JP2000023935A - Health management guide advising device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a health management guide advising device capable of presenting health management guide information of higher serviceability on the basis of impedance measurements. SOLUTION: After impedance is measured (S1-7), a computing process for body fat rate or the like based on only these measurements is performed (S8). Whether or not the measurements were taken under the condition of an event such as 'before breakfast' is determined (S9), and for each event condition the measurements and the computation results are stored in memory for use in correcting in-day fluctuation (S10). Whether or not the memory of the event condition needed for in-day fluctuation correcting computation is satisfied is determined (S11), and the event condition memory data needed for in-day fluctuation correcting computation are read (S12) and in-day fluctuation correcting computation process is carried out (S13). The correction and measurement results are displayed (S14, 15) and procedures are finished.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a health care guideline advice device which measures the impedance of a body and provides various guideline information useful for health care based on the measured value.

[0002]

2. Description of the Related Art Conventionally, as a health management guideline advice device of this type, as shown in FIG. 45, substantially cylindrical current applying electrodes 201 and 202 are provided on both sides of a device 200, respectively.
And grip portions 205 and 206 in which voltage measuring electrodes 203 and 204 are disposed. In this device, the grip portions 205 and 206 are gripped with both left and right hands, the crotch portions of the thumb and forefinger are brought into close contact with the current application electrodes 201 and 202, and the palm surfaces under the ring finger and the little finger are placed on the voltage measurement electrodes 203 and 204. And the electrodes 201 and 202 for current application
The impedance is measured by measuring the body resistance potential by the high frequency current applied from the electrodes by the voltage measuring electrodes 203 and 204. The body fat percentage, the body fat mass, and the like are determined by the bio-impedance method (BIA) based on the body-specific information such as height, weight, age, and gender input using the key input unit 207 and the impedance measured in this manner. He estimated health care guideline information such as lean mass, water content, and basal metabolic rate.

With such an electrode configuration, as shown in FIG. 46, a current application electrode 208 is mounted near the base of the index finger and the middle finger of the back of the hand, and a voltage measurement electrode 209 is mounted on the back of the wrist (see FIG. a)), the electrode 210 for current application is mounted on the fingertip side of the instep, and the electrode 211 for voltage measurement is mounted near the ankle of the instep (see FIG. 46 (b)). Conventional basic measurement method (FIG. 46)
(C) The impedance measurement having the same high accuracy and high reproducibility as that of (c) can be performed by a small, light and inexpensive health management guideline advice device.

[0004]

However, since the impedance value used for estimating the body fat percentage changes due to various physiological factors and environmental factors, the estimated body fat percentage value also changes. was there.

[0005] Of these factors, physiological factors are particularly affected, and daily fluctuations in impedance values due to individual lifestyles of the subject are observed.

FIG. 47 shows an example of such a general circadian variation of the bioelectrical impedance, with the horizontal axis representing the time passage of one day and the vertical axis representing the impedance.

[0007] Fig. 47 shows a general fluctuation when the person does not take a bath in one day, while Fig. 48 shows a general fluctuation when the person takes a bath at 20:00. It can be seen that it increases after that, and when a cold shower bath is used, it once increases and then decreases.

FIG. 49 shows a comparison between a change in impedance when bathing and a general change in a person with high activity (high metabolism) and a person with low activity (low metabolism). For those with high activity, the impedance quickly stabilizes after getting up, and there is little change before and after bathing. On the other hand, for people with low activity, it takes until around noon for the impedance to stabilize, and the change due to bathing is large.

FIG. 50 shows a case where the impedance fluctuates under the influence of fatigue due to work or the like. From 9:00 to 1
If the worker works until 6:00, the impedance becomes the lowest around 13:00, but this point is a state where the metabolism is increased and saturated (metabolism increase saturation point). Thereafter, impedance rises due to poor blood circulation due to fatigue. This appears, for example, as stiff shoulders.

FIG. 51 shows the daily fluctuation of impedance in a person whose body temperature rises due to eating. After breakfast, lunch, and dinner, the impedance temporarily decreased due to the rise in body temperature, and then increased.

FIG. 52 shows the daily fluctuation of the impedance when the body temperature is high due to a disease or the like in comparison with the case of normal fever. Generally, the body temperature becomes higher in the evening than in the morning, so the impedance is lower in the evening than in the morning.

FIG. 53 shows the daily fluctuation of the impedance when the body is cooled by going out in winter. The detailed time on the horizontal axis is omitted, and indoor time (25 ° C) and going out (5 °)
C). It can be seen that the body temperature decreases due to the cold outside air, and the impedance increases.

FIG. 54 shows the weekly variation of the impedance over several weeks, with the abscissa representing the unit of one day.
In this example, Saturday and Sunday are closed and work is performed from Monday to Friday. It is stable around Wednesday due to regular life, rises around Friday due to a week's fatigue, and levels off on Saturday and Sunday if it is inactive and inactive.

FIG. 55 shows the difference in the daily fluctuation of the impedance between the palms (hands) and the soles (foot).
The impedance between the palms is the same as in the above-described general case, but the impedance between the soles gradually decreases due to swelling caused by standing up from around 13:00. Generally, the rate of change in impedance between both soles is more than twice as large as between both palms.

Physiological factors that cause such circadian variations in impedance are roughly classified into the following three. Impedance change due to expansion and contraction of peripheral blood vessels. Such expansion and contraction of peripheral blood vessels can cause changes in circadian rhythm of body temperature, influence of external temperature, autonomic nervous system (activation balance of sympathetic nervous system and parasympathetic nervous system) and fatigue. Caused by poor blood circulation due to Influence due to movement of extracellular fluid (especially lymph fluid etc.): Symptoms such as swelling (edema) in the feet appear when standing for one day. Influence of blood flow distribution change due to a change from the previous posture when a predetermined measurement posture is taken. For example, a case where the posture is changed from a supine position to a standing position for measurement.

The factors among the above three factors are shown in FIG.
As shown in, the impedance between the palms has less variability in the day, so the effect can be reduced by performing impedance measurement between the palms, and the factor can be reduced by teaching the measurement posture. it can. Therefore, the influence of expansion and contraction of peripheral blood vessels is the greatest.

If there is a daily variation in impedance due to the above-described factors, it is difficult to collect a stable value when trying to manage the body fat percentage and the like on a daily basis using trend data at the time of dieting or the like. .

The present invention has been made to solve the problems of the prior art, and an object of the present invention is to provide more useful guideline information for health management based on impedance measurement values. Provided is a health management guideline advice device, in particular, to provide a health management guideline advice device capable of correcting periodic fluctuations in impedance and presenting highly useful health management guideline information, and fluctuations including periodic fluctuations. An object of the present invention is to provide highly useful health management guideline information by correcting fluctuations based on environmental temperature and body temperature that can be easily measured among the above factors.

[0019]

According to a first aspect of the present invention, there is provided an impedance measuring means for measuring the impedance of a subject's body, and calculating health management guideline information based on the measured impedance value. A health care guideline advice device comprising: a calculating means for performing the above-mentioned operation, wherein a periodic fluctuation correcting means for correcting the periodic fluctuation of the impedance is provided.

In this way, even if the impedance is measured at any point in the cycle, accurate health care guideline information in which the influence of the periodic fluctuation is corrected can be provided, and the period exceeds the period of the periodic fluctuation. Since stable values can be collected even when trend information is provided at time intervals, more accurate trends can be grasped, and highly useful health management guideline information can be provided.

In the present invention, the impedance measurement value is obtained by the impedance measurement means. However, the impedance measurement means is not provided, and the measurement value is obtained from an external device such as an external measurement means or input by the user. May be acquired.

According to a second aspect of the present invention, in the first aspect, there is provided measurement time information acquiring means for acquiring information relating to the time of impedance measurement, wherein the periodicity variation correcting means is configured to perform the correction based on the information relating to the measurement time. And a correction processing means for performing a predetermined correction process based on the selected data.

In order to correct the periodic fluctuation of the impedance, it is necessary to specify the measurement time of the impedance measurement value, and this can be obtained by the measurement time information obtaining means. By specifying the measurement time of the impedance measurement value in this way, the impedance measurement value at the time of the specific measurement can be extracted as a representative value, and correction processing such as statistical processing can be performed on the impedance measurement values at a plurality of specific measurement times. By doing so, correction can be performed.

According to a third aspect, in the first aspect, there is provided measurement time information acquisition means for acquiring information relating to the time of impedance measurement, wherein the periodicity variation correction means is provided in the same time domain within different cycles. A data holding unit that holds the measured impedance measurement value; a representative value extraction unit that extracts a representative value of the time domain from a plurality of impedance measurement values held by the data holding unit; and Data selection means for selecting a representative impedance value required for correction, and correction processing means for performing a predetermined correction process based on the selected data are provided.

In order to correct the periodic variation of the impedance, it is necessary to specify the measurement time of the impedance measurement value, which can be obtained by the measurement time information obtaining means. If the impedance measurement values measured in the same time domain within different cycles based on the measurement times specified in this way are held in the same data holding means, each measurement is separated from each other by approximately several cycles. Therefore, it is possible to accumulate the impedance measurement values under the condition that the factor of the periodic fluctuation is almost the same. Therefore,
When a representative value is extracted from the data in each data holding unit, the reliability of the representative value as basic data for correcting the periodic fluctuation is improved. That is, since the basic data that is more suited to the lifestyle of the subject can be extracted, the accuracy of the correction processing can be improved. Since the learning function is ensured by the data holding unit, the accuracy of the correction process is further improved as the data is accumulated.

The time region may have a width or a specific point, and may be an index for separately storing the measured impedance value.

Although the measured impedance value is held in each data holding means, it may be used to hold health management guideline information obtained by a predetermined calculation from the measured impedance value or to obtain the healthcare guideline information. May be stored as intermediate data.

In a fourth aspect based on the third aspect, the data holding means is distinguished by a time region using time as an index, and the impedance measurement value is determined by a predetermined condition according to the presence or absence of a specific action of the subject. In the case of a change exceeding the threshold value, a plurality of data holding units corresponding to the same time domain are provided, and the data holding units are held in different data holding units according to the presence or absence of the specific action.

The time area for distinguishing each data holding means may be defined using time as an index, for example, "9:00 to 9:59", or may be defined as "before breakfast". The action of the subject may be defined as an index.
If this time domain is defined using the subject's actions as indices, even if the impedance measurement value changes beyond a predetermined condition depending on whether or not the subject has a specific action, each impedance measurement value is Since data can be stored separately in the data holding unit when there is an action and in the data holding unit when there is no action, the reliability of data is not impaired even if a representative value is extracted by each data holding unit. However, if this time region is defined using time as an index, even if the impedance measurement value changes beyond a predetermined condition due to the presence or absence of a specific action of the subject, the impedance is held in the same data holding means in the same time region. You. If the presence or absence of this action affects the variation of the impedance measurement value, the reliability of the data is impaired when the representative value is extracted by the data holding unit. Therefore, if a plurality of data holding means corresponding to the same time domain are provided and held in different data holding means depending on the presence or absence of a specific action, the reliability of data is improved even when the representative value is extracted by the data holding means. Is not compromised.

The presence or absence of a specific action includes before and after the specific action. The data holding means may be distinguished before and after if the action is performed almost constantly, and may be distinguished depending on the presence or absence of a special action with a low frequency.

When abnormal data is stored in different data storing means, the same effect can be obtained.

According to a fifth aspect of the present invention, in the fourth aspect, there is provided an action presence / absence determining means for determining the presence / absence of the specific action.

In this way, it is possible to reliably hold the measured impedance value in an appropriate data holding unit.

Such an action presence / absence determining means may associate the presence / absence of a specific action with a predetermined time region and determine the presence / absence based on a measurement time, or may determine the presence / absence of a specific action. May be notified, and if measured at the time of the notification, it may be determined that the state is the notification. Alternatively, the user may specify the input by inputting, and determine based on the presence or absence of the input.

In a sixth aspect based on the third to fifth aspects, the data holding means holds a default value based on a predetermined periodicity variation pattern for use in a stage where there is no or little held data. It is characterized by being.

In this way, it is possible to ensure the reliability of the data when the representative value is extracted even when there is no or few stored data in the data storage means.

In a seventh aspect based on the second to sixth aspects, the correction processing means performs an averaging process on the selected data.

Various correction processes can be performed on the selected data. However, if the data is corrected by the averaging process, the process is simple and quick.

The averaging process includes processes such as simple averaging, moving average, and load averaging.

In an eighth aspect based on the first aspect, there is provided a measuring time information acquiring means for acquiring information relating to the time of impedance measurement, wherein the periodicity fluctuation correcting means is adapted to acquire the impedance based on the information relating to the measuring time. It is characterized by comprising periodic fluctuation pattern recognition means for recognizing a periodic fluctuation pattern of the measured value, and correction processing means for performing a predetermined correction process based on the recognized periodic fluctuation pattern.

In order to correct the periodic fluctuation of the impedance, it is necessary to specify the measurement time of the impedance measurement value, which can be obtained by the measurement time information obtaining means. By specifying the measurement time of the impedance measurement value in this way, it becomes possible to recognize the periodic fluctuation pattern from the impedance measurement value. Since the periodic fluctuation of the impedance can be approximately reproduced, abundant data can be taken out for correction. Accordingly, a more accurate correction process can be performed.

According to a ninth aspect, in the first aspect, there is provided measurement time information acquisition means for acquiring information relating to the time of impedance measurement, wherein the periodicity variation correction means is provided in the same time domain within different cycles. A data holding unit that holds the measured impedance measurement value; a representative value extraction unit that extracts a representative value of the time domain from a plurality of impedance measurement values held by the data holding unit; and A periodic fluctuation pattern recognizing means for recognizing a periodic fluctuation pattern of the impedance measurement value, and a correction processing means for performing a predetermined correction process based on the recognized periodic fluctuation pattern are provided.

