JP3293213B2 - Biological rhythm curve measuring device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a biological rhythm curve measuring device for measuring a biological rhythm curve from a measured value of a human electrocardiogram, and more particularly to a biological rhythm (circadian rhythm) having a period of about one day. Is used for the purpose of measuring in daily life.

[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 referred to as biological rhythms. Biological rhythms are divided into several types according to their cycles, from as long as one year to as short as several seconds. Humans have increased alertness during the light period and become more active, and have decreased alertness during the dark period and enter rest. This is due to the circadian rhythm (Circadian rhyth).
m: Biological rhythm clocked by a biological clock called a rhythm with a cycle of about one day
It is one of.

[0003] Among biological rhythms, the one most closely related to human life is the circadian rhythm having a cycle of about one day. Typical circadian rhythms of humans include body temperature fluctuations, sleep / wake cycles, and hormone secretion fluctuations. In addition, physiological phenomena associated with human life, ranging from physical and mental activities, work and motor skills, sensitivity to drugs, and autonomic functions, may be considered to indicate circadian fluctuations.

At present, the theory that the human circadian rhythm may be divided into two groups of oscillators, a group centered on the core body temperature rhythm and a group centered on the sleep-wake cycle, is prevailing at present. It is said that the core temperature rhythm is affected by the light-dark cycle, and that the sleep-wake cycle is affected by social synchronizing factors.
At the laboratory level, there are quite advanced technologies such as polygraphs to monitor arousal and biological rhythms, but they do not hurt the subject in everyday work situations,
At present, it is not possible to monitor the activity of the living body non-invasively without any hindrance to the work behavior.

[0005] Among these, the rhythm of core body temperature has little influence from the outside, shows a clear circadian rhythm, its relation to other rhythms is quite clear, and continuous measurement is possible. , Is the most important indicator of human circadian rhythm. Candidates for deep body temperature measurement include rectal temperature, eardrum temperature (may be the temperature at the back of the ear canal wall), esophageal temperature, deep subcutaneous temperature, urine temperature, etc. The filling is rectal temperature. However, it is a drawback that all of these methods are painful to the subject.

A general method for measuring rectal temperature is a method in which a probe having a thermistor embedded at the tip thereof is inserted at least 10 cm from the anus, and fixed with tape so that the probe does not come off. A device that calculates the temperature from the resistance value of the thermistor and stores it in a memory is commercially available as a portable thermometer. In addition to a method of directly measuring rectal temperature, a device (core temp) capable of measuring core body temperature from the surface of skin by a convection heat exchange method is commercially available. The larger the diameter of the sensor, the deeper the body temperature can be measured, about 10m from the skin surface
It is possible to measure the body temperature at m depth. However, in this method, the skin needs to be heated by the sensor unit, and there is a risk of low-temperature burns when using for a long time, such as in rhythm measurement, and care must be taken when handling.

As described above, the measurement of the core body temperature tends to be invasive to the subject, and in order to measure the biological rhythm without causing pain to the subject in daily life, measurement other than the core body temperature is required. It is necessary to pay attention to the items. Then, for example, Japanese Patent Application Laid-Open No. 1-29705
No. 3 discloses a technique for estimating the lowest point of the body temperature rhythm from the lowest point of the trend curve of the heart rate during sleep. In addition, Japanese Patent Application No. 3-153444 discloses a biological rhythm curve measuring apparatus including a means for extracting a circadian fluctuation component from a biological signal other than core body temperature and a means for correcting the influence of disturbance on the extracted component. Has been proposed.

[0008]

Problems to be Solved by the Invention
In the prior art disclosed in Japanese Patent Publication No. 3 (1993), since the trend of the heart rate during sleep is observed, there is a problem that only the rhythm curve during sleep can be estimated. Further, the conventional method of deriving a trend curve has a problem that the accuracy of rhythm curve estimation is insufficient. Next, in the method proposed in Japanese Patent Application No. 3-153444, the means for extracting the circadian fluctuation component from the biological signal other than the core body temperature and the means for correcting the influence of disturbance are insufficient.

