is likely to be exhibited, but when measuring rectal temperature in daily life, the same subject has the same biological rhythm curve shape. Not necessarily. It is generally considered that there is one valley in the rhythm curve during sleep as in pattern a in FIG. 14 and that it appears in the second half of the sleep phase. However, actually, the number of valleys is not limited to one, and the position thereof changes daily. In pattern b of FIG. 14, a long valley appears in the first half to the second half of the sleep phase, and in pattern c of FIG. 14, two valleys in total appear in the first half and the second half of the sleep phase. Further, in pattern d of FIG. 14, a valley appears in the first half of the sleep phase. It is considered that these patterns are determined by daytime life, activity / stress, or environmental changes such as the outside temperature. The closer the valley is to one pattern, the stronger the rhythm can be evaluated. The determination of which of the patterns a, b, c, d in FIG. 14 the input rhythm curve is close to can be reliably performed using a general pattern matching discriminant analysis method. For example, the distance can be determined by comparing the distance of the rhythm curve on the characteristic parameter plane (multidimensional) with a typical example of each pattern.

Next, FIG. 15 shows the construction of the biorhythm adjusting means 3 used in the present invention. In the figure, 31 is a rhythm curve input means for inputting the data of the biorhythm curve measured based on the measurement data of the core body temperature. The rhythm curve input means 31 extracts characteristic parameters such as the period, phase, and amplitude from the input rhythm curve and outputs them together with the rhythm curve data to the stimulus condition determination means 33, which will be described later.

Next, reference numeral 32 is an adjustment target setting means, which inputs the present life pattern and physical condition (this can use the evaluation result from the output means 24) and the desired life pattern, and compares and judges them. As a result, the characteristic parameter of the biological rhythm curve that is the adjustment target is set and output to the stimulation condition determining means 33 described later. The adjustment target setting means 2 includes (i) an input unit, (ii) a comparison unit, and (iii)
It is composed of a setting section. The configuration of each unit will be described below.

(I) Input unit The input unit inputs the current life pattern, physical condition, and desired life pattern. The current life pattern consists of personally set time information such as wake-up time, bedtime, and bathing time, and socially-determined time information such as work or class or points of life or sports. It Hereinafter, three typical input examples of the adjustment target will be described. First, as one input example, FIG.
In the pattern a, the bath time is from 0:00 to 1:00, the sleeping time is from 7:00 to 7:00, and the working time is from 9:00 to 19:00. In this current life pattern a, the current physical condition is input subjectively or objectively. For example, the physical condition such as being hard to get up in the morning and often sleepy in the daytime is input. This is output means 2
The evaluation result from 4 may be used. Next, as a desired life pattern, for example, the pattern b in FIG. 16 is input. In this pattern b, bathing time is from 23:00 to 24:00,
The sleeping hours are from 0:00 to 6:00, and each is shifted forward by one hour. The working hours from 9:00 to 19:00 are not shifted because they are times determined by social factors. With this life pattern b, it is possible to meet the demand for having an extra hour in the morning.

Further, as another input example, the work hours are the same as the pattern a in FIG. 16 and the sleeping hours are currently from 22:00 to 3:00, and the desired life pattern is from 23:00 to 6:00. An example is possible. In this input example, it is possible to deal with the improvement of the symptom of waking up early and in trouble.

Further, as another input example, both the current life pattern and the desired life pattern are the same as the pattern b in FIG. 16, but the current physical condition is that it is difficult to wake up in the morning and does not feel in the morning. It is also possible. In this example, it is necessary to determine the condition of stimulation so as to make it easier to wake up in the morning. It is assumed that the current rhythm curve is as shown in FIG. 17 for each of the above input examples. These rhythm curves are input from the rhythm curve input means 31 to the adjustment target setting means 32.

(Ii) Comparing Unit The comparing unit compares the input current life pattern, current physical condition, desired life pattern, and current rhythm curve, and performs case classification according to the comparison result. . For example, as shown in FIG. 18, the difference between the current pattern and the desired pattern is calculated for the sleep time period. In addition, the difference between the current lowest rhythm and the desired wake-up time is calculated. Then, according to each calculation result, the following cases are classified.
For example, the desired sleep time zone is earlier than the current sleep time zone, and the lowest point of the rhythm curve is 1 to 2 of the desired wake-up time.
If it is later than the time before, it is determined to correspond to the above input example (biotic clock recession). Further, when the desired sleep time period is later than the current sleep time period and the lowest point of the rhythm curve is earlier than 1 to 2 hours before the desired wake-up time, the above input example (biological clock advance disease) It is determined to correspond to. In the cases other than the above two cases, the amplitude of the rhythm is judged and it is judged that it corresponds to the above input example (biological clock inactivity).

(Iii) Setting Unit The setting unit sets the adjustment target based on the judgment result of the comparison unit. For example, when it is determined that the adjustment example corresponds to the input example, the adjustment target is set so as to advance the phase of the rhythm. In this case, the minimum phase of the rhythm curve is 7
Since the desired wake-up time is 6:00, the phase advance of 2 to 3 hours is set as the adjustment target. If it is determined that the input example corresponds to the input example, the adjustment target is set so that the phase of the rhythm moves backward. In this case, since the minimum value phase of the rhythm curve is 2:00 and the desired wake-up time is 6:00, the phase retreat of 2 to 3 hours is set as the adjustment target. Furthermore, when it is determined that the input example is satisfied, the rhythm amplitude is set as the adjustment target. In this case, since the minimum phase of the rhythm curve is 4:00 and the desired wake-up time is 6:00, it is not necessary to change the phase. However, since the physical condition is poor, it is determined that the rhythm amplitude is small, and therefore the adjustment target is to increase the rhythm amplitude.

Next, the stimulation condition determining means 33 shown in FIG. 15 will be described. Here, conventionally, C.I. A. Czeisl
er and R.E. E. Kronauer or M.K. E. Je
The timing of stimulation is determined by effectively utilizing the phase response curve to light stimulation by the study of wett et al. According to their research, when adjusting the phase of a biological rhythm curve,
It has been found that it is effective to give a light stimulus within a range of ± 3 hours of the minimum phase of the rhythm curve. Also,
When increasing the amplitude of the rhythm curve, it has been found effective to apply a light stimulus near the maximum value of the rhythm curve.

For example, when it is determined that the input example corresponds to the above, the subject is exposed to strong light at a timing of 4 hours after the phase of the minimum value of the rhythm curve. And
Gradually accelerate the time of exposure. For example, initially 9
The light is applied around 10 o'clock and finally around 6-8 o'clock. This makes it possible to give a stimulus that makes the transition from the sleep phase to the awakening phase smooth.

Further, when it is judged that the input example corresponds to the above, the phase of the minimum value of the rhythm curve is 4-5.
The subject is exposed to a strong light before going to bed at the timing until the hour. For example, light irradiation around 22:00 is effective. Then, if you wake up at the appropriate time in the morning, no further stimulation is necessary.

If it is determined that the input example corresponds to the above-mentioned input example, the subject is illuminated with strong light around noon. Alternatively, the subject is instructed to exercise during the daytime. In other words, it gives a stimulus that makes the transition from the sleep phase to the awakening phase smooth.

Next, the environment information input means 35 shown in FIG. 15 will be described. The environment information input means 35 inputs the amount of received light, the temperature, the amount of activity, etc. as information on the environment that is a stimulus. Here, the information on the amount of received light is obtained as an integrated value of the illuminance on the front surface of the human body, the air temperature is obtained as the temperature change around the human body for one day, and the amount of activity is obtained as the amount of movement of the body. The environment information input means 35 inputs these pieces of information and determines whether or not the stimulus amount is sufficient as a rhythm synchronization factor. If it is not sufficient, the stimulation condition determination means 33 is instructed to increase the stimulation amount.

Next, the stimulating means 34 shown in FIG. 15 will be described. The stimulating means 34 is configured so that the subject receives an appropriate stimulus while performing daily life. For example, when it is determined that the input example corresponds to the above example, the light alarm and the high illuminance light are used together. About 30 minutes before waking up, the light alarm gradually raises the illuminance of the pillow and the illuminance of the bedroom.
This helps to set up the morning rhythm curve. In addition, the high illuminance light can be implemented by raising the illuminance of the light alarm to several thousand lux immediately after getting up or by setting the lighting of the washbasin, dining room, morning office, school, etc. to be very bright. It is also effective to give instructions to take a hot shower in the morning. Such thermal stimulus also has the effect of helping the rise of the morning rhythm curve.

If it is determined that the input example corresponds to the above input example, the illumination control is performed so as to increase the illuminance of the bedroom or the reading stand before going to bed. As a result, the living body feels that the night has come late, and the phase of the minimum value of the rhythm curve is delayed.

If it is judged that the input example is equivalent to the above input example, the rise of the morning rhythm is assisted by the light alarm or the hot shower in the morning. Further, the light control and the air conditioning are linked with the life pattern, and the morning light, the daylight, the light after the evening, the air conditioning, etc. are controlled under the condition close to one day of nature. In addition, the artificial sun in the underground shopping area, the light of the night shift work at the shift work, or the like can be used as the stimulus of the stimulating means 34.

[0046]

With the biorhythm adjusting device of the present invention, the biorhythm curve of the subject is measured, the measured biorhythm curve is evaluated, and the biorhythm is stimulated according to the evaluation result. Since the adjustment is made, it is possible to adjust the biorhythm corresponding to the condition of the subject.

[Brief description of drawings]

FIG. 1 is a block diagram showing an overall configuration of the present invention.

FIG. 2 is a block diagram showing a detailed configuration of measuring means used in the present invention.

FIG. 3 is a diagram showing an example of long-term measurement of rectal temperature according to the present invention.

FIG. 4 is a block diagram showing a detailed configuration of a correction means used in an embodiment of the present invention.

FIG. 5 is a waveform diagram showing an output waveform of the correction means according to the present invention.

FIG. 6 is a waveform diagram of a first reference curve used in the present invention.

FIG. 7 is a waveform diagram of a second reference curve used in the present invention.

FIG. 8 is a perspective view showing the external appearance of an eardrum temperature sensor used in another embodiment of the present invention.

FIG. 9 is a block diagram showing a configuration of an evaluation means used in the present invention.

FIG. 10 is a diagram showing changes in rectal temperature for one week.

FIG. 11 is a diagram showing changes in rectal temperature for another week.

FIG. 12 is a diagram for explaining the rise of rectal temperature.

FIG. 13 is a waveform diagram showing a reference curve used in the present invention.

FIG. 14 is a diagram showing a plurality of patterns of a body temperature fluctuation curve during sleep.

FIG. 15 is a block diagram showing a configuration of adjusting means used in the present invention.

FIG. 16 is a diagram showing an input example of adjustment target setting means used in the present invention.

FIG. 17 is a waveform diagram showing an input example of the rhythm curve input means used in the present invention.

FIG. 18 is a block diagram showing a configuration of a comparison unit of the adjustment target setting means used in the present invention.

[Explanation of symbols]

1 Biorhythm curve measurement means 2 Biorhythm curve evaluation means 3 biorhythm adjustment means

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Claims (2)

[Claims] 1. A biorhythm curve measuring means for measuring a biorhythm curve, a biorhythm curve evaluating means for evaluating the measured biorhythm curve, and a biostimulation according to the evaluation result of the biorhythm curve. And a biorhythm adjusting means for adjusting the biorhythm by applying the biorhythm adjustment device. 2. The biological rhythm adjustment device according to claim 1, wherein the stimulus applied to the living body includes at least an optical stimulus.