In order to correct the periodic variation of the impedance, it is necessary to specify the measurement time of the impedance measurement value, which can be obtained by the measurement time information obtaining means. If the impedance measurement values measured in the same time domain within different cycles based on the measurement times specified in this way are held in the same data holding means, each measurement is separated from each other by approximately several cycles. Therefore, it is possible to accumulate the impedance measurement values under the condition that the factor of the periodic fluctuation is almost the same. Therefore,
When a representative value is extracted from data in each data holding unit, the reliability of the representative value as basic data for recognizing a periodic fluctuation pattern is improved. In other words, the periodicity fluctuation pattern can be recognized more in accordance with the lifestyle of the subject, so that the accuracy of the correction process is improved.
Since the learning function is ensured by the data holding unit, the accuracy of the correction process is further improved as the data is accumulated.

The time region may have a width or a specific point, and may be an index for separately storing the measured impedance values.

Although the measured impedance value is held in each data holding means, it may be used to hold health management guideline information obtained by a predetermined calculation from the measured impedance value or to obtain the healthcare guideline information. May be stored as intermediate data.

According to a tenth aspect, in the ninth aspect, the data holding means is distinguished by a time domain using time as an index, and the impedance measurement value is determined based on the presence or absence of a specific action of the subject. If it changes beyond
Provide a plurality of data holding means corresponding to the same time domain,
It is characterized in that the data is held in different data holding means depending on the presence or absence of the specific action.

If the time domain for distinguishing each data holding means is defined by using the time as an index, the same time is used even if the impedance measurement value changes beyond a predetermined condition depending on the presence or absence of a specific action of the subject. If it is an area, it is held in the same data holding means. If the presence or absence of this action affects the variation of the impedance measurement value, the reliability of the data is impaired when the representative value is extracted by the data holding unit. Therefore, if a plurality of data holding means corresponding to the same time domain are provided and held in different data holding means depending on the presence or absence of a specific action, the reliability of data is improved even when the representative value is extracted by the data holding means. Is not compromised.

The presence or absence of a specific action includes before and after the specific action. The data holding means may be distinguished before and after if the action is performed almost constantly, and may be distinguished depending on the presence or absence of a special action with a low frequency.

When abnormal data is stored in different data storage means, the same effect can be obtained.

According to an eleventh aspect, in the tenth aspect,
An act presence / absence determining means for determining the presence / absence of the specific act is provided.

In this way, the measured impedance value can be reliably held in the appropriate data holding means.

Such an action presence / absence determining means may associate the presence / absence of a specific action with a predetermined time region and determine the presence / absence based on the measurement time, or may determine the presence / absence of the specific action. May be notified, and if measured at the time of the notification, it may be determined that the state is the notification. Alternatively, the user may specify the input by inputting, and determine based on the presence or absence of the input.

In a twelfth aspect based on the ninth to eleventh aspects, the data holding means holds a default value based on a predetermined periodicity variation pattern for use in a stage where no or little data is held. It is characterized by being.

In this way, it is possible to ensure the reliability of the data when the representative value is extracted even when there is no or little data stored in the data storage means.

In a thirteenth aspect based on the eighth to twelfth aspects, the correction processing means includes a stable area extracting means for extracting a time area having a small variation based on the recognized periodic variation pattern. It is characterized by the following.

Since the impedance change state can be grasped by recognizing the periodic fluctuation pattern, if a stable region extracting means for extracting a time region with little fluctuation is provided, it is possible to specify a region where data with little fluctuation can be secured. Therefore, highly reliable data can be extracted as data for correction. Also, an appropriate representative value of the periodic fluctuation can be selected from such a stable region.

In a fourteenth aspect based on the eighth to twelfth aspects, the correction processing means includes a correction data extracting means for extracting an impedance value necessary for correction based on the recognized periodic variation pattern. And performing a predetermined correction process on the extracted impedance value.

By recognizing the periodic fluctuation pattern of the impedance, it is possible to approximately reproduce the periodic fluctuation of the impedance of the subject. Therefore, the basic data of the subject can be used as the basic data for the predetermined correction processing. Reliable data can be extracted according to lifestyle. Accordingly, highly accurate correction processing can be performed.

A fifteenth invention is characterized in that, in the eighth to the fourteenth inventions, a fluctuation pattern display means for displaying the recognized periodic fluctuation pattern is provided.

By displaying the periodic fluctuation pattern in this way, it is possible to provide useful information for the subject to be aware of the lifestyle.

In a sixteenth aspect based on the first to fifteenth aspects, the measurement time information obtaining means is time information obtaining means for obtaining time information expressed by a time at the time of impedance measurement. And

In this way, the measurement time can be objectively specified, and the processing is easy. At the time,
It includes not only hours, minutes, and seconds but also longer days, weeks, months, and years.

The time information represented by such time may be obtained by time detecting means such as a timer, or may be input by the user.

In a seventeenth aspect based on the first to fifteenth aspects, the measurement time information obtaining means is action time information obtaining means for obtaining time information expressed by an action of the subject at the time of impedance measurement. There is a feature.

In this way, the subject can easily specify the measurement time without any means for knowing the time, and the subject can easily determine the measurement time in relation to the behavior of the subject, which is likely to cause impedance change. Since the measurement time is specified, the data can be used as a unit for distinguishing data from each other, such as when the data is held in another data holding unit.

In an eighteenth aspect based on the sixteenth or seventeenth aspect, the measurement time obtaining means is expressed by time information expressed by a time at the time of impedance measurement and an action of a subject at the time of impedance measurement. Time information conversion means for converting at least one of the time information into the other time information is provided.

In this way, the measurement time information can be converted in accordance with the data processing method, so that the degree of freedom in processing is increased. In the conversion method, the user may set and input the correspondence between the action of the subject and the time in advance, or the correspondence may be extracted from the data fluctuation pattern by the recognition unit.

In a nineteenth aspect based on the first to eighteenth aspects, the periodic variation is a daily variation.

The cycle of the impedance change is determined according to the life cycle of the subject, but the physiological activity is generally repeated on a daily basis. If such a periodic change is corrected, stable and reliable health management guideline information can be obtained even when an appropriate time is selected and measured during a day.

According to a twentieth aspect, in the first to eighteenth aspects, the periodic variation is a weekly variation.

The cycle of the impedance change is determined according to the life cycle of the subject.
It is generally repeated on a weekly basis. If such a periodic change is corrected, stable and reliable health management guideline information can be obtained even when an appropriate day of the week is selected and measured.

According to a twenty-first aspect, in the first to twentieth aspects, the periodic fluctuation corrected data holding means for holding the impedance value or the health management guideline information obtained by the periodic fluctuation correcting means, And a trend recognizing means for recognizing a change of the impedance value or the health management guideline information held in the sex variation corrected data holding means in units of time intervals equal to or longer than the cycle.

In this way, it is possible to provide highly reliable trend information based on stable data in which the influence of periodic fluctuation is corrected.

According to a twenty-second aspect, in the first to twentieth aspects, the periodic fluctuation corrected data holding means for holding the impedance value or the health management guideline information obtained by the periodic fluctuation correcting means, And a trend recognizing means for recognizing a change in the impedance value or the health management guideline information held in the sex variation corrected data holding means at different time intervals equal to or longer than the cycle.

In this way, trends at different time intervals, such as short-term, medium-term, and long-term, can be provided collectively, instead of trends at fixed time intervals. More diverse information can be provided.

According to a twenty-third aspect, in the twenty-second or twenty-third aspect, there is provided a trend display means for displaying the recognized trend.

In this way, the user can directly and easily obtain the trend information.

A twenty-fourth aspect of the present invention is a health care guideline advice device, comprising: impedance measurement means for measuring the impedance of a subject's body; and arithmetic means for calculating health care guide information based on the measured impedance value. Environmental temperature measuring means for measuring the environmental temperature of the device; and environmental temperature influence correcting means for correcting the influence of the environmental temperature on the impedance measured value based on the environmental temperature measured value measured by the environmental temperature measuring means. Features.

In this way, it is possible to correct the influence of the environmental temperature which exerts a physiological influence on the subject and causes a change in impedance, so that it is possible to provide more accurate health care guide information. it can.

The correction of the influence of the environmental temperature may be performed on the measured impedance value, may be performed on the health management guide information obtained by a predetermined calculation from the measured impedance value, or may be performed on the health management guide information. It may be performed on intermediate data to obtain.

According to a twenty-fifth aspect, in the twenty-fourth aspect,
An environment determining means is provided for determining whether or not the environment is suitable for impedance measurement based on the environmental temperature measured by the environmental temperature measuring means.

In this way, measurement can be performed only in an environment where highly accurate health management guideline information can be provided, and there is no possibility of providing low-accuracy information.

In a twenty-sixth aspect based on the twenty-fifth aspect, the environmental temperature influence correcting means performs a correction process based on the measured environmental temperature when the environment determining means determines that the environment is not suitable for impedance measurement. It is characterized by the following.

In this way, even when measurement is performed in an environment that is not suitable for impedance measurement, correction processing is performed, so that highly accurate information can be provided.

A twenty-seventh aspect of the present invention provides a health care guideline advice device comprising: impedance measurement means for measuring the impedance of a subject's body; and arithmetic means for calculating health care guideline information based on the measured impedance value. It is characterized by comprising a body temperature measuring means for measuring the body temperature of the subject, and a body temperature influence correcting means for correcting the influence of the body temperature on the impedance based on the measured body temperature measured by the body temperature measuring means.

In this way, it is possible to correct the influence of body temperature, which is a cause of impedance fluctuation, and to provide more accurate health care guide information.

The correction of the influence of the body temperature may be performed on the measured impedance value, may be performed on the health management guide information obtained by a predetermined calculation from the measured impedance value, or may be obtained on the health management guide information. May be performed on intermediate data.

The twenty-eighth invention is the twenty-seventh invention, wherein
The body temperature measuring means is provided at a portion that comes into contact with the subject's skin at the time of impedance measurement.

In this way, since the body temperature at the time of impedance measurement can be measured, the body temperature at an appropriate point in time can be easily measured as data for correcting the impedance.

A twenty-ninth aspect of the present invention is based on the twenty-eighth aspect,
The part which comes into contact with the subject's skin is an electrode constituting the impedance measuring means.

Since the electrode is generally made of metal and has high thermal conductivity, if the electrode is provided with a body temperature measuring means, the electrode can be used as a heat collecting member and the structure of the body temperature measuring means can be simplified. it can.

[0092] In a thirtieth aspect based on the twenty-seventh to twenty-ninth aspects, a state determination is performed to determine whether or not the subject is in a state suitable for impedance measurement based on the body temperature measurement value measured by the body temperature measurement means. Means are provided.

In this way, measurement can be performed only in an environment where highly accurate health management guideline information can be provided, and there is no possibility of providing low-accuracy information.

A thirty-first aspect is the invention according to the thirtieth invention, wherein
The body temperature influence correction unit performs a correction process based on a measured body temperature when the state determination unit determines that the subject is not in a state suitable for impedance measurement.

In this way, even when measurement is performed at a body temperature that is not suitable for impedance measurement, correction processing is performed, so that highly accurate information can be provided.

[0096] A thirty-second invention provides a healthcare guideline advice device comprising: impedance measurement means for measuring the impedance of a subject's body; and arithmetic means for calculating healthcare guideline information based on the measured impedance value. A common temperature measurement unit capable of measuring both the environmental temperature of the apparatus and the body temperature of the subject; and an effect on impedance based on at least one of the environmental temperature measurement value and the body temperature measurement value measured by the temperature measurement unit. And a temperature influence correcting means for correcting

In this way, it is possible to correct the influence of at least one of the environmental temperature and the body temperature, which is a factor of the impedance variation, so that it is possible to provide more accurate health care guide information. Further, since the temperature can be measured by the common temperature measuring means, there is no need to provide a separate measuring means, and the number of components can be reduced.

The correction of the influence of the environmental temperature or the body temperature may be performed on the measured impedance value, may be performed on the health management guide information obtained by a predetermined calculation from the measured impedance value, or may be performed on the health management guideline. It may be performed on intermediate data for obtaining information.

[0099] A thirty-third invention is a method according to the thirty-second invention, wherein
An object identification unit is provided for identifying whether the measurement target of the temperature measurement unit is an environmental temperature or a body temperature.

In this way, since the temperature measurement value measured by the common temperature measurement means is identified, correction processing can be performed according to the object, and more accurate health care guide information can be provided. .

A thirty-fourth aspect is the invention according to the thirty-third aspect, wherein
Environmental temperature value extracting means for extracting an environmental temperature value for correction from a temperature measurement value identified as an environmental temperature measurement value by the object identification means; and a body temperature measurement value identified by the object identification means. A body temperature value extracting means for extracting a body temperature value for correction from the temperature measurement value, an environment suitable for impedance measurement based on the environmental temperature value and the body temperature value, and an environment for determining whether or not the subject is in a state. State determination means, wherein the temperature influence correction means, when the environment and state determination means determined that the environment and state are not suitable for impedance measurement, at least one of the environmental temperature value or body temperature value Is characterized in that a correction process based on is performed.

In this way, even if the environment and state are not suitable for impedance measurement, the correction processing is performed, so that highly accurate health care guideline information can be provided.

The thirty-fifth invention is the thirty-fourth invention, wherein
The temperature correction unit includes: an environment temperature value holding unit that holds an impedance measurement value at the environment temperature value for each environment temperature value in a predetermined range; and a plurality of impedance measurement values held by the environment temperature value holding unit. Environmental temperature representative value extracting means for extracting a representative value of, an environmental temperature fluctuation pattern recognizing means for recognizing a fluctuation pattern of an impedance measurement value with respect to the environmental temperature value, and a predetermined correction based on the recognized fluctuation pattern. Environmental temperature correction processing means for performing processing, a body temperature value holding means for holding an impedance measurement value at the body temperature value for each body temperature value in a predetermined range, and a plurality of impedance measurement values held by the body temperature value holding means. Means for extracting a representative value of body temperature for extracting a representative value of a range; A pair temperature variation pattern recognition means for recognizing a down, characterized in that a pair temperature correction processing means for performing a predetermined correction process on the basis of the recognized variation pattern.