The present invention has been made in view of the above points, and it is an object of the present invention to provide a subject with no pain in a daily work scene and without hindering the work behavior. It is an object of the present invention to provide a biological rhythm curve measuring device capable of non-invasively measuring the rhythm of a living body.

[0010]

According to the biological rhythm curve measuring device of the present invention, as shown in FIG. 1, a main sensor for measuring a heart rate of a living body is provided to solve the above-mentioned problems. Unit 2, a sub-sensor unit 3 for disturbance measurement, a timer means 4 for determining a measurement timing by each sensor unit 2, 3, and a unit for storing measurement results by each sensor unit 2, 3 in time series. Storage means 5, circadian component extraction means 10 for extracting a circadian variation component having a cycle of about one day from the measurement time series of the main sensor unit 2, and at least a main sensor unit for the extracted circadian variation component. A correction means 6 for correcting the influence of disturbance based on one or more of the measurement results of the second sensor unit 2 or the sub sensor unit 3, and a rhythm curve output means for outputting a rhythm curve of the corrected body temperature. It is those composed of 8.
It is preferable that the measurement items of the sub sensor unit 3 include at least one of an outside temperature, an illuminance, a physical activity, and a body posture state.

Here, the circadian component extraction means 10
Is a section length for setting the length of the peripheral time series data section used when calculating a value representing the circadian component for each unit time of the measurement result time series of the main sensor unit 2 as shown in FIG. Setting means 11, data dividing means 12 for allocating a peripheral time series section which is a circadian component expression value calculation range for each unit time, and calculating a minimum value of the heart rate from the time series data of the allocated peripheral time series section. I
Collects some data from the minimum and calculates their average.
Mel preferably comprises a section data level representative value calculating unit 13 for calculating a value representing the circadian component as the section data level representative value by. Further, as shown in FIG. 8, the correcting means 6 determines a disturbance appearance section from at least one or more measurement results of the sub-sensor section 3 or the main sensor section 2, and determines a biological appearance section in the disturbance appearance section.
Effect of the disturbance on the section including the reaction delay time
Disturbance influence judging means 65 for judging as a fluctuation section to receive
And a disturbance influence correction unit 62 that deletes, supplements, or corrects the circadian component extracted from the data of the main sensor unit 2 according to the output result of the disturbance influence determination unit 65. Here, the disturbance influence correction means 62
It is affected by the disturbance determined by the disturbance influence determination means 65.
If the fluctuation section is short enough to complement the previous and subsequent data,
In the case, the circulator extracted from the data of the main sensor
Eliminate fluctuation sections affected by disturbance among the diane components
After that, interpolation is performed from the data before and after
The fluctuation section affected by the disturbance determined by the step 65 is
If it cannot be complemented after being deleted for a long time,
Fluctuation affected by the disturbance determined by the determination means 65
Of the sections that are determined to be particularly affected by disturbance,
It is preferable to lower the whole after deleting and complementing
No. As shown in FIG. 1, it is preferable to further include an estimating means 7 for estimating a true rhythm curve from the corrected circadian component, and a characteristic parameter output means 9 for outputting characteristic parameters of the rhythm curve.

[0012]