As described above, the environmental temperature value holding means for holding the impedance measured value at the environmental temperature value for each predetermined range of the environmental temperature value, and the body temperature for holding the impedance measured value at the relevant body temperature value for each predetermined temperature range of the body temperature value Basic value for recognizing a variation pattern for each of the environmental temperature value and the body temperature value when extracting a representative value from data stored in each of the environmental temperature value holding means and each of the body temperature value holding means. The reliability of the representative value is improved, and the accuracy of the correction process is also improved. Since the learning function is ensured by the data holding unit, the accuracy of the correction process is further improved as the data is accumulated.

In a thirty-sixth aspect based on the thirty-third to thirty-fifth aspects, there is provided a state estimating means for estimating the state of the subject based on the temperature measurement value identified by the object identification means. It is characterized by the following.

The body temperature not only causes impedance fluctuation, but also fluctuates due to abnormal physical condition or fluctuates with specific actions such as bathing. It can be used to estimate the condition of the examiner. Therefore, the measured value of the body temperature can be used for providing more various information.

[0107]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS (First Embodiment) FIG. 1 shows a health management guideline advice device 1 according to a first embodiment of the present invention.
Is shown.

The device 1 mainly comprises a main unit 2, a foot electrode unit 3, and a cable 4 for connecting between the main unit 2 and the foot electrode unit 3.

The main unit 2 mainly straddles the main body 5 having a substantially rectangular parallelepiped shape, grips 6 and 7 having substantially columnar shapes provided in parallel on both right and left sides thereof, and the main body 5 and the grips 6 and 7. It comprises bridge portions 8 and 9.

A display unit 10 as a display means and a key input unit 11 for inputting body specific information and operation information are provided on the front surface of the main unit 5, and a power switch 12 is provided on the front surface of the bridge unit 8. Is provided.

The grip portions 6 and 7 are provided with current application electrodes 13 and 14 and voltage measurement electrodes 15 and 16, respectively.

The foot electrode section 3 is provided with a left foot positioning section 18 and a right foot positioning section 19, which form substantially the outer shape of the foot, on a substantially rectangular parallelepiped sheet material section 17. Substantially semicircular current applying electrodes 20 and 21 are provided on the finger side, and substantially semicircular voltage measuring electrodes 22 and 23 are provided on the heel side in opposite directions.
When both feet are placed along 19, the finger side of the sole is on the current application electrodes 20, 21 and the heel side is the voltage measurement electrodes 22, 23.
, Respectively. Further, a housing portion 2 is provided at a front portion (right side in FIG. 1) of the sheet material portion 17.
4 are provided. Further, a through hole 25 is formed in the front of the sheet material portion 17 between the two leg positioning portions 18 and 19. If the foot electrode unit 3 is mounted on a weight scale having a display unit in the through hole 25 and used, the two-foot positioning unit 1
The weight to be input as body-specific information is measured by placing both feet on 8, 19, and the measured value is passed through hole 25.
Can be read through. Further, if the two leg positioning portions 18 and 19 are provided apart from each other through the through hole 25 in this manner, the measurement accuracy is reduced due to the subject's thighs contacting each other at the time of measurement to change the energization path. It can also be prevented.

FIG. 2 is a sectional view taken along line AA ′ of FIG. The sheet material portion 17 is formed by bonding a top sheet 26 and a back sheet 27 with an adhesive.
The elastic sheet material 28 whose edge is sandwiched by the top sheet 26
Are exposed from the substantially elliptical opening 29. The current applying electrode 21 and the voltage measuring electrode 23 are exposed on the surface of the elastic sheet material 28. The electrodes 21 and 23 have SU
Materials such as S, Ag, and Ag-Cl are used, a silicone resin, a urethane rubber sheet or the like is used for the elastic sheet material 28, and P is used for the top sheet 26 and the back sheet 27.
VC, PET, polyester and the like are used.

In this embodiment, the current application electrodes 13, 1
4, 20, 21 and voltage measurement electrodes 15, 16, 22,
23 constitutes an impedance measuring means.

Cable 4 has connectors 30 and 31 at both ends.
And the main body device 2 and the foot electrode unit 3 are detachably connected to each other.

FIG. 3 shows a basic posture when measurement is performed using the present apparatus 1. With the upright posture, the left foot and the right foot are arranged on the left foot positioning part 18 and the right foot positioning part 19 of the foot electrode part 3, respectively, and the grip parts 6, 7 are respectively gripped by the left hand and the right hand, and the elbows are extended to extend the body. The device 2 is held at approximately shoulder level so as to face the front of the body, so that the arm and the torso are substantially at right angles. At this time, the bases of the index and middle fingers of both palms are in contact with the current applying electrodes 13 and 14, and the part between the base of the thumb and the wrist is in contact with the voltage measuring electrodes 15 and 16.

FIG. 4 is a block diagram showing a circuit configuration inside the device 1. As shown in FIG.

Reference numeral 32 denotes an electrode signal switching unit for switching the connection state of the electrodes; 33, a high-frequency signal generation unit for generating a high-frequency current having a predetermined frequency f ₀ ;
Differential amplifier which receives the resistance potential signal from 5,16,22,23, bandpass filter for cutting signal other than the frequency f ₀ is 35, a demodulation circuit for demodulating a high frequency signal components 36, 37 is an analog signal A / D converter for converting a digital signal into a digital signal, 38 is a battery, 12 is a power switch,
40 is a buzzer, 10 is a display unit, 11 is a key input unit, 41
Is an output unit for outputting measurement / computation results to an external device such as a printer, 42 is a memory (ROM) storing a measurement control program, a computation program, a conversion table for extracting health management guideline advice information, etc., 43 Is a memory (RAM) for storing body-specific information, measurement values, and the like input by the user; 44, a predetermined program is executed to perform measurement and calculation, calculate health management guideline advice information, and display it on the display unit 10. Or CPU to output to external device
It is. The switching of the electrode signal switching unit 32 is performed by an analog switch or a relay, and what kind of switching is performed is determined by a switching control signal issued from the CPU 44.

In this embodiment, the ROM, the RAM, and the CP
U44 constitutes the calculating means.

FIGS. 5 to 10 show examples of the connection state of the electrode signal switching unit. FIG. 5A shows the connection state of the electrode signal switching unit 32 when the body impedance is measured between the right palm and the sole of the right foot (measurement mode between the right hand and the right foot). FIG. 5 (b)
The conduction path in this connection state is shown by approximating the body of the subject with an equivalent circuit including a resistor and a capacitor.

At this time, the connection line Ih ₂ of the current application electrode 14 for the right hand is connected to one end of the high frequency signal generation section 33, and the connection line If ₂ of the current application electrode 21 for the right foot is connected to the high frequency signal generation section 33. Is connected to the other end. The connection line Ef ₂ connection lines Eh ₂ and right foot of the voltage measuring electrodes 23 of the voltage measuring electrodes 16 for the right hand is connected to one end and the other end of the input of the differential amplifier 34, respectively. The connection lines Ih ₁ and voltage measuring electrodes 1 of the current supply electrode 13 for the left hand
5 of connecting lines Ef ₁ connection line the If ₁ and the voltage measurement electrodes 22 of the connecting wire Eh ₁ and current supply electrode 20 for the left foot
Is OPEN without being connected to anywhere. In such a connection state, a high-frequency current is applied from the current application electrodes 14 and 21 that contact the right palm and the right sole, and a resistance potential generated between the right hand and the right sole is detected by the current.

FIG. 6A shows a case where the body impedance is measured between the left palm and the sole of the left foot (measurement mode between the left hand and the left foot).
3 shows a connection state of the electrode signal switching unit 32 of FIG. FIG. 6 (b)
Fig. 3 shows the current path in this connection state by approximating the body of the subject with an equivalent circuit composed of a resistor and a capacitor.

At this time, the connection line Ih ₁ of the current application electrode 14 for the left hand is connected to one end of the high frequency signal generation section 33, and the connection line If ₁ of the current application electrode 21 for the left foot is connected to the high frequency signal generation section 33. Is connected to the other end. The connection line Ef ₁ the connection line Eh ₁ and the voltage measuring electrodes 23 for the left foot of the voltage measurement electrodes 16 for the left hand are connected to one end and the other end of the input of the differential amplifier 34, respectively. The connection line Ih ₂ and voltage measuring electrodes 1 of the current supply electrode 13 for the right hand
Fifth connection line Eh ₂ and connecting lines Ef ₂ of the connection line the If ₂ and the voltage measurement electrodes 22 of the current supply electrode 20 for the right foot
Is OPEN without being connected to anywhere.

FIG. 7A shows a connection state of the electrode signal switching unit 32 when the body impedance is measured between the soles (both sole impedance measurement mode). FIG.
(B) shows the current path in this connection state by approximating the body of the subject with an equivalent circuit composed of a resistor and a capacitor.

At this time, the connection line If ₁ of the current application electrode 13 for the left foot is connected to one end of the high-frequency signal generation section 33, and the connection line If ₂ of the current application electrode 14 for the right foot is connected to the high-frequency signal generation section 33. Is connected to the other end. The connection lines Ef ₁ and Ef ₂ of the voltage measurement electrode 15 for the left foot and the voltage measurement electrode 16 for the right foot are connected to the input terminal of the differential amplifier 34. The connection line Eh connection line Ih ₁ and the voltage measurement electrodes 22 of the connecting line Eh ₂ and current supply electrode 20 for the left hand of the connecting line Ih ₂ and voltage measuring electrodes 23 of the current supply electrode 21 for the right hand ₁ is not connected anywhere and OPE
N.

FIG. 8A shows a case where body impedance is measured between both palms (impedance measurement mode between both palms).
3 shows a connection state of the electrode signal switching unit 32 of FIG. FIG. 8B
Fig. 5 shows the current path in this connection state by approximating the body of the subject with an equivalent circuit composed of a resistor and a capacitor.

At this time, the connection line Ih ₁ of the left-hand current application electrode 13 is connected to one end of the high-frequency signal generation section 33, and the connection line Ih ₂ of the right-hand current application electrode 14 is connected to the high-frequency signal generation section 33. Is connected to the other end. The connection lines Eh ₁ and Eh _{2 of} the left-handed voltage measuring electrode 15 and the right-handed voltage measuring electrode 16 are connected to the input terminals of the differential amplifier 34. The connection line Ef connection line the If ₁ and the voltage measurement electrodes 22 of the connecting line Ef ₂ and current supply electrode 20 for the left foot of the connecting line the If ₂ and voltage measuring electrodes 23 of the current supply electrode 21 for the right foot ₁ is not connected anywhere and OPE
N.

FIG. 9A shows a case where the body impedance is measured between the right palm and the sole of the left foot (measurement mode between the right hand and the left foot).
3 shows a connection state of the electrode signal switching unit 32 of FIG. FIG. 9B
Fig. 5 shows the current path in this connection state by approximating the body of the subject with an equivalent circuit composed of a resistor and a capacitor.

At this time, the connection line Ih ₂ of the current application electrode 14 for the right hand is connected to one end of the high frequency signal generation section 33, and the connection line If ₁ of the current application electrode 21 for the left foot is connected to the high frequency signal generation section 33. Is connected to the other end. The connection line Ef ₁ the connection line Eh ₂ and left foot of the voltage measuring electrodes 23 of the voltage measuring electrodes 16 for the right hand is connected to one end and the other end of the input of the differential amplifier 34, respectively. The connection lines Ih ₁ and voltage measuring electrodes 1 of the current supply electrode 13 for the left hand
5 of connecting lines Eh ₁ and connecting lines Ef ₂ of the connection line the If ₂ and the voltage measurement electrodes 22 of the current supply electrode 20 for the right foot
Is OPEN without being connected to anywhere.

FIG. 10 shows a connection state of the electrode signal switching section 32 when the body impedance is measured between the left palm and the sole of the right foot (measurement mode between the left hand and the right foot). FIG. 10 (b)
The conduction path in this connection state is shown by approximating the body of the subject with an equivalent circuit including a resistor and a capacitor.

At this time, the connection line Ih ₁ of the current application electrode 14 for the left hand is connected to one end of the high frequency signal generation section 33, and the connection line If ₂ of the current application electrode 21 for the right foot is connected to the high frequency signal generation section 33. Is connected to the other end. The connection line Ef ₂ the connection line Eh ₁ and the voltage measuring electrodes 23 for the right foot of the voltage measurement electrodes 16 for the left hand are connected to one end and the other end of the input of the differential amplifier 34, respectively. The connection line Ih ₂ and voltage measuring electrodes 1 of the current supply electrode 13 for the right hand
5 of connecting lines Ef ₁ connection line the If ₁ and the voltage measurement electrodes 22 of the connecting line Eh ₂ and current supply electrode 20 for the left foot
Is OPEN without being connected to anywhere.

By switching the connection state of the electrodes by the electrode signal switching unit 32, the impedance between various parts of the body can be measured. In addition, since the impedance of a specific part can be measured more accurately by using the impedance measurement value between different parts, it is possible to correct an error due to the body shape and the like.

The measuring procedure by the present apparatus 1 will be described with reference to the flowchart shown in FIG.

First, when the power switch is turned on, RA
Measurement preparation processing such as initialization of M and the like and checking of each circuit element and display element is performed (step 1). FIG. 12 shows a state where the display unit 10 is fully lit. Height, weight, age,
The gender, the body fat percentage based on the measured value, the corrected body fat percentage, the obesity degree by a lighted bar, the completion of preparation, and the display during measurement are possible.

Next, specific body information including height, weight, age, and gender is input by the key input unit 11 (step 2). Here, regarding the weight, it is desirable to represent the weight of the day by the measured value after defecation and urination before breakfast, rather than inputting the measured value at each event timing of the day.

Next, the event conditions are similarly set in the key input unit 1.
1 is selected (step 3). The event condition is the time (measurement) in the subject's daily life
It is expressed using. Here, "0 free" in the event condition selection display indicates a condition outside the event, "1" is before breakfast, "2" is before lunch, "3" is before bathing (or before dinner), ""4" indicates conditions after bathing (within about 10 minutes). The event condition may be any condition that can trigger an impedance change, and is not limited thereto. Here, the key input unit 11 constitutes a measurement time information acquisition unit (action time information acquisition unit).

It is determined whether or not all the body specifying information has been input, based on “READY” (step 4).

[0138] If No is determined in step 4, the process returns to step 2 to input unspecified body specifying information.

If the determination in Step 4 is Yes, the subject is notified by displaying the start of measurement on the display unit 10 (Step 5), and the impedance between the measurement sites is measured (Step 6). ). At this time, an impedance is measured by applying a high-frequency current through a predetermined current application electrode and detecting a body resistance potential generated by the current through a predetermined voltage measurement electrode.

FIG. 13A shows a display example of the display unit 10 in a state in which measurement preparation is completed and measurement start is notified when “0 free” is selected as an event selection condition and measurement is performed outside the event condition. It is. In FIG. 13B, data is already stored in the event selection conditions “1” to “3”, and when the measurement is performed by selecting “4” as the event selection condition, measurement preparation is completed and measurement is started. Is reported. FIG. 14 shows a display on the display unit 10 during measurement.

When the measurement is completed, the subject is notified by displaying it on the display unit 9 (step 7).

An arithmetic process for calculating health management guideline information such as body fat percentage, body fat mass, lean mass, water content, basal metabolism, etc. is performed based only on the measured values (step 8). In the arithmetic processing, an arithmetic program stored in the ROM 42 is executed, and the measured impedance value is converted into health management guideline information such as a body fat percentage using a predetermined conversion formula or a conversion table.

Next, it is determined whether or not the measurement is made under an event condition (step 9). If the determination is Yes, that is, if the measurement is performed under the event condition, the measured value and the calculation result are stored for each of the event conditions for the daily fluctuation correction, and the process proceeds to step 11 (step 10). No, that is, if the measurement is performed under conditions other than the designated event, the process proceeds to step 11.

In step 11, it is determined whether or not the event condition memory required for the daily fluctuation correction calculation is satisfied. If Yes, the memory data is read out under the event conditions necessary for the daily fluctuation correction calculation (step 12),
A daily fluctuation correction calculation process described later is performed (step 1).
3) A result display process of the daily fluctuation correction calculation process is performed (step 14), and a measurement result display process is performed (step 1).
5), end the processing. If No in step 11,
The measurement result display process of step 15 is performed. In this case, since the correction is not performed, the measurement result display process is performed using only the current measurement value. In the present embodiment, the ROM 4
2, the RAM 43 and the CPU 44 constitute data selection means and correction processing means.

FIG. 15A is a display example of a measurement result when “0 free” is selected as the event selection condition and the data of the event condition is not stored in the memory. Only the results are displayed, and the lighting of the bar indicates that the subject is in a slightly obese state.
FIG. 15B is a display example of a measurement result in a case where data of the event conditions “1” to “3” are stored and measurement is performed under the current event selection condition “4”, and is based on only actual measurement values. Both the uncorrected body fat percentage (17.6%) and the corrected body fat percentage (18.0%) are displayed. Here also, the bar indicates that it is in the standard state. FIG. 15C shows a display example of the measurement result when the data of the event conditions “1” to “3” is stored in the case where “0 free” is selected as the event selection condition. Uncorrected body fat percentage based on
0.0%) and the corrected body fat percentage (18.0%) are both displayed. Here also, the bar indicates that the subject is in a slightly obese state.

An example of the daily fluctuation correction calculation processing will be described below.

(Example 1) In the case of processing and correcting the impedance measurement value, the impedance measurement value before breakfast is Zh ₁ , the impedance measurement value after bathing is Zl, the diurnal variation corrected value is Z _men, and Z _men = ( _{a * Zh 1 + b * Zl} ) / (a + b)
The correction is performed by averaging Zh ₁ and Zl as in (a and b are integer constants, for example, a = b = 1). In general, since the impedance is highest before breakfast and lowest after bathing, it is corrected using the highest and lowest values of impedance. In this case, for example, Z _men is directly substituted into the calculation formula f (H, W, Sex, Age, Z) of the body fat percentage, and the corrected body fat percentage is calculated as% F _atmen = f (H, W, S
ex, Age, Z _men ).

[0148] (Example 2) processing the calculated value of body fat rate before breakfast when correcting by processing percent value F _at h _1, the calculated value% F _at l after bathing, the daily fluctuation corrected value % F _atmen and% F
_{atmen = (a *% F at} h 1 + b *% F at l) / (a + b)
Is calculated by As in the case of Example 1, the correction is performed using the maximum value and the minimum value of the impedance.

As described above, the correction processing may be performed by processing the measured impedance value, or may be performed on the result value obtained by performing the arithmetic processing on the measured impedance value.

(Example 3) In the case of processing and correcting the measured values before and after bathing, the impedance measured value before bathing is Zh ₂ , the impedance measured value after bathing is Zl, the value after circadian variation correction is Z _men, and Z _men = (A * Zh ₂ + b * Zl) / (a + b). Since the rate of change in impedance before and after bathing is large, correction is made using these values.
As in the case of Example 1, the calculation is performed by directly substituting Z _men into the arithmetic expression such as the body fat percentage.

(Example 4) In the case of making correction by reflecting an event condition of two values or more, the impedance measurement value before breakfast is Zh ₁ , the impedance measurement value before bathing is Zh ₂ , the impedance measurement value after bathing is Zl, this time The measured impedance value of Z is Z _X , the value after intra-day variation correction is Z _men, and Z _men = (a * Zh ₁ + b * Zh ₂
+ C * Zl + d * Z X) / (a + b + c + d) (c, d
Is an integer constant), and the correction is performed by averaging these values.

In the above-described example, the correction is performed using the impedance measurement values before and after the bathing and before and after bathing. However, the measurement time points that can be used for the correction are not limited to these. Further, the correction method is not limited to the above-described averaging process.

In the present embodiment, the display unit 10 displays both the uncorrected body fat percentage based on only the actually measured values and the corrected body fat percentage, but displays the variation range of the body fat percentage. You may be able to. FIG. 16 shows an example in which the body fat percentage based on only the actually measured values and the variation range of the body fat percentage are displayed. Since the data of the event conditions “1” to “4” have already been stored in the memory, the fluctuation width displayed here is used to set the fluctuation width display value to Δ% F _at and Δ% F _at =% F
It can be calculated by _at h _1- % F _at l. Here, the fluctuation range is calculated from the body fat percentage before breakfast when the impedance within the day becomes the highest and after bathing when the impedance becomes the lowest,
The calculation method of the fluctuation range is not limited to this. As described above, it is possible to correct the circadian variation of the bioelectrical impedance and to provide highly accurate health management guideline information such as a body fat percentage which is not affected by the circadian variation. Such information is particularly useful when performing trend management over a long period of one week or more.

The health management guideline advice device according to this embodiment can measure the impedance between the left and right palms and soles, but can measure only the impedance between predetermined parts such as between both palms. It is a matter of course that it may be something.

Further, in the present embodiment, the measurement is performed with both elbows extended while standing upright. However, the amount of change in impedance is measured by flexing and stretching the joints of the elbows, knees, etc., and the amount of muscle and the like and the amount of metabolism are improved. The present invention is also applicable to a health management guideline advice device that can be estimated with high accuracy.

(Second Embodiment) Hereinafter, a health management guideline advice device according to a second embodiment of the present invention will be described.

The health management guideline advice device according to the second embodiment has substantially the same configuration as that of the first embodiment, and the same components are denoted by the same reference numerals and description thereof is omitted.

The external configuration of the apparatus is the same as that of the first embodiment shown in FIG. FIG. 17 shows the circuit configuration.
FIG. 4 except that a reference signal (timer signal) generation unit 39 as a measurement time information acquisition unit (time / time information acquisition unit) is connected to the CPU 44 and performs control based on a signal from the reference signal generation unit 39. The description is omitted because it is the same as the first embodiment shown.

On the basis of the flowchart shown in FIG.
The procedure of the measurement process in the present embodiment will be described.

When a battery is inserted, resetting of circuit elements and the like and initialization of time are performed (step 21). At this time, processing for setting a measurement event matching time zone is also performed. The setting of the event matching time zone is, for example, 6:00 to 8:00 as the event matching time zone of “before breakfast” and “before lunch”.
10:00 to 12: 0
0, 18: 0 for the “before dinner” event
From 00:00 to 20:00, an event matching time zone of “before bathing” is set to 20:00 to 22:00, and an event matching time zone of “after bathing” is set to 20:00 to 22:00.

Next, it is determined whether or not it is the system reference timing (step 22). If Yes, the process proceeds to step 23, and if No, the process proceeds to step 24.

At step 23, it is determined whether or not it is the reference time timing (1 second or 1 minute). If Yes, the time is updated (step 25). If No, the process returns to step 22.

In step 24, the measurement power switch is set to O
N is determined. If Yes, the measurement processing shown in FIG. 11 is performed (Step 30), and the process returns to Step 22. If No, the process returns to step 22.

After performing the time update processing in step 25, it is determined whether or not the time is within the measurement event condition conforming time zone (step 26). If Yes, a matching time zone mark setting process is performed (step 27), and a matching time zone mark and time display process is performed (step 28).
Return to If No, a reset process of the matching time zone mark is performed (step 29), and the process proceeds to step 28 to perform a time display process.

FIG. 19A shows an example of display on the display unit 10, in which the time (10:32) is displayed and the event condition is indicated as "2" (before lunch) as an event condition conforming time zone mark to which this time belongs. Flashes to encourage measurement under pre-lunch event conditions. In the case where the measurement is performed in a state where the matching time zone mark is set as described above, the selection input of the event condition can be omitted. FIG.
(B) shows the display pattern at the time of full lighting, but is the same as that of the first embodiment except that the time can be displayed. In the present embodiment, the ROM 42, the RAM 43
And the CPU 44 constitute time information conversion means.

As described above, since the event matching time zone can be set according to the personal lifestyle, more accurate correction can be performed. Further, since the user is prompted to perform measurement in each time zone, the subject does not need to set event conditions at the time of measurement, and data collection in a constant time zone can be easily performed.

(Third Embodiment) Hereinafter, a health management guideline advice device according to a third embodiment of the present invention will be described.

Since the health management guideline advice device according to the third embodiment has the same configuration as that of the second embodiment except for the processing procedure, the description of the same configuration will be omitted by using the same reference numerals.

Based on the flowchart shown in FIG.
The procedure of the measurement process in the present embodiment will be described.

[0170] Except for the measurement processing shown in step 40, FIG.
8 is the same as the procedure of the second embodiment shown in FIG.

FIG. 21 shows a subroutine of the measurement process shown in step 40 of FIG.

When the power switch is turned on, measurement preparation processing such as initialization of the RAM and the like and check of each circuit element and display element is performed (step 41). At this time, a default value is initially set in the divided memory.

Next, the body specifying information including the height, weight, age, and gender is input through the key input unit 11 (step 42). At this time, the personal data is registered in the memory, and the personal No. May be used to call this value.

Next, an event condition is selected (step 43). At this time, an event may be automatically selected from the event condition time zone according to the time.

Whether or not all the body specific information has been input is determined by “READY” (step 4).
4).

If No is determined in the step 44, the process returns to the step 42 to input the unspecified body specifying information.

[0177] If the determination is Yes in step 44, the subject is notified by displaying the start of measurement on the display unit 9 or the like (step 45), and the bioimpedance ( _Zt ) between the measurement sites is measured. A measurement process is performed (step 46).

When the measurement is completed, the subject is notified to the subject by displaying it on the display unit 9 (step 47).

Next, a divided memory is selected as data holding means according to the time at the end of the measurement, and the memory storage data (Z ^* _{m n-1} ) at the time of the previous measurement is called (step 4).
8). The divided memory will be described later. * Indicates an average value, and m indicates the divided memory No. Where n is the number of data storage histories (n ≧ 2).

Next, it is determined whether or not the area is a parallel divided memory holding area by an event or the like (step 49).

If No in step 49, data abnormality is determined (step 50). In this case, | Z _t
-Z ^* _{m n-1} | ≧ 20 (Ω) and n ≧ 5 determine whether data is abnormal. If Yes, go to step 57. If No, a divided memory data update process is performed (step 51).

The division memory data updating process is performed as follows.

First, Z is calculated from the previous data and the current data.
^{_{* M n = (Z * m}} n-1 + Z t) / 2 performs moving average processing (step 51a).

Next, (Step 51b).

Next, the data after processing such as moving average and standard deviation is stored in the divided memory, and the data in the memory is updated (step 51c).

When the above-mentioned divided memory data update processing is completed, the routine proceeds to step 61.

If Yes in step 49, the main divided memory side before bathing or the like is selected (step 52), and data abnormality is determined as in step 50 (step 53).

If No in step 53, the flow advances to the divided memory data update processing in step 51. Step 53
In If Yes, the selected special division memory side, such as after bathing (step ^{_{54), | Z t -Z *}} m n-1 '| ≧ 20
(.OMEGA.) And whether or not n.gtoreq.5 is determined (step 55).

If No in step 55, the flow advances to the divided memory data update processing in step 51 in step 51.

If Yes in step 55, it is determined whether or not there is stored data (Z ^* _{m n-1} ') for the previous abnormality determination (step 56).