According to the present invention, the living body is controlled by the main sensor unit 2.
The sub sensor 3 measures the outside temperature, illuminance,
Measures disturbances such as physical activity and body posture. The timing of measurement by each of the sensor units 2 and 3 is determined by timer means 4.
The measurement data is stored in the storage unit 5 in time series. Based on the stored measurement result,
The circadian component extraction means 10 including the section length setting means 11, the data classification means 12, and the section data level representative value calculation means 13 from the electrocardiogram measurement data, the time series of the peripheral time series section assigned for each unit time Calculating the value representing the circadian component as the representative value of the section data level by obtaining the minimum value of the heart rate from the data or collecting some data from the minimum and calculating the average value thereof, about 1 day as a unit The circadian fluctuation component to be extracted. Next, based on the disturbance measurement data, the correcting section 6 including the disturbance influence determining section 65 and the disturbance influence correcting section 62 determines an appearance section of the disturbance, and sets a response delay time to the disturbance of the living body in the disturbance appearance section. After determining the added section as a fluctuation section affected by disturbance, the circadian component data extracted from the electrocardiogram measurement data is deleted or supplemented or corrected according to the result, and the influence of disturbance is removed, and the rhythm curve is removed. Output means 8
Output a rhythm curve of body temperature.

[0013]

FIG. 1 is a block diagram showing an embodiment of the present invention. In this embodiment, a main sensor unit 2 and a sub sensor unit 3 are provided as the detection unit 1. The main sensor unit 2
It is for electrocardiogram measurement, and its main measurement item is ECG (electrocardiogram). At present, it is difficult to measure an ECG in daily life because an electrode must be attached to the subject's chest in order to measure the ECG, but it is difficult to measure the rectal temperature by inserting a probe at least 10 cm from the anus. By comparison, it does not cause any pain or shame to the subject, and the degree of invasion of the subject is greatly reduced as compared to the measurement of rectal temperature. Instead of obtaining complete ECG waveform data, heart rate, ECG RR interval (using the reciprocal of the average value per unit time), pulse wave (using pulse rate), autonomic nervous activity It is possible to extract the circadian fluctuation component as described below by only obtaining partial data such as (calculated from the fluctuation of the R-R interval per unit time). You may comprise so that electrocardiogram measurement data may be acquired by a pulsimeter or a wristwatch type heart rate monitor. Next, the sub sensor unit 3 is for disturbance measurement, and the main measurement items are the outside air temperature and illuminance, the degree of physical activity, and the posture state. The timing of the electrocardiographic measurement and the disturbance measurement by the detecting means 1 is determined by the timer means 4. By allowing the timer time of the timer means 4 to be set arbitrarily, variable sampling can be performed. As a result, in areas where rhythm fluctuations are large,
The sampling period can be shortened, and the sampling period can be lengthened in a portion where the rhythm variation is small, so that measurement data can be efficiently collected.

The measurement data of the main sensor section 2 and the sub sensor section 3 of the detecting means 1 are stored in the storage means 5 in time series. The measurement interval by the timer means 4 is 1 minute to 5 minutes.
Although it is preferable to set the range to minutes, the measurement interval is, for example, 1
Set to be as short as a minute, and adjacent multiple (for example, 5)
May be calculated, and the average value may be stored in chronological order.

Next, the circadian component extraction means 10 extracts a circadian variation component from the measurement data time series of the electrocardiographic information by the main sensor unit 2 among the measurement data stored in the storage means 5 in time series. Next, the correction means 6 removes the measurement noise from the extracted circadian fluctuation component, corrects the influence of the disturbance element based on the disturbance measurement data by the sub-sensor unit 3, and further, removes the high-frequency noise by a low-pass filter. Is removed to obtain a biological rhythm curve. The estimating means 7 includes a curve fitting means using a periodic function curve approximating a biological rhythm, a means for estimating a valley or a peak of the rhythm curve from a series of points before and after.

The rhythm curve output means 8 is a means for displaying a rhythm curve waveform, and is constituted by, for example, an LCD display having a graphic function. The feature parameter output means 9 calculates and outputs the feature of the biological rhythm curve. Here, other characteristics of the rhythm curve include, for example, a duty ratio, a spectrum, a rising slope, the number of local maxima, and the number of local minima.