[0191] If No in step 56, the newly provided data abnormality determination storage split memory, a data Z _t Z ^* _m
is stored as _n '(step 57), and the process returns to step 45. If Yes in step 56, | Z _t -Z
^{_{* M n-1 '| ≦}} 10 (Ω) whether by confirming the coincidence of the data (step 58). If Yes, the storage division memory data updating process for data abnormality determination is performed (step 59). If No, the measurement result abnormality (error) and re-measurement are notified (step 60), and the process returns to step 45.

After performing the processing of step 59, all divided memory data is called, and a graph display processing of a learning recognition pattern is performed (step 61).

Next, a calculation process using the measured value measured this time is performed (step 62), and a calculation result display process is performed (step 63).

FIG. 22 is a display example of the display unit (variation pattern display means) 10 displaying the daily fluctuation pattern in a graph and displaying the body fat percentage and the body fat mass based on the current measured values. In this display example, the horizontal axis is a time zone, the day is divided into six time zones every three hours, and the time zone from 0:00 to 5:59 is omitted (here, the time zone is shown). , “6-8” indicates a time zone up to 8:59). The vertical axis is a relative display, and can take a body fat percentage or an impedance value. Naturally, the same display may be performed by dividing the horizontal axis into twelve time zones corresponding to all divided memories.

Next, the daily divided memory data is called to grasp the daily fluctuation pattern, and information necessary for calculating the daily representative value such as the maximum value, the minimum value, and the event condition value is extracted (step 64).

Next, a daily representative value calculation process and a calculation process are performed (step 65), a calculation result display process based on the daily representative value is performed (step 66), and the measurement process subroutine ends.

A method for setting a divided memory area will be described.

FIG. 23 shows memories 1 to 12 and memory 10 '.
12 to 12 'schematically show divided memory areas.

A 24-hour day is divided into, for example, two-hour units, and twelve data storage memories are provided for each measurement, and a measurement value for each measurement (if the body-specific information changes, the information Is stored together with the impedance information) and the calculation result value is automatically determined and stored in which of the twelve data storage memory areas divided in two-hour units from the time information at the time of measurement.

The time axis shown below the memories 1 to 12 arranged in order indicates the time at which the measurement to be stored in each memory area was performed. For example, memory 1 is 0:
Information such as measurement values and calculation result values measured during the time period from 00 to 1:59 is stored. The correspondence between the measurement time and the memory area may be made to correspond by events such as before and after breakfast, before and after lunch, before and after dinner, and before and after bathing. In response to such event conditions, at the time of initial setting, by setting a time zone suitable for an individual's lifestyle, it is possible to make a high-recognition judgment from a stage where data accumulation is small.

Memory areas corresponding to times from 18:00 to 23:59 are memories 10 to 12 and memories 10 'to
The reason why the double structure 12 ′ is provided twice is that this time period is before and after bathing, and the value of data greatly differs before and after bathing. This is for storing data in different memory areas, such as storing the data after bathing in the memories 10 'to 12'.

A method of determining data for sorting and storing data in a memory area before or after bathing will be described below.

If a time zone corresponding to the event conditions before and after the bathing is set, the determination is performed based on the measurement data in the time zone (18:00 to 23:59 in the above case).

[Determination Condition before Bathing] a When compared with the data stored in the divided memory in the time zone before the event condition before and after the bathing, it is determined whether or not the value is close to the equivalent value or not less than the equivalent value. Determine. For example, the determination is made based on Z ₉ + α ≧ Z ₁₀ ≧ Z ₉ −α.
Here, α: a value within 10Ω or about 20% of the actually measured value Z ₉ : data stored in the divided memory area in a time zone before the event condition before and after bathing Z ₁₀ : an event condition time zone before and after bathing (in this case, Is 18:
00 to 19:59). (b) In the case of a special case such as a cold water shower, the bioimpedance tends to be higher at the time of cold water shower than at the time of bathing, as opposed to when hot water is taken. Thus, for example, Z ₁₀
> Z ₉ + α. If it is necessary to determine a special case such as a cold water shower, another divided memory may be provided in parallel.

[Determination Condition after Bathing] It is determined whether or not the value is lower than a predetermined difference when compared with data stored in the time zone divided memory before the event condition before and after the bathing. For example, the determination is made based on Z ₉ −α> Z ₁₀ . here,
α, Z ₉ , and Z ₁₀ are the same as the determination conditions before bathing.

The measurement data is determined using such conditions and stored in the divided memory areas before or after bathing, respectively.

As described above, if the measured data is determined and stored in different divided memory areas, the reliability of the data is not impaired even when a predetermined process is performed on the data stored in each divided memory area.

The case where the time zones corresponding to the event conditions before and after bathing are set has been described. When such time zones are not considered, a plurality of divided memory areas are arranged in parallel over the entire time zone. In this case, the data may be determined in each time zone.

The method of calculating the intra-day fluctuation corrected intra-day representative value in steps 64 and 65 will be described below.

By storing data in the divided memory data,
A daily fluctuation correction pattern as shown in FIG. 24 can be obtained. In the graph of FIG. 24, time is taken on the horizontal axis, divided into time zones corresponding to the divided memory areas, and impedance is taken on the vertical axis.

The intra-day fluctuation corrected intra-day representative value Z
If _D is assumed to be calculated by the average value of the two values after bathing and before breakfast, can be calculated by ^{_{Z D = (Z * 4 n4}} + Z'* 10 n10) / 2.

When there are a plurality of values after bathing, Z _D = ｛Z ^* _{4 n4} + (Z ′ ^* _{10 n10} + Z ′ ^* _{11 n11} + Z)
^{_{'* 12 n12) / 3}}} / 2 can be calculated by.

[0213] Here, although calculated diurnal representative value Z _D with a value after bathing and before breakfast, the calculation method is not limited thereto.

[0214] In this way a representative value Z _D in the fluctuation corrected date day calculated by arithmetic processing using the arithmetic expression such as a body fat percentage, and displays the result as the operation result by the daily fluctuation corrected circadian representative value .

The processing for determining and storing abnormal data in steps 50, 53 and 55 to 58 will be described below.

In this processing, when there is a large difference between the data stored so far and the divided memory in a certain time zone, for example, a change corresponding to before and after bathing of the event condition occurs outside the bathing event condition time zone. If you do
The following processing is performed.

It is determined that the data is abnormal data, the storing process in the divided memory area is stopped, and the data is temporarily stored in the separate memory area.

[0218] Of the prescribed number of times (for example, about 5 times),
If a value corresponding to abnormal data occurs a plurality of times in the same time period, another divided memory area is secured in parallel in the same time period as before and after the bath.

If the value corresponding to the abnormal data is not reproduced after the specified number of times, the stored data is deleted.

Further, in the above-mentioned divided memory area, data relating to the circadian variation of the bioelectrical impedance is collected, statistical processing is performed, and an average circadian variation pattern is extracted. May be stored.

In this embodiment, the ROM 42 and the RAM 43
And the CPU 44 comprises a representative value extracting means, an action presence / absence determining means,
The periodic fluctuation pattern recognition unit, the correction processing unit, and the correction data extraction unit are configured.

(Fourth Embodiment) Hereinafter, a health management guideline advice device according to a fourth embodiment of the present invention will be described.

Since the third embodiment is the same as the third embodiment except for the measurement processing subroutine, only the measurement procedure will be described based on the flowchart shown in FIG.

Steps 71 to 77 are the same as those in the measurement procedure of the third embodiment shown in FIG. 21 and will not be described.

After notifying the end of the measurement in step 77,
A measurement result calculation process is performed (step 78), and a display process of the calculation result is performed (step 79).

Next, all divided memory data is called (step 80), and the reference area value (Zr
The extraction process of the small areas fluctuation (Zr _n-1 within ± 10 [Omega) from _n-1) (step 81). That is, in general, the daily fluctuation is small, the stored value of the divided memory area in the measurement time zone with high daily reproducibility is set as the reference area value, and compared with the stored value of the divided memory area in other time zones, the data within the predetermined fluctuation range is Is extracted. In the present embodiment, the ROM 42, the RAM 43, and the CPU 44 constitute a stable area extracting unit.

A process for notifying the extracted region as a time zone suitable for measurement in the lifestyle is performed (step 82). As the notification method, it may be displayed so as to be superimposed on the daily fluctuation pattern graph, or if the time is displayed at the time of non-measurement, it may be displayed that the time is appropriate.

Next, a divided memory corresponding to the time at the end of the measurement is selected, and the memory storage data (Z _m
n-1 ) is called (step 83).

[0229] Next, by _{Δ = Z m n-1 -Zr} n-1 performs a calculation process of the correction value (step 84), using the delta, performs correction processing by Z _D = Z _t -Δ ( Step 8
5).

Next, the calculation processing of the body fat percentage and the like is performed using the impedance correction result value (step 86), the calculation result display processing is performed (step 87), and the current measurement value is registered in the divided memory. Perform update processing (step 8
8), the measurement processing subroutine ends.

The above-described correction processing will be described more specifically.

In FIG. 26, shown below each divided memory area is an average daily fluctuation pattern stored as a default value (the vertical axis in FIG. 26 indicates the reference area value as the origin). ing.). In this pattern, if, 10:00 to 12:00 as a reference region, the default value Z ₆ stored in the memory area corresponding to the time zone as the reference area value.

[0233] In this case, the measurement time is 9:00, if the measurement result is Zt _1, the Zt _1, 8: 00~10:
The data is stored in the memory 5 corresponding to the time zone of 00. Then, since the impedance value based on the circadian pattern in the corresponding time zone in the memory 5 (in this case the default value) is Z _5, Z ₆ is the reference area value,
Diurnal variation correction operation, Z _D = Zt ₁ - carried out by (Z ₅ -Z _6).

In this case, the correction process is performed using the default value of the daily fluctuation pattern. However, by accumulating the measurement data, the daily fluctuation pattern according to the lifestyle of the subject can be acquired by learning. .

First, data is stored in a predetermined divided memory area corresponding to the measurement time for each measurement.

The stored data is processed in each divided memory area, and the next data is stored. The description will be made taking the m-th memory area as an example. a: the number of data stored in the memory area n b: moving average operation value _{^{Z * m n = (Z *}} m n-1 + Z m n) /
2c: The average value in the standard deviation SD _mn b may be calculated not by the moving average processing but by the simple averaging processing or the weight averaging processing. The standard deviation SD _mn in c is _{SD mn-1, Z m n} , to calculate the Z ^* _{m n-1} to the variable approximation formula _{f (SD mn-1, Z} m n, Z * m n-1) It may be.

The daily fluctuation correction can be performed using the daily fluctuation pattern based on the processed data in each divided memory area instead of the daily fluctuation pattern based on the default value.

However, when the data storage amount is insufficient, n ≧ 5 and SD <10Ω or 20% of the measured value
The processed divided memory data may be used only in the time zone satisfying the condition of degree, and the default value may be used in other time zones.

[0239] In order to perform the same processing as the daily fluctuation correction according to the default value, it is necessary to normalize with Z ^* _{m n} a reference area value Z ₆ ^*.

(Fifth Embodiment) Hereinafter, a health management guideline advice device according to a fifth embodiment of the present invention will be described.

Since the third embodiment is the same as the third embodiment except for the measurement processing subroutine, only the measurement procedure will be described based on the flowchart shown in FIG.

Steps 91 to 99 are the same as those in FIG.
The fourth embodiment is the same as the fourth embodiment shown in FIG.

After performing the calculation result display processing in step 99, the registration update processing to the intra-day divided memory is performed (step 100).

Next, a process of calculating the daily representative value is performed (step 101), a calculation process of the body fat percentage or the like is performed using the daily representative value (step 102), and a display process of the calculation result is performed (step 103). .

Next, a registration update process to the weekly divided memory area is performed (step 104). The weekly divided memory area is the same as the above-mentioned divided memory area.
It is a memory area divided into seven, tree, gold, earth and day. In the weekly divided memory area, the intra-day fluctuation corrected intra-day representative value calculated in step 101 is stored as the representative value of the day of the week. The reference area value of the day may be used as the representative value.

Next, a process of calculating a weekly representative value by an average value process or the like is performed (step 105), and a calculation process of a body fat percentage or the like based on the weekly representative value is performed (step 106), and a display process of the calculation result is performed. (Step 107). The weekly fluctuation pattern can be acquired in the same manner as the daily fluctuation pattern.

FIG. 28 is a display example of a display unit displaying a weekly variation pattern based on a weekly representative value and a daily representative value. The horizontal axis is divided into seven for each day of the week, and the vertical axis is a relative display of the body fat percentage or the impedance value based on the daily representative value.

Next, registration and update processing to the long-term trend division memory is performed (step 108), all data in the long-term trend division memory is called (step 109), long-term trend graph display processing is performed (step 110), and measurement is performed. The processing subroutine ends.

FIG. 29 shows an example of a display section displaying a long-term trend.

FIG. 29 (a) shows the representative values of the day and the current day and up to six times before. The vertical axis indicates the relative body fat percentage or impedance value. As shown in FIG. 29B, in addition to displaying the intraday representative value, the representative value may be blinked and the band from the maximum value to the minimum value may be displayed in a band shape as shown in FIG. As shown in (c), only the representative value, the maximum value, and the minimum value may be lit and displayed.

In FIG. 29D, the horizontal axis is divided into current, previous, one week ago, two weeks ago, one month ago, three months ago, and six months ago.
The time axis is compressed and displayed. The vertical axis similarly indicates the daily representative value of the body fat percentage or the impedance value. The data is stored in the memory with the measurement date and time,
Such display is possible by calling the data of the corresponding date and time. At this time, as the data at the corresponding date and time, an average value of a plurality of data within a predetermined period before and after may be displayed.

In this embodiment, the RAM 42 constitutes the data holding means for which the periodicity fluctuation has been corrected.
43 and the CPU 44 constitute trend recognition means, and the display unit 10 constitutes trend display means.

(Sixth Embodiment) FIG. 30 shows a sixth embodiment of the present invention.
11 shows a health management guideline advice device 51 according to the embodiment.

First, the schematic configuration of the device 51 will be described. The structure common to the main body device 2 of the health management guideline advice device 1 according to the first embodiment is denoted by the same reference numeral, and the description is omitted.

[0255] On both sides of the main body 5 having a substantially rectangular parallelepiped shape, grips 6 and 7 having a substantially cylindrical shape are provided.

A display unit 10 for displaying information such as measured values and health management guideline information is provided above the front surface 5a of the apparatus body 5. Below the display unit 10, a key input unit 11 including a data call switch 52, input mode setting switches 53 for switching an input mode of body specific information including height, weight, age, and gender, a numeric keypad 54, and a decision switch 55. And a power switch 56. Above the display unit 10, a temperature sensor unit 57 is provided.

The grip portions 6 and 7 are provided with substantially cylindrical current application electrodes 13 and 14 and voltage measurement electrodes 15 and 16, respectively. The current application electrodes 13 and 14 and the voltage measurement electrodes 15 and 16 are provided. Insulating portions 58 and 59 are provided between them. The bridge unit 60 is provided with a measurement start switch 61.

FIG. 31 shows the circuit configuration inside the device 51. The temperature sensor 57 as a temperature measuring means is
The second embodiment is the same as the first embodiment except that the second embodiment is connected to the CPU 44 via the A / D converter 63 and does not have the electrode switching unit, and thus the description is omitted.

FIG. 32 is a sectional view showing a schematic structure near the temperature sensor unit 57.

A condenser lens 65 such as a Fresnel lens is fitted in a window 64 provided on the front of the apparatus. An infrared sensor 6 is provided inside the condenser lens so as to receive infrared rays from an opening on the condenser lens side surrounded by the heat sink 66.
7 are arranged. A reference temperature sensor 68 made of a thermistor is arranged in the heat sink 66.
It is used for calibration of the infrared temperature sensor 67 and measurement of the environmental temperature. The infrared sensor 67 and the reference temperature sensor 68 are both connected to the substrate 69.

FIG. 33 shows a posture when measurement is performed using the device 51. Hold the grips 6, 7 with both hands and extend both arms to hold the device 51 at shoulder height on the front of the body.
At this time, infrared rays emitted from the face or the like enter the temperature sensor section 67.

FIG. 34 shows a first modification of the present embodiment having a temperature sensor unit 70 having a different configuration. FIG. 34 is a cross-sectional view showing a schematic configuration near the temperature sensor unit 70.

A slit plate having a plurality of slits is fitted in the window portion 64 of the front surface 5a, and a thermistor 72 is arranged on the back surface of the slit plate and connected to the substrate 69.

FIG. 35 shows a temperature sensor 73 having a different configuration.
A second modification example having the following is shown.

In this device, a temperature sensor 73 is provided on the current applying electrode 14 of the grip 7. , FIG. 35
(A) is a schematic sectional view of the current applying electrode 14 (the components of the grip 7 are omitted in the figure), and SUS is used.
Front side (arrow B)
Side), a concave portion 74 is formed on the back surface.
, A temperature sensor 75 made of a thermistor or the like is arranged and fixed by a mold part 76. The temperature sensor 75 is connected to a substrate (not shown) through a hollow inside by a cable 77. The mold portion 76 is formed of an adhesive / mold material such as an epoxy resin mixed with a thermally conductive filler or the like.

When the temperature sensor 73 is disposed on the current applying electrode 14 as described above, the environmental temperature is measured when the grip 7 is not gripped, and the grip 7 is gripped as shown in FIG. 35 (b). In this case, the skin temperature at the crotch between the thumb and the forefinger in contact with the front surface of the electrode 14 can be measured.

FIG. 36 shows a temperature sensor 79 having a different configuration.
A third modification example having the following is shown.

In this device, a temperature sensor 79 as a temperature measuring means is disposed on the insulating portion 59 of the grip 7.

FIG. 36A shows the insulating portion 59 of the grip portion 7.
FIG. 3 is a schematic sectional view of the second embodiment, and a component member 80 made of a resin such as polycarbonate or ABS has a small diameter concave shape in the insulating portion 59. A concave portion 81 is provided substantially at the center in the axial direction on the back side (arrow C side) of the insulating portion 59, a temperature sensor 82 composed of a thermistor is arranged, the periphery is fixed by a molded portion, and the outer surface is formed of SUS, aluminum or the like. It is covered with a plate 84. The temperature sensor 82 is connected to the cable 8 through the component 80.
5 is connected to a substrate (not shown).

When the temperature sensor section is disposed on the insulating section as described above, the environmental temperature is measured when the grip section 7 is not gripped, and when the grip section 7 is gripped as shown in FIG. The skin temperature of the middle finger turned to the insulating section 59 can be measured.

FIG. 37A shows an example of display on the display unit 10. The temperature can be displayed in addition to the time. The time is 10:32, the temperature is 22.4 ° C., and it is indicated by a blinking display that the event time period is suitable for the event “2” (before lunch), and it is indicated that the temperature condition is appropriate. ing. FIG. 37 (b) shows the display unit 10.
Is an example of all lighting display patterns of
"Inappropriate temperature" is displayed.

On the basis of the flowchart shown in FIG.
The measurement procedure will be described.

Since this processing procedure is the same as the processing shown in FIG. 18 except for steps 120 to 124 and step 119, the description of the same parts will be omitted.

After performing the setting process of the matching time zone mark in step 117, the temperature measuring process is performed, and the measured temperature value (T _t ) is stored in the memory (step 120).

Next, it is determined whether the environmental temperature is equal to or higher than a specified temperature.
The determination is made based on 5 ° C ≦ _Tt (step 121). Ye
If it is s, the appropriate temperature mark setting process is performed, and the inappropriate temperature mark reset process is performed (step 122), and the process proceeds to step 123. If No, an inappropriate temperature mark setting process is performed and an appropriate temperature mark reset process is performed (step 124), and the process proceeds to step 123.

In step 123, the matching time zone mark,
An appropriate / unsuitable temperature mark, time and temperature display processing is performed, and the process returns to step 112.

In step 114, if the measurement power switch is ON, the measurement processing described later is performed (step 1).
19).

(Environmental Temperature Correction Processing Subroutine) Hereinafter, step 1 will be described based on the flowchart shown in FIG.
The case where the environmental temperature correction processing is performed in the nineteenth measurement processing subroutine will be described.

Since steps 131 to 137 are the same as steps 1 to 7 in FIG.
Description is omitted.

After notifying the end of measurement in step 137,
15 ° C whether the environmental temperature T _t (° C) is above the specified temperature
It is determined by ≦ _Tt (step 138). If Yes, the arithmetic processing is performed using only the measured values (step 13).
9) Go to step 140. If No, environmental temperature fluctuation correction calculation processing is performed by the following equation (step 14).
1) Go to step 140. Z _X = Z _t − | (T ₀ −T _t ) * m | where T ₀ = 20 ° C. and m = 10Ω / 5 ° C.

At step 140, it is determined whether or not the measurement is performed under event conditions. If Yes, the measured value and the calculation result are stored for each event condition for daily fluctuation correction (step 142), and the process proceeds to step 143. N
If it is o, the process proceeds to step 143.

At step 143, it is determined whether or not the event condition memory data required for the daily fluctuation correction calculation is satisfied. If Yes, the memory data is read out under the event conditions required for the daily fluctuation correction calculation (step 144), the daily fluctuation correction calculation processing is further performed using the value after the temperature correction (step 145), and the daily fluctuation correction calculation result is obtained. (Step 146), the measurement result display process using only the current measurement value is performed, and
An inappropriate temperature mark display process is performed (step 147), and the measurement process subroutine ends.

If No in step 143, it is determined whether or not the environmental temperature is corrected (step 148). If No here, the process proceeds to a step 147. If Yes, the arithmetic processing after the measurement value correction is performed (step 14).
9), a calculation result display process after temperature correction is performed (step 150), and the process proceeds to step 147.

In this embodiment, the ROM 42 and the RAM 43
The CPU 44 constitutes an environmental temperature influence correcting means and an environmental determining means.

(Body Temperature Correction Processing Subroutine) FIG.
The case where the body temperature (skin temperature) correction processing is performed in the measurement processing subroutine of step 119 based on the flowchart shown in FIG.

Steps 151 to 157 are the same as steps 1 to 7 in FIG. 11, and a description thereof will be omitted.

[0287] determines after notifying the measurement ends at step 157, whether the temperature T _b is the specified value or higher, at 20 ° C ≦ T _b (step 159). If Yes, it is determined whether the environmental temperature _Tt (° C) is equal to or higher than a specified temperature by 15 ° C ≦ _Tt
(Step 160).

If “Yes” in the step 160, the arithmetic processing based on only the measured value is performed (step 161), the processing for setting the appropriate temperature mark and the processing for resetting the inappropriate temperature mark are performed (step 162), and the process proceeds to the step 169.

If No in step 160, temperature correction calculation processing 1 is performed by the following equation (step 163). Z _X = Z _t − | (T ₀ −T _t ) * m | where T ₀ = 20 ° C. and m = 10Ω / 5 ° C.
Next, an inappropriate temperature mark setting process and an appropriate temperature mark setting process are performed (step 164), and the process proceeds to step 169.

If No in step 159, an inappropriate temperature mark setting process and an appropriate temperature mark reset process are performed (step 165), and it is determined whether the environmental temperature T _t (° C.) is _{equal to} or higher than a specified temperature by 15 ° C. ≦ T _t. (Step 16
6).

If No in step 166, temperature correction calculation processing 2 is performed according to the following equation (step 167), and the flow advances to step 169. Z _X = Z _t − | (T ₀ −T _t ) * m | where T ₀ = 20 ° C. and m = 15Ω / 5 ° C.

If Yes in step 166, temperature correction calculation processing 3 is performed by the following equation (step 168), and the flow advances to step 169. Z _X = Z _t − | (T ₀ −T _b ) * m | where T ₀ = 20 ° C. and m = 5Ω / 5 ° C.

Steps 169 to 179 are the same as steps 140 to 150 in FIG. 39, and a description thereof will not be repeated.

In this embodiment, the ROM 42 and the RAM 43
The CPU 44 constitutes a body temperature influence correction unit, a state determination unit, and an environment determination unit. (Environmental Temperature / Body Temperature Discrimination Measurement Subroutine) A case will be described below in which the correction temperature information identifies the environmental temperature or the body temperature in the measurement process subroutine of step 119 based on the flowchart shown in FIG.

Steps 181 to 184 are the same as steps 1 to 4 in FIG. 11 and will not be described.

If Yes in step 184,
A READY display such as "Ready" is performed (step 18).
5).

Next, it is determined whether or not it is the sampling timing. If No, the determination operation is performed again. If Yes, the impedance ( _Zt ) between the electrodes is measured (step 187), and the temperature ( _Tt ) is measured (step 188).

Next, it is determined whether or not the measured impedance value (Z _t ) is within the biological measurement range (for example, 350Ω to 1500Ω) (step 189). If No, the process returns to step 186. If Yes, it is determined whether or not the impedance measurement value is a value within the biological range continuously 30 times or more (step 190).

If No in step 190, the process returns to step 186.

If Yes in step 190, the start of measurement is notified by displaying it on the display unit 10 (step 191).

Next, a bioimpedance measurement process is performed (step 192).

Next, a process of discriminating whether the measured temperature value is an environmental temperature or a body temperature (skin temperature) is performed (step 19).
3).

[0303] For example, the following methods are available for the identification processing. The measured value when the power switch is off is defined as the environmental temperature, and the temperature after the power switch is turned on is defined as the body temperature. In this case, as the environmental temperature, the latest value before the power switch is turned on, or the average value or stable value of the latest multiple values is adopted. The latest value, average value, or stable value before the automatic start determination in step 190 is adopted as the environmental temperature, and the temperature thereafter is set as the body temperature. However, the identification method is not limited to such a method.

Next, the end of measurement is notified (step 19).
4). At this time, the stability of the measurement impedance and the stability of the skin temperature value are used as the determination conditions for the end of the measurement.

Next, the measured temperature value at the end of the measurement is registered as a body temperature value (step 195).

Next, temperature correction calculation processing, that is, environmental temperature correction processing and body temperature correction processing are performed (step 19).
6). The correction method is the same as the above-described method, and a description thereof will be omitted.

Next, a calculation process is performed using the corrected value (step 197), and the calculation result is displayed (step 19).
8), the measurement processing subroutine ends.

In this embodiment, the ROM 42 and the RAM 43
The CPU 44 constitutes a temperature influence correction unit and an object identification unit.

(Subroutine before and after bathing determination measurement processing subroutine)
A case will be described below in which the measurement processing subroutine in step 119 determines from the body temperature (skin temperature) information value whether or not it is before or after bathing and whether or not the measurement is inappropriate due to a disease or the like, based on the flowchart shown in FIG.

Steps 201 to 215 are performed
Steps 181 to 195 in FIG. 41 are the same as those in FIG.

After registering the temperature measurement value at the end of the measurement in step 215 as a body temperature value (T _b ), it is determined whether or not the condition is an event condition before and after bathing (step 216).

[0312] If Yes in step 216, the body temperature is determined by the prescribed value or more whether the 35 ° C <T _b (step 217). If Yes, the measurement result is registered as post-bathing data (step 218), and the process proceeds to step 220. If No, the measurement result is registered as pre-bathing data (step 219), and the flow proceeds to step 222.

If No in step 216, the flow advances to step 222.

[0314] At step 220 determines, whether the measurement unsuitable state due to heat generation, such as illness, or body temperature is the specified value or higher, i.e., by 38 ° C <T _b. If No, go to step 22. If Yes, the improper temperature mark is set or a message to that effect is displayed to notify the user that the measurement is inappropriate (step 221), and the process proceeds to step 222.

At step 222, a daily fluctuation correction calculation process is performed. At this time, the temperature correction processing may be performed, and the daily fluctuation correction calculation processing may be further performed on the temperature correction value.