Next, the detailed configuration of the detecting means 1 will be described with reference to FIG. In the figure, reference numeral 22 denotes a device for measuring electrocardiographic information (heart rate, RR interval, etc.).
For example, electrocardiographic information such as a heart rate and an R-R interval is measured in accordance with the output of. The measurement data is data logger 5
1 is stored. The data logger 51 is storage means for storing various measurement data in time series. 31
Reference numeral denotes an acceleration sensor which has a configuration such as a pedometer and is attached to the wrist of the subject to detect the acceleration of the wrist. Reference numeral 32 denotes an activity meter which detects the activity of the body based on the acceleration of the wrist. 31 may be worn not only on the wrist but also on the abdomen like a pedometer, in which case 32 will detect the activity of the whole body. The measurement data is stored in the data logger 51 as the number of zero crossings of the acceleration output per unit time or the integrated value of the acceleration output. Numeral 33 denotes a light receiving sensor, which changes the amount of electric current in accordance with the amount of received light. Reference numeral 34 denotes an illuminometer, which measures the ambient illuminance based on the output of the light receiving sensor 33. The measurement data is stored in the data logger 51. Reference numeral 35 denotes a thermistor outside temperature sensor for measuring the ambient temperature. The measurement data is also stored in the data logger 51. 36 is a piezoelectric or pressure-sensitive conductive sensor,
The amount of energization changes according to the pressing force. Reference numeral 37 denotes a posture measuring device, which determines the posture of the human body, that is, whether the human body is standing or sitting and lying, based on the output of a piezoelectric or pressure-sensitive conductive sensor 36 mounted on the buttocks of the human body or the upper back of the thigh. measure. The measurement data is data logger 5
1 is stored.

FIGS. 3 and 4 show examples of long-term measurement of rectal temperature, activity (wrist movement), heart rate (beats / minute), and posture information. The activity (wrist movement) is represented by a zero cross (times / minute). Further, the posture information is represented by whether or not the user is standing. In the figure, s indicates a sleep period, and w indicates a wake period. Fig. 3 shows measurement in normal life (about 58 hours), Fig. 4
Is a measurement (about 35 hours) under conditions in which the influence of disturbance is reduced as much as possible by suppressing physical activity. Each data is sampled every minute. These data are for the same subject. Naturally, it is expected that the data of FIG. 3 is obtained in daily life, whereas the body temperature data of FIG. 4 is close to a biological rhythm curve to be estimated by the present invention. Rhythm is not measured in free run state,
Although it was not possible to remove the influence of disturbance as strictly as the nt route method, under the influence of the external synchronization factor in a 24-hour cycle, a biological rhythm curve to be estimated based on body temperature fluctuation as shown in FIG. 4 was obtained. You can think. Here, an example is disclosed in which a circadian fluctuation component is extracted from the heart rate data as shown in FIGS. 3 and 4, and the influence of disturbance is removed to estimate a biological rhythm waveform such as the body temperature fluctuation in FIG.

As is clear from comparison of the rectal temperature and the heart rate data in FIGS. 3 and 4, the general tendency of the heart rate fluctuation is very similar to that of the rectal temperature. Therefore,
If the rough fluctuation tendency can be calculated from the heart rate measurement time series, it is considered that the biological rhythm of the subject can be measured without measuring the rectal temperature. The means for realizing this function is the circadian component extraction means 10 in FIG. 1, which extracts circadian components in units of about one day by processing the heart rate measurement data. The detailed configuration is shown in FIG.

The circadian component extracting means 10 is provided in FIG.
As shown in (1), it is composed of a section length setting means 11, a data dividing means 12, and a section data level representative value calculating means 13. As shown in FIG. 3 and FIG. 4, since there is a lot of noise in a pattern that the heart rate temporarily increases, a circadian fluctuation component can be obtained by estimating a noise-free base level for each unit time. Can be calculated. To estimate such a base level, first, the section length setting means 11 sets how long the surrounding data time series should be used. The data time series range to be used is set, and the base level of the data within the range set by the section data level representative value calculating means 13 is calculated using the section as the data level representative value. It is considered that about 10 to 30 minutes is appropriate as the section length set by the section length setting means 11. The method of setting the data time series range used for the calculation by the data dividing means 12 (allocating for each unit time) is roughly classified into sections each having a certain length on both sides at each time, and setting it as a calculation range. A method of shifting the data time series and a method of dividing the entire data time series into sections of a fixed length in advance and assigning a calculation result common to the section to all times in the divided section are conceivable. further,
As a method of calculating the base level of the data of the section by the section data level representative value calculating means 13, a method of obtaining the minimum value of the data of the section is general. In this case, besides taking the only minimum value, a method of collecting some data from the minimum and taking the average value thereof is also conceivable.