Next, a calculation process such as a body fat percentage is performed using the corrected value (step 223), and the calculation result is displayed on the display unit 10
Is displayed (step 224), and the measurement processing subroutine ends.

In this embodiment, the ROM 42 and the RAM 43
The CPU 44 constitutes an object identification unit and a state estimation unit.

A case will be described below in which the correction processing is performed by learning and recognizing the temperature in the measurement processing subroutine of step 119 with reference to the flowcharts shown in FIGS. 43 and 44.

Steps 231 to 241 are the same as steps 151 to 161 in FIG.
Steps 249 to 258 are the same as steps 169 to 179 in FIG.

At step 239, No, that is, body temperature T _b
If 20 ° C.> T _b , the measured value is registered and updated in the temperature (body temperature) fluctuation pattern recognition divided memory in parallel with the daily fluctuation pattern recognition divided memory (step 24).
2). Here, the divided memory for recognizing a temperature (body temperature) fluctuation pattern is provided with a divided memory area in units of 2.5 ° in the range of 0 ° C. to 20 ° C. (specified temperature).

Next, the entire memory area of the divided memory for recognizing the temperature (body temperature) fluctuation pattern is called, and T ₀ , m of the temperature correction equation is determined by linear regression processing or the like.

Next, it is determined whether or not the environmental temperature _Tt is equal to or lower than a specified value.
It is determined based on 15 ° C. ≦ _Tt (step 244). N
o _{If, Z X = Z t - |} (T 0 -T b) * m | , the process proceeds to step 249 performs a temperature correction calculation process. Y
If es, go to step 246.

If No in step 240, that is, if the environmental temperature _Tt is 15 ° C.> _Tt , the flow advances to step 246.

In step 246, the measured values are registered and updated in the temperature (environmental temperature) fluctuation pattern recognition divided memory in parallel with the daily fluctuation pattern recognition divided memory. Here, the temperature (environmental temperature) fluctuation pattern recognition divided memory is 0 °.
A divided memory area in units of 2.5 ° is provided in a range of C to 15 ° C (specified temperature).

Next, the entire memory area of the divided memory for recognizing the temperature (environmental temperature) fluctuation pattern is called, and T ₀ , m of the temperature correction equation is determined by linear regression processing or the like (step 248).

Next, Z _X = Z _t- | (T ₀ -T _t ) * m
The temperature correction calculation process is performed by |

[0327] After performing the calculation process using only the measured value in step 241, the process also proceeds to step 249.

In the present embodiment, the RAM 43 constitutes an environmental temperature value holding means and a body temperature value holding means, and the ROM 42, RA
The M43 and the CPU 44 constitute environmental temperature representative value extraction means, environmental temperature fluctuation pattern recognition means, environmental temperature correction processing means, body temperature representative value extraction means, body temperature fluctuation pattern recognition means, and body temperature correction processing means.

[0329]

As described above, according to the first aspect of the present invention, it is possible to provide accurate health management guideline information in which impedance is measured at any point in a cycle and the effect of periodic fluctuation is corrected. It is possible to collect stable values even when providing trend information at time intervals exceeding the period of the periodic fluctuation, so it is possible to grasp more accurate trends, and health management with high utility Can provide guidance information.

According to the second aspect, the impedance measurement value at the time of a specific measurement is taken out as a representative value, or a plurality of impedance measurement values at the time of a specific measurement is corrected by performing a correction process such as a statistical process. Will be able to do.

According to the third aspect of the present invention, at the time of each measurement of the impedance measurement values held in the same data holding means, the impedance measurement values are separated from each other by substantially several periods, so that the factor of the periodic fluctuation is substantially the same condition. Impedance measurements can be stored. Therefore, when a representative value is extracted from the data in each data holding unit, the reliability of the representative value as basic data for correcting the periodic fluctuation is improved.
That is, since the basic data that is more suited to the lifestyle of the subject can be extracted, the accuracy of the correction processing can be improved. Since the learning function is ensured by the data holding unit, the accuracy of the correction process is further improved as the data is accumulated.

If a plurality of data holding means corresponding to the same time domain are provided as in the fourth invention and are held in different data holding means depending on the presence or absence of the specific action, the representative value can be set by the data holding means. Extraction does not impair the reliability of the data.

According to the fifth aspect, it is possible to reliably hold the measured impedance value in an appropriate data holding unit.

According to the sixth aspect, the reliability of data when a representative value is extracted even when there is no or little data stored in the data storage means can be ensured.

According to the seventh aspect, since the correction processing is simple, quick processing is possible.

According to the eighth aspect, by specifying the time when the impedance measurement value is measured, the periodic fluctuation pattern can be recognized from the impedance measurement value. Since the periodic fluctuation of the impedance can be approximately reproduced, abundant data can be taken out for correction. Accordingly, a more accurate correction process can be performed.

According to the ninth aspect, at the time of each measurement of the impedance measurement values held in the same data holding means, the impedance measurement values are separated from each other by approximately several periods, so that the factor of the periodic fluctuation is substantially the same condition. Impedance measurements can be stored. Therefore, when a representative value is extracted from the data in each data holding unit, the reliability of the representative value as basic data for recognizing the periodic fluctuation pattern is improved. In other words, the periodicity fluctuation pattern can be recognized more in accordance with the lifestyle of the subject, so that the accuracy of the correction process is improved. Since the learning function is ensured by the data holding unit, the accuracy of the correction process is further improved as the data is accumulated.

If a plurality of data holding means corresponding to the same time domain are provided as in the tenth invention and are held in different data holding means depending on the presence or absence of a specific action, the representative value can be set by the data holding means. Extraction does not impair the reliability of the data.

According to the eleventh aspect, it is possible to reliably hold the measured impedance value in an appropriate data holding unit.

According to the twelfth aspect, it is possible to secure the reliability of data when extracting a representative value even at a stage where there is no or little data stored in the data storage means.

According to the thirteenth aspect, by extracting a time region with little change, it is possible to specify a region in which data with little change can be secured, so that highly reliable data can be used as correction data. Can be extracted. Also, an appropriate representative value of the periodic fluctuation can be selected from such a stable region.

According to the fourteenth aspect, the periodic variation of the impedance of the subject can be approximately reproduced by recognizing the periodic variation pattern of the impedance. As the basic data, highly reliable data corresponding to the subject's lifestyle can be extracted. Accordingly, highly accurate correction processing can be performed.

By displaying the periodic fluctuation pattern as in the fifteenth aspect, it is possible to provide useful information for the subject to be aware of the lifestyle.

According to the sixteenth aspect, the measurement time can be objectively specified, and the processing is easy.

According to the seventeenth aspect, the subject can easily specify the measurement time without any means for knowing the time,
Since the measurement time is specified in relation to the subject's action that is likely to cause impedance change, it can also be used as a unit to distinguish data from each other, such as when holding it in another data holding means. Can be used.

According to the eighteenth aspect, since the measured time information can be converted according to the data processing method, the degree of freedom in processing is increased. In the conversion method, the user may set and input the correspondence between the action of the subject and the time in advance, or the correspondence may be extracted from the data fluctuation pattern by the recognition unit.

According to the nineteenth aspect, stable and reliable health management guideline information can be obtained even when an appropriate time of day is selected and measured.

According to the twentieth aspect, stable and reliable health management guideline information can be obtained even when an appropriate day of the week is selected and measured.

According to the twenty-first aspect, highly reliable trend information based on stable data corrected for the influence of periodic fluctuation can be provided.

According to the twenty-second aspect, it is possible to collectively provide trends at different time intervals such as short-term, medium-term, and long-term, instead of trends at fixed time intervals. More diverse information can be provided.

According to the twenty-third aspect, the user can directly and easily acquire the trend information.

According to the twenty-fourth aspect, it is possible to correct the influence of the environmental temperature, which has a physiological effect on the subject and causes a variation in impedance, and thus provides more accurate health care guide information. be able to.

According to the twenty-fifth aspect, measurement can be performed only in an environment in which highly accurate health management guideline information can be provided, and there is no danger of providing low-accuracy information.

According to the twenty-sixth aspect, even when measurement is performed in an environment unsuitable for impedance measurement, correction processing is performed, so that highly accurate information can be provided.

According to the twenty-seventh aspect, it is possible to correct the influence of body temperature, which is a factor of impedance fluctuation, so that more accurate health care guide information can be provided.

According to the twenty-eighth aspect, since the body temperature at the time of impedance measurement can be measured, the body temperature at an appropriate point in time as data for correcting impedance can be easily measured.

According to the twenty-ninth aspect, since the electrode is generally made of metal and has high thermal conductivity, the electrode can be used as a heat collecting member, and the structure of the body temperature measuring means can be simplified.

According to the thirtieth aspect, measurement can be performed only in an environment in which highly accurate health management guideline information can be provided, and there is no danger of providing inaccurate information.

According to the thirty-first aspect, since the correction processing is performed even when the measurement is performed at a body temperature that is not suitable for impedance measurement, highly accurate information can be provided.

According to the thirty-second aspect, it is possible to correct the influence of at least one of the environmental temperature and the body temperature, which is a factor of the impedance fluctuation, so that it is possible to provide more accurate health management guideline information. . Also,
Since the measurement can be performed by the common temperature measurement means, it is not necessary to provide a separate measurement means, and the number of parts can be reduced.

According to the thirty-third aspect, since the temperature measurement value measured by the common temperature measurement means is identified, it is possible to perform a correction process according to the object, thereby providing more accurate health care guideline information. Can be.

According to the thirty-fourth aspect, even when the environment and the state are not suitable for impedance measurement, the correction processing is performed, so that it is possible to provide highly accurate health care guideline information.

According to the thirty-fifth aspect, when a representative value is extracted from the data in each of the environmental temperature value holding means and each of the body temperature value holding means, a variation pattern for each of the environmental temperature value and the body temperature value is recognized. The reliability of the representative value as basic data is improved, and the accuracy of the correction processing is also improved. Since the learning function is ensured by the data holding unit, the accuracy of the correction process is further improved as the data is accumulated.

[0364] According to the thirty-sixth aspect, the measured body temperature can be used for estimating the state of the subject associated with the fluctuation of the body temperature. Therefore, the measured value of the body temperature can be used for providing more various information.

[Brief description of the drawings]

FIG. 1 is a perspective view showing an overall configuration of a health management guideline advice device according to a first embodiment of the present invention.

FIG. 2 is a sectional view taken along the line AA 'of FIG.

FIG. 3 shows a basic posture when measurement is performed using the health management guideline advice device according to the first embodiment of the present invention.

FIG. 4 is a block diagram showing a circuit configuration inside the health management guideline advice device according to the first embodiment of the present invention.

FIG. 5A is a diagram illustrating a connection state of an electrode signal switching unit in a right hand / right foot impedance measurement mode.
FIG. 5B is a diagram schematically showing the energization path in the same mode.

FIG. 6A is a diagram illustrating a connection state of an electrode signal switching unit in a left hand / left foot impedance measurement mode.
FIG. 6B is a diagram schematically showing the energization path in the same mode.

FIG. 7A is a diagram showing a connection state of an electrode signal switching unit in an impedance measurement mode between both soles. FIG.
(B) is a figure which showed typically the energization path in the same mode.

FIG. 8A is a diagram illustrating a connection state of an electrode signal switching unit in an impedance measurement mode between both hands. FIG.
(B) is a figure which showed typically the energization path in the same mode.

FIG. 9A is a diagram showing a connection state of an electrode signal switching unit in a right hand / left foot impedance measurement mode.
FIG. 9B is a diagram schematically showing the energization path in the same mode.

FIG. 10A is a diagram showing a connection state of an electrode signal switching unit in a left hand / right foot impedance measurement mode. FIG. 10B is a diagram schematically showing the energization path in the same mode.

FIG. 11 is a flowchart showing a measurement procedure by the health management guideline advice device according to the first embodiment of the present invention.

FIG. 12 is a diagram showing a state in which the display unit of the health management guideline advice device according to the first embodiment of the present invention is fully lit.

FIGS. 13A and 13B are diagrams showing displays on the display unit in a state of notifying the start of measurement of the health management guideline advice device according to the first embodiment of the present invention.

FIG. 14 is a diagram showing a display on a display unit during measurement of the health management guideline advice device according to the first embodiment of the present invention.

FIGS. 15A, 15B, and 15C are diagrams showing displays on a display unit showing measurement results of the health management guideline advice device according to the first embodiment of the present invention.

FIG. 16 is a view showing a display when displaying a fluctuation range of the body fat percentage on the display unit of the health management guideline advice device according to the first embodiment of the present invention.

FIG. 17 is a block diagram showing an internal circuit configuration of the health management guideline advice device according to the second embodiment of the present invention.

FIG. 18 is a flowchart showing a measurement procedure of the health management guideline advice device according to the second embodiment of the present invention.

FIG. 19A is a view showing a display on a display unit of the health management guideline advice device according to the second embodiment of the present invention. FIG. 19B is a diagram showing all lighting patterns of the display section.

FIG. 20 is a flowchart showing a measurement procedure of the health management guideline advice device according to the third embodiment of the present invention.

FIG. 21 is a flowchart illustrating a procedure of a measurement processing subroutine of FIG. 20;

FIG. 22 is a diagram showing a display on a display unit for displaying a daily fluctuation pattern of the health management guideline advice device according to the third embodiment of the present invention.

FIG. 23 is a diagram schematically showing a divided memory area of the health management guideline advice device according to the third embodiment of the present invention.

FIG. 24 is a graph showing a daily fluctuation correction pattern of the health management guideline advice device according to the third embodiment of the present invention.

FIG. 25 is a flowchart showing a procedure of a measurement processing subroutine of the health management guideline advice device according to the fourth embodiment of the present invention.

FIG. 26 is a graph showing default values of daily fluctuation patterns of the health management guideline advice device according to the fourth embodiment of the present invention.

FIG. 27 is a flowchart showing a procedure of a measurement processing subroutine of the health management guideline advice device according to the fifth embodiment of the present invention.

FIG. 28 is a diagram showing a display on a display unit for displaying a weekly variation pattern of the health management guideline advice device according to the fifth embodiment of the present invention.

FIGS. 29A to 29D are views showing displays on a display unit for displaying a long-term trend of the health management guideline advice device according to the fifth embodiment of the present invention.

FIG. 30 is a perspective view showing an overall configuration of a health management guideline advice device according to a sixth embodiment of the present invention.

FIG. 31 is a block diagram showing an internal circuit configuration of a health management guideline advice device according to a sixth embodiment of the present invention.

FIG. 32 is a sectional view showing a schematic configuration near a temperature sensor of a health care guideline advice device according to a sixth embodiment of the present invention.

FIGS. 33 (a) and 33 (b) are views showing postures when measurement is performed using the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 34 is a cross-sectional view showing a schematic configuration near a temperature sensor unit of a first modification of the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 35 (a) is a cross-sectional view illustrating a schematic configuration near a temperature sensor unit of a second modification of the health management guideline advice device according to the sixth embodiment of the present invention. FIG. 35 (b)
FIG. 4 is a diagram showing a state where a grip portion is gripped.

FIG. 36 (a) is a cross-sectional view illustrating a schematic configuration near a temperature sensor section of a third modification of the health management guideline advice device according to the sixth embodiment of the present invention. FIG. 36 (b)
FIG. 4 is a diagram showing a state where a grip portion is gripped.

FIG. 37 (a) is a diagram showing a display on the display unit of the health management guideline advice device according to the sixth embodiment of the present invention. FIG. 37B is a diagram showing an all-lit display pattern of the display unit.

FIG. 38 is a flowchart showing a measurement procedure of the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 39 is a flowchart showing a measurement processing subroutine when the environmental temperature correction processing is performed by the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 40 is a flowchart illustrating a measurement processing subroutine when performing a body temperature correction process of the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 41 is a flowchart showing a measurement processing subroutine for identifying correction temperature information of the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 42 is a flowchart showing a measurement processing subroutine in the case where the health management guideline advice device according to the sixth embodiment of the present invention performs state determination from body temperature notification.

FIG. 43 is a first half of a flowchart showing a measurement processing subroutine in a case where a correction processing based on temperature learning recognition is performed by the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 44 is a latter half of a flowchart showing a measurement processing subroutine in a case where a correction process based on learning recognition of temperature is performed by the health management guideline advice device according to the sixth embodiment of the present invention.

FIG. 45 is a perspective view showing the overall configuration of a health management guideline advice device according to a conventional example.

46 (a), 46 (b) and 46 (c) are views showing a conventional impedance basic measurement method.

FIG. 47 is a graph showing general circadian fluctuations in bioelectrical impedance.

FIG. 48 is a graph showing general circadian fluctuations in bioimpedance when taking a bath.

FIG. 49 is a graph showing general diurnal variations in bioimpedance between a person with high activity and a person with low activity.

FIG. 50 is a graph showing general circadian fluctuations in bioimpedance when there is an effect of fatigue.

FIG. 51 is a graph showing general circadian fluctuations in bioimpedance of a person whose body temperature is high due to eating.

FIG. 52 is a graph showing general circadian fluctuations in bioimpedance of a person whose body temperature is high due to a disease or the like.

FIG. 53 is a graph showing an example of circadian variation in bioimpedance when the body is cooled by going out in winter.

FIG. 54 is a graph showing an example of a weekly variation in bioimpedance.

FIG. 55 is a graph showing circadian variations in impedance between both palms and between soles.

[Explanation of symbols]

 1,51 Health management guideline advice device 2 Main unit 3 Foot electrode unit 4 Cable 6,7 Grip unit 10 Display unit 11 Key input unit 13,14,20,21 Electrode for current application 15,16,18,19 For voltage measurement Electrode 32 Electrode signal switching unit 39 Reference signal (timer signal) generation unit 42 ROM 43 RAM 44 CPU 57, 70, 73, 82 Temperature sensor unit 67 Infrared sensor 72 Thermistor 75 Temperature sensor 82 Temperature sensor

Claims (36)

[Claims] 1. A health care guideline advice device comprising: impedance measurement means for measuring the impedance of a subject's body; and arithmetic means for calculating health care guideline information based on the measured impedance value. A health care guideline advice device comprising a periodic variation correction means for correcting sex variation. 2. The apparatus according to claim 1, further comprising: a measuring time information acquiring unit for acquiring information on an impedance measurement time, wherein the periodicity variation correcting unit selects data of an impedance measurement value required for the correction based on the information on the measuring time. 2. The health management guideline advice device according to claim 1, further comprising a selection unit, and a correction processing unit that performs a predetermined correction process based on the selected data. 3. A measurement time information acquisition unit for acquiring information on impedance measurement time, wherein the periodicity variation correction unit stores data that holds impedance measurement values measured in the same time region in different periods. Holding means, representative value extracting means for extracting a representative value of the time domain from a plurality of impedance measurement values held in the data holding means, and selecting a representative impedance value necessary for the correction based on information on the time domain. 2. The health management guideline advice device according to claim 1, further comprising a data selection unit, and a correction processing unit that performs a predetermined correction process based on the selected data. 4. The data holding means is distinguished by a time domain using time as an index, and when the impedance measurement value changes beyond a predetermined condition depending on the presence or absence of a specific action of the subject, the same time is used. 4. The health management guideline advice device according to claim 3, wherein a plurality of data holding units corresponding to the areas are provided, and the data holding units are held in different data holding units according to the presence or absence of the specific action. 5. The health management guideline advice device according to claim 4, further comprising an action presence / absence determining means for determining the presence / absence of the specific action. 6. The data holding means according to claim 3, wherein said data holding means holds a default value based on a predetermined periodicity fluctuation pattern for use at a stage where there is no or little held data. Health management guideline advice device. 7. The apparatus according to claim 2, wherein the correction processing means performs an averaging process on the selected data.
7. The health management guideline advice device according to any one of items 6 to 6. 8. A measurement time information acquisition unit for acquiring information on the impedance measurement time, wherein the periodic variation correction unit recognizes a periodic variation pattern of the impedance measurement value based on the information on the measurement time. 2. The health management guideline advice device according to claim 1, further comprising: periodic fluctuation pattern recognition means; and correction processing means for performing predetermined correction processing based on the recognized periodic fluctuation pattern. 9. A measurement time information acquisition unit for acquiring information relating to impedance measurement time, wherein the periodicity variation correction unit stores impedance measurement values measured in the same time region in different periods. Holding means, a representative value extracting means for extracting a representative value of the time domain from a plurality of impedance measured values held in the data holding means, and recognizing a periodic variation pattern of the impedance measured value based on information on the time domain. 2. The health management guideline advice device according to claim 1, further comprising: a periodic fluctuation pattern recognizing unit that performs a predetermined correction process based on the recognized periodic fluctuation pattern. 10. The data holding means is distinguished by a time domain using time as an index, and when the impedance measurement value changes beyond a predetermined condition depending on the presence or absence of a specific action of the subject, the same time is used. 10. A plurality of data holding means corresponding to an area, wherein different data holding means hold data in accordance with the presence or absence of the specific action.
Health management guideline advice device described. 11. The health management guideline advice device according to claim 10, further comprising an action presence / absence determination unit for determining whether or not the specific action is performed. 12. The data holding means according to claim 9, wherein said data holding means holds a default value based on a predetermined periodicity fluctuation pattern for use at a stage where no held data is present or a small amount. Health management guideline advice device. 13. The health according to claim 8, wherein the correction processing unit includes a stable region extracting unit that extracts a time region having a small variation based on the recognized periodic variation pattern. Management guideline advice device. 14. The correction processing means includes correction data extraction means for extracting an impedance value necessary for correction based on the recognized periodic fluctuation pattern, and a predetermined correction for the extracted impedance value. 13. The health management guideline advice device according to claim 8, which performs processing. 15. The health management guideline advice device according to claim 8, further comprising a fluctuation pattern display unit for displaying the recognized periodic fluctuation pattern. 16. The health management guideline advice according to claim 1, wherein the measurement time information acquisition unit is a time information acquisition unit that acquires time information expressed by a time at the time of impedance measurement. apparatus. 17. The measurement time information acquisition means according to claim 1, wherein the measurement time information acquisition means is time information acquisition means for acquiring time information expressed by an action of the subject at the time of impedance measurement. Health management guideline advice device. 18. The measurement time acquisition means according to claim 1, wherein at least one of the time information expressed by the time at the time of impedance measurement and the time information expressed by the action of the subject at the time of impedance measurement is converted to the other time information. 18. The health management guideline advice device according to claim 16, further comprising time information conversion means for converting time information into time information. 19. The health management guideline advice device according to claim 1, wherein the periodic fluctuation is a daily fluctuation. 20. The health management guideline advice device according to claim 1, wherein the periodic variation is a weekly variation. 21. A periodic fluctuation corrected data holding unit for holding an impedance value or health management guideline information obtained by the periodic fluctuation correcting unit, and an impedance value stored in the periodic fluctuation corrected data holding unit. 21. The health management guideline advice device according to claim 1, further comprising a trend recognition unit that recognizes a change in health management guideline information in units of time intervals equal to or longer than the cycle. 22. A periodic fluctuation corrected data holding unit for holding the impedance value or the health management guideline information obtained by the periodic fluctuation correcting unit, and an impedance value stored in the periodic fluctuation corrected data holding unit. 21. A trend recognizing means for recognizing a change in health management guideline information at different time intervals longer than the cycle.
Health management guideline advice device described. 23. The health management guideline advice device according to claim 21, further comprising trend display means for displaying the recognized trend. 24. A health care guideline advice device comprising: impedance measurement means for measuring the impedance of a body of a subject; and calculation means for calculating health care guide information based on the measured impedance value. Health, comprising: an environmental temperature measuring means for measuring the environmental temperature; and an environmental temperature influence correcting means for correcting the influence of the environmental temperature on the impedance measured value based on the environmental temperature measured value measured by the environmental temperature measuring means. Management guideline advice device. 25. The health care guideline according to claim 24, further comprising an environment determining unit that determines whether the environment is suitable for impedance measurement based on the environmental temperature measured by the environmental temperature measuring unit. Advice device. 26. The environmental temperature influence correction means performs a correction process based on an environmental temperature measurement value when the environment determination means determines that the environment is not suitable for impedance measurement. Health management guideline advice device described. 27. A health care guideline advice device comprising: an impedance measurement means for measuring the impedance of a body of a subject; and a calculation means for calculating health care guideline information based on the measured impedance value. A health care guideline advice device, comprising: a body temperature measuring means for measuring a body temperature; and a body temperature influence correcting means for correcting the influence of the body temperature on the impedance based on the measured body temperature measured by the body temperature measuring means. 28. The health care guideline advice device according to claim 27, wherein said body temperature measuring means is provided at a portion which comes into contact with the subject's skin at the time of impedance measurement. 29. The site in contact with the subject's skin,
29. The health care guideline advice device according to claim 28, wherein the health care guideline advice device is an electrode constituting the impedance measuring means. 30. The apparatus according to claim 27, further comprising a state determination unit configured to determine whether the subject is in a state suitable for impedance measurement based on the body temperature measurement value measured by the body temperature measurement unit. 29. The health care guideline advice device according to 29. 31. The body temperature influence correcting means performs a correction process based on a measured body temperature when the state determining means determines that the subject is not in a state suitable for impedance measurement. Item 30. The health management guideline advice device according to Item 30. 32. A healthcare guideline advice device comprising: impedance measurement means for measuring the impedance of a subject's body; and arithmetic means for calculating healthcare guideline information based on the measured impedance value. And a common temperature measuring means capable of measuring both the body temperature of the subject and a temperature for correcting the effect on the impedance based on at least one of the environmental temperature measurement value and the body temperature measurement value measured by the temperature measurement means. A health management guideline advice device comprising an influence correction means. 33. The health management guideline advice device according to claim 32, further comprising target identification means for identifying whether the temperature measurement means is an environmental temperature or a body temperature. 34. An environmental temperature value extracting means for extracting an environmental temperature value for correction from a temperature measured value identified as an environmental temperature measured value by said object identifying means, and a body temperature measured value by said object identifying means. Body temperature value extracting means for extracting a body temperature value for correction from a temperature measurement value identified as being present, and an environment suitable for impedance measurement based on the environmental temperature value and the body temperature value and a state of a subject or not. Environment / state determination means for determining the environmental temperature value or the body temperature value when the environment / state determination means determines that the environment and state are not suitable for impedance measurement. 34. The health management guideline advice device according to claim 33, wherein the correction process is performed based on at least one of the following. 35. An environment temperature value holding means for holding an impedance measurement value at the environment temperature value for each of a predetermined range of environment temperature values, and a plurality of impedances held by the environment temperature value holding means. An environmental temperature representative value extracting means for extracting a representative value of the range from the measured value; an environmental temperature fluctuation pattern recognizing means for recognizing a fluctuation pattern of the impedance measurement value with respect to the environmental temperature value; and Environmental temperature correction processing means for performing a predetermined correction process based on: a body temperature value holding means for holding an impedance measurement value at the body temperature value for each of a predetermined range of body temperature values; and a plurality of body temperature values held by the body temperature value holding means. Means for extracting a representative value in the range from the measured impedance value; a means for extracting a representative value for the body temperature; 35. An apparatus according to claim 34, further comprising: a body temperature fluctuation pattern recognizing unit that recognizes a fluctuation pattern of the measured temperature value; and a body temperature correction processing unit that performs predetermined correction processing based on the recognized fluctuation pattern. Health management guideline advice device. 36. The apparatus according to claim 33, further comprising state estimation means for estimating the state of the subject based on the temperature measurement value identified by the object identification means as a body temperature measurement value.
36. The health management guideline advice device according to any one of the items 35 to 35.