FIGS. 6 and 7 show examples of output waveforms of the circadian component extracting means for the heart rate data of FIGS. 3 and 4 obtained by using such means. Although these output waveforms are affected by disturbances as in the case of the body temperature measurement waveform, they can be seen to be waveforms in which the circadian fluctuation component is emphasized when compared with the original heart rate measurement data time series.

Next, an example of estimating a biological rhythm curve by removing the influence of disturbance from these output waveforms will be disclosed. Looking at changes in rectal temperature and heart rate, the level was low during bedtime and increased during awakening, which is the same tendency during normal life and during activity suppression. Referring to FIGS. 3 and 4, in the measurement data in normal life, masking of body temperature and heart rate rhythm is observed due to the influence of daily life, and in particular, physical activity (running walking, limb exercise, etc.) and bathing The level rise is remarkable. As described above, the influence of the disturbance on the body temperature and the heart rate variability usually appears in the direction in which the level increases. In addition, there is a delay of several minutes in the response of the heart rate to events that cause elevated levels. Generally, the delay time of the heart rate response is shorter than the delay time of the rectal temperature, and the magnitude of the response is expected to be larger than the magnitude of the rectal temperature response. Based on these facts, as a means to correct the influence of disturbance, first, from the measurement data of the sub sensor or the main sensor, the section where the cause of the increase in heart rate is considered to be determined, and the heart rate response The delay time is added to the section where the heart rate is affected by the disturbance, and then the circadian fluctuation component calculated from the heart rate is deleted and the data in that section is deleted and complemented from the preceding and following circadian fluctuation component data. It is considered that the rhythm curve should be estimated by performing the following. If the section in which the heart rate is affected by the disturbance is too long to be complemented, only the fluctuation section of the steeper circadian fluctuation component data is deleted and complemented, and then the whole may be corrected downward. it is conceivable that.

Next, the detailed structure of the correction means 6 will be described with reference to FIG. First, the measured heart rate data and its circadian fluctuation component may include measurement noise in addition to the influence of disturbance. Therefore, the noise removing unit 61 compares, for example, 10
An isolated point sequence separated by a beat or more is removed as noise. This utilizes the property that the circadian fluctuation component does not change rapidly.

On the other hand, in the disturbance influence determining means 65, the disturbance measurement data by the sub sensor unit 3 or the main sensor unit 2
Based on the heart rate measurement data, the section in which the disturbance element considered to affect the heart rate circadian fluctuation component data is determined, and the section obtained by adding the heart rate response delay time to the disturbance element appearance section is determined by the disturbance element. The heart rate circadian fluctuation component is determined to be a fluctuation section. The following can be considered as an example of determining an appearance section of a disturbance element that is considered to affect the heart rate circadian fluctuation component data.

As a first example, a method is conceivable in which the output of the posture measuring device 37 is used to determine the appearance section of the disturbance element based on the posture of the human body, that is, whether the human body is standing, sitting or lying. . In this case, it is expected that the physical activity is affected when the posture of the human body is in the upright position. Therefore, the section may be determined as the disturbance element appearance section. In this scheme,
Not only the output of the attitude measuring device 37 but also the output of the illuminometer 34 and the output of the outside air temperature sensor can be used. In other words, when the ambient illuminance increases, it can be determined that the user has gone out, so that it can be determined that the section has been affected by physical activity, and it can be determined that the disturbance element has appeared even when the external temperature has rapidly increased or decreased.

As a second example, a method is considered in which the output of the activity meter 32 is used to determine a section in which the amount of physical activity is larger than a certain set value as a section in which a disturbance element appears. In this method, the output (heart rate or the like) of the electrocardiographic information measuring device 22 of the main sensor unit can be used instead of the output of the activity meter 32. Now, a section obtained by adding the heart rate response delay time to the disturbance element appearance section determined in this way is determined as a fluctuation section of the heart rate circadian fluctuation component due to the disturbance element.
What is necessary is just to set a value of several minutes to several tens of minutes (for example, 5 to 10 minutes).

Next, the disturbance influence correcting means 62 corrects the heart rate circadian fluctuation component data after passing through the noise removing means 61 based on the output result of the disturbance influence determining means 65. If the fluctuation section of the heart rate circadian fluctuation component due to the disturbance element determined by the disturbance influence determination means 65 is not so long, the circadian fluctuation component of the fluctuation section is deleted, and then interpolation is performed from the preceding and following data. The interpolation methods include straight line interpolation, higher-order curve interpolation,
A method such as spline interpolation can be employed. In addition, when it is not possible to complement the heart rate circadian fluctuation component due to the disturbance element determined by the disturbance influence determination unit 65 after deleting the fluctuation section due to a long period, the fluctuation that is determined to have a large influence of the disturbance is particularly large. A method may be employed in which only the section is deleted and complemented, and then the whole is corrected downward.

FIG. 9 shows the process of determining the fluctuation section of the heart rate circadian fluctuation component due to the disturbance element and deleting and complementing the heart rate circadian fluctuation component data as described above. 9, 11, and 13 show the heart rate data of FIG. 3, and FIGS. 10, 12, 14, and 15 show the heart rate data of FIG. 9 and 10 show the results of disturbance influence correction according to the first example. Here, the section in which the posture of the human body is standing is determined as the appearance section of the disturbance element, and the heart rate response delay time is set to 5
The variation section of the heart rate circadian variation component due to the disturbance element was calculated as the minute, and the heart rate circadian variation component data was deleted. 11 and 12 show the results of the disturbance influence correction according to the second example. Here, the activity meter 32
Using the number of zero crossings as the output of, a section exceeding 100 times per minute is determined as a disturbance element appearance section, and a heart rate response delay time of 5 minutes is used to calculate a fluctuation section of a heart rate circadian fluctuation component due to the disturbance element. Heart rate circadian fluctuation component data was deleted. FIG. 13 and FIG.
9 shows another example of the result of disturbance influence correction according to the second example. Here, the output (heart rate) of the electrocardiographic information measuring device 22 of the main sensor unit is used, and the difference between the maximum value and the minimum value of the heart rate in the section of 10 minutes before and after a certain time exceeds 30. Is determined as the appearance section of the disturbance element, and the heart rate response delay time is set to 5 minutes, the fluctuation section of the heart rate circadian fluctuation component due to the disturbance element is calculated, and the heart rate circadian fluctuation component data is deleted. Also, in FIG. 15, FIGS.
4 shows an example in which a section in which the logical sum of a section determined as a fluctuation section of the heart rate circadian fluctuation component due to a disturbance element is obtained is newly set as a fluctuation section and deletion and complementation of the heart rate circadian fluctuation component data are performed.

In any of the examples, it is considered that a result close to the waveform of the body temperature fluctuation obtained by reducing the influence of disturbance as shown in FIG. If the amplitudes of these output results are corrected downward based on the magnitude of physical activity or the like, the waveform of the heart rate circadian fluctuation component close to the body temperature fluctuation, in which the influence of disturbance is further reduced, can be estimated. It is needless to say that the constants used in these correction examples are only examples, and are not limited to these numerical values.

Next, the missing value complementing means 63 complements missing sections such as a section removed as noise and a section where measurement was impossible. As the complementing method, a method such as linear complementation, higher-order curve complementation, or spline complementation can be adopted. Finally, the low-pass filter 64 removes high-frequency noise from the measured data after the processing of disturbance influence correction and missing value complementation, and outputs a biological rhythm curve. As a result, a very smooth rhythm curve having a cycle of about one day can be obtained. In FIG. 15, the result is shown in the lowermost graph.

Next, the estimating means 7 estimates a true rhythm curve from the biological rhythm curve obtained by the correcting means 6. For example, it is conceivable to perform curve fitting to a reference curve by least squares approximation. As the reference curve, a function such as the following equation can be used as a modification of the trigonometric function. f (x) = A ｛1- (1-cos (2π (x−c) /
L)) ^2/4} where, A is the amplitude, L is the period of about 24 hours. As another reference curve, as shown in FIG. 16, a rectangular wave having a period of about 24 hours and a duty ratio of 1: 2 or a curve obtained by rounding the corner may be used. This utilizes the fact that the ratio between the bedtime and the awakening period is about 1: 2. Further, as shown in FIG. 17, a triangular wave having a period of about 24 hours or a curve obtained by taking the corner and rounding may be used. In addition, reference data created by averaging data of several cycles of an individual can be used, but it goes without saying that this differs depending on the subject.

Next, a method of estimating a true rhythm curve by a method other than the curve fitting to the reference curve will be described. For example, a method is conceivable in which a differential equation (such as a van der Pol type or Volterra type) expressing nonlinear vibration is used to obtain a coefficient of the equation that fits the measured data. 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 / falling portion of the output curve of the correction means 6 or predicting a curve between before and after relations. Model and linear AR
The MA model may be used. Further, the output of the low-frequency pass filter 64 of the correction means 6 can be used as it is as an estimation curve. In this case, in particular, when determining the lowest point of the core body temperature during sleep, the number of valleys is not limited to one, but it is sufficient to take the minimum value among the minimum values.

[0033]

According to the present invention in the biological rhythm curve apparatus of the present invention, unlike the prior art to measure the biological rhythm from the deep body temperature, raw
Since the circadian fluctuation component is extracted from the heart rate of the body to measure the biological rhythm, there is an effect that invasion to the subject is reduced. In particular, in the invention of claim 1, the circadian fluctuation component is extracted by calculating the minimum value of the heart rate of the living body or collecting some data from the minimum and calculating the average value thereof, so that the invasiveness to the subject is It has the effect of measuring a biological rhythm very similar to the recurrence tendency of the rectal temperature while having a simple configuration with little. Also, unlike the conventional technique of measuring a biological rhythm without giving a subject a disturbance, the disturbance given to the subject is measured by the sub-sensor unit, and based on the disturbance measurement data, the appearance section of the disturbance is determined, and the disturbance is determined. The circadian fluctuation component extracted from the measurement data obtained by the main sensor section is quantitatively corrected as the fluctuation section affected by the disturbance, which is the section in which the response delay time to the disturbance of the living body is added to the appearance section. In addition, the effect of the disturbance can be appropriately corrected in consideration of the response delay time of the living body to the disturbance, and thus, there is an effect that it is possible to measure the biological rhythm of the subject in daily life.

[Brief description of the drawings]

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

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

FIG. 3 is a diagram showing an example of long time measurement during normal life according to the present invention.

FIG. 4 is a diagram showing an example of a long-time measurement during activity suppression according to the present invention.

FIG. 5 is a block diagram of a circadian component extraction unit used in the present invention.

FIG. 6 is a diagram showing an example of extracting circadian fluctuation components during normal life.

FIG. 7 is a diagram illustrating an example of extracting a circadian fluctuation component during activity suppression.

FIG. 8 is a block diagram illustrating a detailed configuration of a correction unit used in the present invention.

FIG. 9 is a diagram showing a first correction example of a rhythm curve during normal life.

FIG. 10 is a diagram showing a first example of correction of a rhythm curve during activity suppression.

FIG. 11 is a diagram illustrating a second example of correcting a rhythm curve during normal life.

FIG. 12 is a diagram illustrating a second correction example of a rhythm curve when activity is suppressed.

FIG. 13 is a diagram illustrating a third example of correction of a rhythm curve during normal life.

FIG. 14 is a diagram illustrating a third example of correction of a rhythm curve during activity suppression.

FIG. 15 is a diagram illustrating a fourth correction example of the rhythm curve when the activity is suppressed.

FIG. 16 is a waveform chart of a first reference curve used in the present invention.

FIG. 17 is a waveform diagram of a second reference curve used in the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Detection means 2 Main sensor part 3 Sub sensor part 4 Timer means 5 Storage means 6 Correction means 7 Estimation means 8 Rhythm curve output means 9 Feature parameter output means 10 Circadian component extraction means

Continuation of the front page (56) References JP-A-5-3877 (JP, A) JP-A 1-297053 (JP, A) JP-A-63-242227 (JP, A) JP-A-5-3876 (JP) , A) JP-A-1-236033 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) A61B 5/00-5/0295

Claims (5)

(57) [Claims] 1. A main sensor unit for measuring a heart rate of a living body, a sub sensor unit for measuring disturbance, timer means for determining a measurement timing by each sensor unit, and a measurement result by each sensor unit. A storage means for storing in chronological order, and about 1
A circadian component extracting means for extracting a circadian variation component having a cycle of a day, and an influence of a disturbance on the extracted circadian variation component based on at least one of a measurement result of a main sensor unit or a sub-sensor unit And a rhythm curve output unit that outputs a corrected biological rhythm curve.The circadian component extraction unit expresses a circadian component for each unit time in the time series of measurement results of the main sensor unit. Section length setting means for setting the length of the peripheral time series data section used when calculating the value to be calculated, and data dividing means for allocating the peripheral time series section to be the circadian component expression value calculation range for each unit time, Find the minimum value from the time series data of the assigned peripheral time series section or from the minimum
To collect some data and calculate their average
Biorhythm curve measuring apparatus, characterized in that it comprises the section data level representative value calculating means for calculating a value representing a more circadian component as the section data level representative value. 2. The apparatus according to claim 1, wherein the correcting means determines an appearance section of the disturbance from at least one measurement result of the sub sensor section or the main sensor section, and adds a reaction delay time to the disturbance of the living body to the disturbance appearance section. And a disturbance influence correction means for deleting or supplementing or correcting the circadian component extracted from the data of the main sensor unit according to the output result of the disturbance influence judgment means. Claims characterized by
Item 2. A biological rhythm curve measuring device according to item 1 . 3. The disturbance influence correction means includes a disturbance influence determination means.
The fluctuation section affected by the disturbance determined by the step is before and after
If it is short enough to be complemented from the data from
Of the circadian components extracted from
After deleting the fluctuation section affected by the disturbance,
From the data, and it was determined by the disturbance influence determination means.
Compensation after removing the variable section affected by disturbance is long
Is not possible, it is determined by the disturbance influence determination means.
Of the fluctuation section affected by the disturbance
After deleting and complementing only the sections determined to be large,
The biological rhythm curve measuring device according to claim 2, wherein the correction is performed downward . 4. The method according to claim 1, wherein the disturbance influence determining means is provided before and after a certain time.
The difference between the maximum and minimum values of the heart rate within a certain section
The feature that distinguishes the section that exceeds it as the appearance section of the disturbance element
The biological rhythm curve measuring device according to claim 2 or 3, wherein: 5. The sub-sensor part may be a human buttocks or a large part.
A piezoelectric or pressure-sensitive conductive cell attached to the upper back of the thigh
The posture of the human body is standing or sitting or lying by the output of the sensor
At least a posture measurement device for measuring the position
The biological rhythm curve measuring device according to any one of claims 1 to 4, characterized in that: