JP2014221160A - Activity meter - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prevent the deterioration of energy consumption calculation precision attributed to circadian variation in weight of a person to be measured.SOLUTION: An activity meter includes a memory 12 for associating and storing information on circadian variation related to circadian variation in weight, attribute information related to an attribute of the living body, and weight information showing the weight, an acceleration sensor 20 for detecting body motion information showing a user's body motion, and a CPU 30 for executing the processes below. The CPU 30 acquires the user's attribute information, acquires weight information related to the user's weight, specifies information on the circadian variation corresponding to the user's attribute information by referring to the memory 12, and based on the specified information on the circadian variation and the user's weight information, estimates the user's weight at a prescribed time. The user's activity amount during a prescribed period is calculated based on the estimated weight, and the body motion information detected by the acceleration sensor 20 in the prescribed period including the prescribed time in a period.

Description

  The present invention relates to an activity meter that measures an amount of physical exercise activity of a measurement subject.

  2. Description of the Related Art Conventionally, an activity meter is known as a device for calculating (estimating) energy consumption related to physical exercise. As a technique related to the activity meter, for example, Patent Document 1 discloses the following technique. That is, Patent Document 1 discloses a body motion detection device that discriminates walking motion from other motions and calculates energy consumption according to each motion form. Further, Patent Document 2 discloses an exercise energy consumption estimation device that achieves high accuracy of energy consumption estimation by taking into account various information related to the measurement subject in energy consumption estimation. .

JP 2009-131482 A JP 2007-252646 A

  By the way, in order to calculate the energy consumption with high accuracy, it is necessary to make the parameter values used for calculating the energy consumption as accurate as possible. One of the parameters required for calculating energy consumption is the weight of the person being measured. Here, since the body weight fluctuates within a day (referred to as “daily fluctuation”), it is not actually a constant parameter. Therefore, daily fluctuations in body weight hinder high accuracy in calculating energy consumption.

It should be noted that neither Patent Document 1 nor Patent Document 2 discloses or even suggests the technical idea of considering the daily fluctuation of the weight of the person to be measured in the calculation of energy consumption.
This invention is made in view of the said situation, and makes it a solution subject to prevent the deterioration of the calculation accuracy of the energy consumption resulting from the daily fluctuation | variation of a to-be-measured person's weight.

  In order to solve the above-described problem, a first aspect of the activity meter is a memory that stores daily fluctuation information related to daily fluctuations in body weight, attribute information related to biological attributes, and weight information indicating weight in association with each other. The attribute information acquisition unit for acquiring the attribute information of the user, the weight information acquisition unit for acquiring the weight information related to the weight of the user, and the storage unit, and corresponding to the attribute information of the user A body weight for estimating the weight of the user at a predetermined time on the basis of the daily fluctuation information specified by the daily fluctuation information specifying section and the daily fluctuation information specified by the daily fluctuation information specifying section and the weight information of the user. An estimation unit, a body motion detection unit for detecting body motion information indicating the body motion of the user, the weight of the user estimated by the weight estimation unit, and the body motion in a predetermined period including the predetermined time within a period. detection In on the basis of the said detected body motion information, characterized in that it and a activity amount calculation unit that calculates an activity amount of the user in the predetermined period.

According to the first aspect of the activity meter of the present invention, the weight of the user at a predetermined time is estimated based on the daily fluctuation information corresponding to the attribute information and the weight information of the user and the weight information of the user. . This estimated weight is a weight calculated in consideration of the daily fluctuation information. Therefore, by using this estimated weight in the calculation of the activity amount, the calculation accuracy of the activity amount is improved. That is, based on the estimated weight and the body motion information detected by the body motion detection unit in a predetermined period including the predetermined time within the period, the amount of activity of the user in the predetermined period is calculated with high accuracy. The Therefore, according to the aspect of the activity meter of the present invention, the deterioration of the calculation accuracy of the energy consumption due to the daily fluctuation of the weight of the measurement subject is prevented, and the calculation accuracy is improved.
The “daily fluctuation information” is information relating to daily fluctuations in body weight. “Attribute information” is information related to the attributes of a living body. “Weight information” is information indicating the weight.

According to the second aspect of the activity meter of the present invention, in the first aspect of the activity meter described above, the weight information indicates the weight of the user at a reference time, and the weight estimation unit includes: Based on the daily fluctuation of the weight indicated by the daily fluctuation information, the weight of the user at the predetermined time is estimated from the weight of the user at the reference time.
With this configuration, the weight of the user at the reference time can be used as a reference, and the weight of the user at the predetermined time can be calculated with high accuracy from the reference weight and the daily fluctuation information. Then, by using the weight of the user calculated with high accuracy in this way for calculating the energy consumption, the energy consumption is calculated with high accuracy.

According to the third aspect of the activity meter of the present invention, in the second aspect of the activity meter, the predetermined period is a period from a start time to an end time, and the predetermined time is the start time. And the weight estimation unit, based on the daily fluctuation of the weight indicated by the daily fluctuation information, the first weight that is the weight of the user at the start time from the weight of the user at the reference time And calculating a second weight, which is the weight of the user at the end time, from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information. A second calculation unit; and an estimation unit that estimates an average value of the first weight and the second weight as the weight of the user in the predetermined period.
With this configuration, the weight of the user at the start time, which is the time when the user's body movement starts, and the weight of the user at the end time, which is the time when the user's body movement ends, are calculated. The average value is used as the weight value of the user during the body movement period in the calculation of energy consumption. Thereby, energy consumption is calculated with high accuracy.

According to the fourth aspect of the activity meter of the present invention, in the second aspect of the activity meter, the predetermined period is a period from a start time to an end time, and the predetermined time is a start time. The weight estimation unit calculates the weight of the user at the start time from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information, and is calculated by the calculation unit. An estimation unit that estimates the weight of the user as the weight of the user in the predetermined period.
With this configuration, the weight of the user at the start time, which is the time when the user's body movement starts, is calculated, and the calculated value is used as the weight value of the user during the body movement period in the calculation of energy consumption. . Thereby, energy consumption is calculated with high accuracy.
According to the fifth aspect of the activity meter of the present invention, in the second aspect of the activity meter, the predetermined period is a period from a start time to an end time, and the predetermined time is an end time. The weight estimation unit calculates the weight of the user at the end time from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information, and is calculated by the calculation unit. An estimation unit that estimates the weight of the user as the weight of the user in the predetermined period.
With this configuration, the weight of the user at the end time, which is the time when the user's body movement ends, is calculated, and the calculated value is used as the weight value of the user during the body movement period in the calculation of energy consumption. . Thereby, energy consumption is calculated with high accuracy.
According to the sixth aspect of the activity meter of the present invention, in any one of the first to fifth aspects of the activity meter described above, when the maximum value of the weight of the user in the daily fluctuation is a reference weight, The daily fluctuation information indicates a relationship between a ratio of the weight of the user to the reference weight and time.
With this configuration, the weight of the user at a desired time can be calculated easily and with high accuracy by referring to the daily fluctuation information. Then, by using the weight of the user calculated with high accuracy in this way for calculating the energy consumption, the energy consumption is calculated with high accuracy.

According to a seventh aspect of the activity meter of the present invention, in any one of the second to sixth aspects of the activity meter described above, the activity meter further includes a communication unit that communicates with an external device, and the weight information is Including information indicating the reference time, the weight information acquisition unit can acquire the weight information from the external device via the communication unit.
With this configuration, the weight information acquired from the external device via the communication unit includes time information corresponding to the weight information, so that the weight estimation unit can estimate the weight of the user at a predetermined time with high accuracy. The Then, by using the user's weight estimated with high accuracy in this way for calculating the energy consumption, the energy consumption is calculated with high accuracy.

According to the eighth aspect of the activity meter of the present invention, in any one of the first to seventh aspects of the activity meter, the attribute information is information indicating the gender of the user, and the age of the user. And at least one of the information indicating the living situation.
With this configuration, various parameters that greatly affect the daily fluctuation of the weight are included in the attribute information, and the daily fluctuation information specified by the daily fluctuation information specifying unit is more suitable for each user. To be. Therefore, the estimation result by the weight estimation unit and the calculation result of the consumed energy are made more accurate.

It is a block diagram which shows the system configuration example of the active mass meter which concerns on one Embodiment of this invention. It is a block diagram which shows the main function structural examples of CPU of the active mass meter which concerns on one Embodiment of this invention. It is a figure which shows an example of the approximate curve formed by carrying out the curve regression of the daily fluctuation | variation of a body weight. It is a figure which shows the flowchart of the calculation process of the energy consumption by the active mass meter which concerns on one Embodiment of this invention. It is a figure which shows an example of the daily fluctuation information utilized in the active mass meter which concerns on the 1st modification of one Embodiment of this invention. It is a block diagram which shows the structural example of the health management system which concerns on the 4th modification of one Embodiment of this invention. It is a block diagram which shows the structural example of the health management system which concerns on the 4th modification of one Embodiment of this invention.

  Preferred embodiments of the present invention will be described below in detail with reference to the accompanying drawings. However, in each figure, the size and scale of each part are appropriately changed from the actual ones. Further, since the embodiments described below are preferable specific examples of the present invention, various technically preferable limitations are attached thereto. However, the scope of the present invention is particularly limited in the following description. Unless otherwise stated, the present invention is not limited to these forms.

FIG. 1 is a block diagram showing a system configuration example of an activity meter according to an embodiment of the present invention. As shown in FIG. 1, the activity meter 1 includes a memory 12, a communication interface 14, a timer unit 16, a display unit 18, an acceleration sensor 20, an operation unit 22, and a CPU 30.
The memory 12 is a non-volatile storage medium in which various programs that are read and executed by the CPU 30 and a coefficient table TBL and the like are recorded. In the coefficient table TBL, daily fluctuation information, which is information related to daily fluctuations in weight, and attribute information are stored in association with each other.

“Diurnal variation” means a variation in body weight in one day. The “daily fluctuation information” is information indicating the relationship between the ratio of the weight at each time with respect to the reference weight and the time when the maximum value of the weight in the daily fluctuation is the reference weight. “Attribute information” is information about attributes related to a living body, and is information indicating, for example, sex, age, life group, and the like. The “life group” is a group that is classified based on, for example, a daily behavior situation or a living situation. “Body weight information” is information indicating the weight at the reference time, for example.
The daily fluctuation information recorded in the memory 12 is, for example, “coefficients k _{0 to} k ₄ ” related to the daily fluctuation curve represented by (Equation 1) described later. In this case, the coefficient table TBL is a table in which information (coefficient) for determining the daily fluctuation curve is associated with attribute information. Therefore, if the attribute information of a user is determined, a daily fluctuation curve suitable for the user can be created by referring to the coefficient table TBL.

The communication interface 14 is an interface that accepts external input. Specifically, as the communication interface 14, for example, a communication interface including a USB (Universal Serial Bus) controller or the like, or an IC (integrated circuit) card interface (for example, FeliCa (registered trademark)) for performing contactless communication using electromagnetic waves. )) And the like.
The timer unit 16 generates time information indicating the time and outputs it to the CPU 30.
The display unit 18 includes, for example, an LCD (Liquid Crystal Display) and the like, and outputs various information (for example, information on various setting items, information on operation guidance, information on energy consumption, information on body movement) output from the CPU 30. Etc.) is displayed.

The acceleration sensor 20 detects acceleration generated in the activity meter 1, generates body motion information that is an electrical signal corresponding to the acceleration, and outputs the body motion information to the CPU 30. The acceleration sensor 20 functions as a body motion detection unit that detects body motion information indicating the body motion of the user. The acceleration sensor 20 may be a one-dimensional acceleration sensor that detects acceleration in one direction, a two-dimensional acceleration sensor that detects acceleration in two directions orthogonal to each other, or three orthogonal to each other. It may be a three-dimensional acceleration sensor that detects the acceleration in the direction.
The operation unit 22 is a member for various operations (for example, information input operation and setting operation) by the user. The mode of the operation unit 22 is not particularly limited. For example, the operation unit 22 may be provided in any mode such as a button type operation unit or a touch panel type operation unit.

  The CPU 30 is a control unit that comprehensively controls each unit of the activity meter 1. FIG. 2 is a block diagram illustrating a main functional configuration of the CPU 30. The processing of each unit illustrated in FIG. 2 indicates each function realized by the CPU 30 reading a program from the memory 12 and executing each instruction code of the program. As shown in FIG. 2, the CPU 30 includes a user information setting unit 30-1, a daily fluctuation information specifying unit 30-2, a weight estimating unit 30-3, and a consumption energy calculating unit 30-4.

  The user information setting unit 30-1 sets attribute information and weight information related to the user. Specifically, the user information setting unit 30-1 gives the user information based on, for example, information input by an operation of the operation unit 22 by the user or information input from an external device or the like via the communication interface 14. Such attribute information and weight information are set. In other words, the user information setting unit 30-1 functions as an attribute information acquisition unit that acquires user attribute information together with the operation unit 22 and / or the communication interface 14, and a weight information acquisition unit that acquires user weight information. Function as.

  The daily fluctuation information identification unit 30-2 corresponds to the user attribute information and the weight information by referring to the coefficient table recorded in the memory 12 based on the attribute information set by the user information setting unit 30-1. Identify daily fluctuation information. In other words, the daily fluctuation information specifying unit 30-2 functions as a daily fluctuation information specifying unit that specifies the daily fluctuation information corresponding to the user attribute information with reference to the coefficient table TBL recorded in the memory 12.

  Here, an example of daily fluctuation information will be described in detail. FIG. 3 is a diagram illustrating an example of an approximate curve obtained by performing a curve regression on the daily fluctuation of the body weight. In the graph shown in FIG. 3, the value on the vertical axis represents the weight at each time point with respect to the maximum value when the maximum value (hereinafter referred to as “reference weight”) in the daily fluctuation of the weight is 100 (%). The percentage (%) is shown. The horizontal axis (x) indicates each time from the wake-up time to the wake-up time on the next day.

In the example shown in FIG. 3, an approximate curve (hereinafter referred to as “daily fluctuation curve”) indicating a change in body weight from the time when the subject wakes up to the time of wakeup on the next day is:
y = k ₄ * x ⁴ + k ₃ * x ³ + k ₂ * x ² + k ₁ * x + k ₀ (Formula 1)
It is expressed with the polynomial.
In (Expression 1), the value of y indicates the ratio (%) of the body weight at each time x when the reference body weight is 100 (%). In (Expression 1), the value of x indicates the difference Δt from the reference time when the time corresponding to the reference weight is the reference time Tp. That is, the daily fluctuation curve represented by (Expression 1) indicates the relationship between the difference Δt from the reference time Tp and the weight at the time corresponding to each difference Δt.
In this example, the time Tp, which is the time immediately after dinner, is used as the reference time. However, for example, other times such as the time Tg1 immediately after getting up and the time Tl immediately after lunch may be used as the reference time.

The time Tg1 shown in FIG. 3 is the time immediately after getting up. Time Tb is the time immediately after breakfast. Time Tl is the time immediately after lunch. Time Tp is the time immediately after dinner. Time Tg2 is the time immediately after getting up the next day. Here, the time Tp is the time when the weight becomes maximum in the daily fluctuation.
The number of data used for the curve regression for obtaining the daily fluctuation curve is N (in the example shown in FIG. 3, the first wake-up data at time Tg1, the breakfast data at time Tb, the lunch data at time Tl, the time Assuming that the dinner time data relating to Tp and the second rising time data relating to time Tg2 are 5), the daily fluctuation information is expressed as a (N-1) th order polynomial (fourth order polynomial in the example shown in FIG. 3). Is preferably obtained. However, the daily fluctuation curve may of course be obtained as a simpler polynomial in consideration of the calculation accuracy of the energy consumption required for the activity meter 1.

The body weight estimation unit 30-3 functions as a body weight estimation unit that estimates the body weight of the user during a period in which the user is moving based on the daily fluctuation curve and the body weight information of the user. For example, the weight estimation unit 30-3 is based on the daily fluctuation information specified by the daily fluctuation information specifying unit 30-2 and the user's weight information, and the user's weight at the body movement start time and the user at the body movement end time. Are calculated, and the average value is calculated. In this example, the average value calculated by the weight estimation unit 30-3 is estimated as “the weight of the user in the period during which body movement is occurring”.
The consumption energy calculation unit 30-4 is based on the weight of the user, which is the estimation result of the weight estimation unit 30-3, and the body motion information generated by the acceleration sensor 20 during a predetermined period in which the user was experiencing body motion. , And functions as an activity amount calculation unit for calculating the activity amount of the user in the predetermined period.

Hereinafter, with reference to the flowchart shown in FIG. 4, the calculation process of the energy consumption by the active mass meter 1 which concerns on this embodiment is demonstrated. FIG. 4 is a diagram illustrating a flowchart of energy consumption calculation processing by the activity meter 1 according to the present embodiment.
First, CPU30 sets the attribute information which concerns on the user of the said active mass meter 1 (step S1). That is, when attribute information related to the user is input by the operation of the operation unit 22 by the user, or when attribute information related to the user is input from an external device or the like via the communication interface 14, the CPU 30 The input attribute information is set as attribute information related to the user.

  Then, CPU30 sets the weight information which concerns on the user of the said active mass meter 1 (step S2). Prior to step S2, the activity meter 1 requests the user to input weight information indicating the weight at the “predetermined time”. Specifically, the CPU 30 may display the fact on the display unit 18 to notify the user, or notify the user in advance by an instruction manual or the like related to the activity meter 1. In step S <b> 2, the CPU 30 sets the input weight information as weight information indicating the weight of the user at “predetermined time”. In this example, the “predetermined time” is, for example, “PM 12:00”. However, the “predetermined time” is not limited to “PM 12:00” and may be any time.

Examples of the weight information input method include a method by an input operation using the operation unit 22 and a method of inputting from an external device through the communication interface 14.
When the processing in step S2 is completed, the CPU 30 refers to the coefficient table TBL recorded in the memory 12 and identifies the daily fluctuation information corresponding to the attribute information set in step S1 (step S3). Specifically, in step S3 in the present embodiment, CPU 30 specifies the coefficients k ₀ to k ₄ to determine the diurnal variation curve expressed by equation (1), to produce a diurnal variation curve according to the user .

Further, in step S3, CPU 30 by performing the following calculation, to calculate the maximum weight _{W p} is the weight of the user at the reference time Tp. Specifically, for example, using the weight W ₁₂ at 12 o'clock PM and the value of y corresponding to PM 12 o'clock on the generated daily fluctuation curve (ratio R ₁₂ (%)),
W _p : 100 = W ₁₂ : R ₁₂ (Formula 2)
The maximum weight _Wp is calculated from the proportional expression.
In this example, the “predetermined time” related to the weight information set in step S2 is “PM 12 o'clock”. However, the weight at the “predetermined time” is the weight W _pd and the “predetermined time” on the daily fluctuation curve is set. If the corresponding value of y is the ratio R _pd , (Equation 2) is
W _p : 100 = W _pd : R _pd (Formula 2 ′)
And generalized.

  By the way, when body motion occurs in the user, the acceleration sensor 20 detects acceleration generated in the activity meter 1, generates body motion information that is an electrical signal corresponding to the acceleration, and outputs the body motion information to the CPU 30. In other words, when body motion occurs in the user, the CPU 30 acquires body motion information generated and output by the acceleration sensor 20 in accordance with the body motion (step S4). Here, based on the daily fluctuation curve generated in step S3, the body motion information acquired in step S4, and the time information generated by the time measuring unit 16, the CPU 30 starts to generate body motion in the user. The body weight at the “movement start time” and the “body movement end time” at which the body movement ends is estimated (step S5). Specifically, the CPU 30 performs the following calculation in step S5.

<< When the body movement start / end time tx is a time before the reference time Tp >>
The CPU 30 calculates the difference Δt between the reference time (in this example, time Tp) and the body movement start / end time tx,
Δt = − | Tp−tx | (Formula 3)
Calculate as
<< When body movement start / end time tx2 is later than reference time Tp >>
The CPU 30 calculates the difference Δt between the reference time (in this example, time Tp) and the body movement start / end time tx,
Δt = | Tp−tx | (Formula 4)
Calculate as

The CPU 30 substitutes the value of Δt as the value of x in the identified daily fluctuation curve (the value of x in (Equation 1)), so that the value of y at the body motion start / end time tx (value of the ratio Rx) ) Is calculated. The above-described calculation is performed for the body motion start time ts and the body motion end time te, and the ratios Rs and Re are calculated for each. Then, the CPU 30 uses the maximum weight Wp and the ratio Rs as the weight w _s at the body movement start time ts,
w _s = W _p × Rs
As
Weight _{w e} in motion end time te, by using the maximum body weight _{W p} and the proportion Re,
w _e = _{W p} × Re
Calculate as

After calculating the weight _{w e} in body weight _{w s} body motion end time te in motion start time ts in step S5, CPU 30 calculates the energy consumption in accordance with the body movement information of the user (step S6). Specifically, the CPU 30 calculates energy consumption by the following calculation formula, for example. That is, the weight of the user is w, the magnitude of the acceleration detected by the acceleration sensor 20 (body motion information generated by the acceleration sensor 20) is a, and the arbitrarily set first coefficient and second coefficient are c1. , C2, the CPU 30 uses the energy consumption E as
E = w × a × c1 + c2 (Formula 5)
Calculate as Here, the user's weight w, may be used, for example the mean value of the weight w _s and weight w _e. That is,
_{w = (w s + w e} ) / 2 ... ( Equation 6)
W may be calculated as

That is, in this example, the CPU 30 calculates the first weight, which is the user's weight at the body movement start time, from the user's weight at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information. And a second calculation unit that calculates a second weight, which is the weight of the user at the body movement end time, from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information. The average value of the first body weight and the second body weight functions as an estimation unit that estimates the body weight of the user during a predetermined period in which the body motion has occurred in the user.
Incidentally, the energy consumption in this example, to estimate the average value of the weight w _e in body weight w _s body motion end time te in motion start time ts as the weight of a predetermined time period, an activity amount of a user by using the E is calculated, but the estimated weight may be at a certain time within a predetermined period. For example, the weight w _s in motion start time ts may be estimated as a weight of the user in a predetermined period, or may estimate the weight w _e in body movement end time te as the user's weight during a predetermined period .

  According to the activity meter 1 according to the present embodiment, the weight of the user during the period in which the user is moving is estimated based on the daily fluctuation information corresponding to the attribute information and the weight information of the user. This estimated weight is a weight calculated in consideration of the daily fluctuation information. Therefore, by using this estimated weight in the calculation of energy consumption, the energy consumption can be calculated with high accuracy. Therefore, according to the activity meter 1 according to the present embodiment, deterioration of the calculation accuracy of the energy consumption due to the daily fluctuation of the user's weight is prevented, and high calculation accuracy is realized.

Note that the values of the first coefficient c1 and the second coefficient c2 may be set arbitrarily, but it is preferable to set different values depending on sex, age, and the like. As attribute information, in addition to gender and age, for example, information related to height, lean mass, and the like is included, and in consideration of such information, the first coefficient c1 and the second coefficient c2 are set. The calculation accuracy of can be further improved.
As described above, according to the present embodiment, the activity meter that improves the calculation accuracy of energy consumption by preventing the deterioration of the calculation accuracy of energy consumption due to the daily fluctuation of the weight of the person being measured is provided. Can be provided.

The present invention has been described above based on the embodiments. However, the present invention is not limited to the above-described examples, and it goes without saying that modifications and applications are possible within the scope of the present invention.
[First Modification]
In order to avoid redundant description, differences from the above-described embodiment will be described, and descriptions of configurations, operations, and effects similar to those of the activity meter according to the above-described embodiment will be omitted.
In the above-described embodiment, as shown in FIG. 3, the body weight is estimated using an approximate curve (daily fluctuation curve) formed by regression of the daily fluctuation, but in this modified example, the daily fluctuation is curved regression. As shown in FIG. 5, a straight line formed by connecting coordinates related to each data (first wake-up data, breakfast data, lunch data, supper data, and second wake-up data) Used to estimate FIG. 5 is a diagram illustrating an example of daily fluctuation information in the activity meter according to the modification.

In this modification, the daily fluctuation is expressed by a plurality of linear expressions. That is, in the example shown in FIG. 5, the first straight line L1 connecting the coordinates of the first wake-up data and the breakfast data is represented by y = ax ₁ + b (Expression 7)
age,
A second straight line L2 connecting the coordinates of the breakfast data and the lunch data is represented by y = cx ₂ + d (Equation 8)
age,
A third straight line L3 connecting the coordinates of the lunchtime data and the dinnertime data is represented by y = ex ₃ + f (Equation 9)
age,
A fourth straight line L4 connecting the coordinates of the dinner data and the coordinates of the second wake-up data is represented by y = gx ₄ + h (Equation 10)
age,
Information indicating the relationship between the “ratio” and the “time” represented by the first straight line L1 to the fourth straight line L4 is referred to as daily fluctuation information.

Here, the value of y indicates the ratio (%) of the body weight at each time with respect to the reference weight, where the reference weight is 100 (%). x _{1 to} x ₄ indicate a difference Δt that is a time difference from the reference time Tp, and for the period from immediately after the first wake-up to immediately after breakfast, the difference Δt is substituted into x1 in (Equation 7), and breakfast the difference Δt is for the period until just after after-lunch substituted in x ₂ in equation (8), for the period until just after lunch after-dinner substituted into x ₃ the difference Δt in equation (9), dinner immediately after - for a period from immediately after the second wake-up is substituted into x ₄ the difference Δt in equation (10).
According to the first modification, it is possible to provide an activity meter that has the same effect as the activity meter according to the above-described embodiment.

[Second Modification]
In the activity meter 1 of the above-described embodiment, the user is prompted to input weight information at a predetermined time, but the present invention is not limited to this, and the time when the weight and the weight are measured from an external device. May be acquired via a communication unit. Such an external device is a scale. For example, a USB (Universal Serial Bus) interface may be provided as the communication interface 14 of the activity meter 1 and connected to the weight scale via a USB connector. In this case, when the activity meter 1 is connected to the weight scale, weight information including the weight and the time when the weight is measured may be transmitted from the weight scale to the activity meter 1. Further, the weight information may be measured in the past with a weight scale, or may be measured in real time with the weight scale and the activity meter 1 connected. Good.

[Third Modification]
In the embodiment described above, the daily fluctuation information generated based on the general subject data is used. However, the present invention is not limited to this, and the daily day relating to a specific individual who is the user of the activity meter 1 It may be fluctuation information.
In the case of such a configuration, the activity meter 1 collects user weight information associated with time information from a weight scale capable of transmitting and receiving data via the communication interface 14, and provides user-specific daily fluctuation information. It may be generated.

[Fourth Modification]
In the embodiment described above, the daily fluctuation information is stored in advance in the coefficient table TBL of the memory 12 and is not updated. However, the present invention is not limited to this, and the contents of the coefficient table TBL are updated. May be.
For example, the health management system 100 shown in FIG. 6 includes a plurality of activity meters 1A, 1B, 1C, a plurality of weight scales 2A, 2B, 2C, and a plurality of terminal devices 3A, 3B, 3C, and the server. And a device 4. The server device 4 includes a plurality of activity meters 1A, 1B, 1C, a plurality of weight scales 2A, 2B, 2C, and a plurality of terminal devices 3A, 3B via a plurality of terminal devices 3A, 3B, 3C,. , 3C... Can transmit and receive data. The terminal devices 3A, 3B, 3C... Correspond to so-called smartphones and personal computers. The server device 4 collects activity amount information from each of the activity meter 2A, 2B, 2C... And collects weight information from each of the weight meters 2A, 2B, 2C. And according to the request | requirement from a user, the said user's activity amount, the log | history of a weight, the advice regarding a diet, and the advice regarding health can be transmitted to terminal device 3A, 3B, 3C ... now.

When receiving the provision of the service from the server device 4, the user inputs attribute information indicating biological attributes such as age and sex in advance using the terminal devices 3A, 3B, 3C. The server device 4 manages a user ID that uniquely identifies a user and attribute information in association with each other.
Moreover, the weight information collected from each of the weight scales 2A, 2B, 2C,... Includes the weight and the time when the weight is measured. The server device 4 generates new daily fluctuation information as general subject data based on the collected weight information. Then, when collecting activity amount information from the activity meter 1A, 1B, 1C... Via the plurality of terminal devices 3A, 3B, 3C..., New daily fluctuation information is transferred to the activity meter 1A, 1B, 1C. And update the contents of the coefficient table TBL. Thereby, the total number of daily fluctuation information as general subject data supplied to the activity meter 1 can be increased. By configuring in this way, it is possible to specify the daily fluctuation information having higher suitability for each user in the specification of the daily fluctuation information in step S3 described above, and the calculation accuracy of energy consumption is further improved. .
In the example described above, the plurality of activity meters 1A, 1B, 1C... And the plurality of weight scales 2A, 2B, 2C... Are connected to the server device 4 via the plurality of terminal devices 3A, 3B, 3C. As shown in FIG. 7, the plurality of activity meters 1A, 1B, 1C... And the plurality of weight scales 2A, 2B, 2C. May be.

  Moreover, the server apparatus 4 produces | generates the daily fluctuation information which concerns on the said user based on the weight information collected for every user, This daily fluctuation information is delivered with respect to each activity meter 1A, 1B, 1C .... Also good. In this case, since it is possible to use the daily fluctuation information unique to the user, it is possible to specify the daily fluctuation information having higher suitability for each user in the identification of the daily fluctuation information in step S3 described above. Therefore, the calculation accuracy of energy consumption can be further improved.

[Fifth Modification]
In the above example, in order to calculate the energy consumption E,
E = w × a × c1 + c2 (Formula 5)
In the setting of the first coefficient c1 and the second coefficient c2, gender and age are included as attribute information. In this modification, the calculation accuracy of energy consumption can be further improved by modifying (Equation 5) as follows.
E = w * a * c1 + f * c2 + h * c3 + c4 (Formula 5 ')
“F” is a coefficient indicating information related to the lean body mass of the user. “H” is a coefficient indicating information related to the height of the user. Further, c3 is a third coefficient, which is a coefficient indicating other arbitrary information related to the user. c4 is a fourth coefficient, which is a coefficient indicating other arbitrary information related to the user.

  Further, the above-described embodiments include inventions at various stages, and various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements. For example, even if some constituent requirements are deleted from all the constituent requirements shown in the embodiment, the problem described in the column of the problem to be solved by the invention can be solved, and the effect described in the column of the effect of the invention can be achieved. In the case of being obtained, a configuration from which this configuration requirement is deleted can also be extracted as an invention.

DESCRIPTION OF SYMBOLS 1 ... Activity meter, 12 ... Memory, 14 ... Communication interface, 16 ... Time measuring part, 18 ... Display part, 20 ... Accelerometer, 22 ... Operation part, 30 ... CPU.

Claims (8)

A storage unit that stores the daily fluctuation information related to daily fluctuations in weight, the attribute information related to the attributes of the living body, and the weight information indicating the weight;
An attribute information acquisition unit for acquiring the attribute information of the user;
A weight information acquisition unit for acquiring weight information related to the weight of the user;
With reference to the storage unit, a daily fluctuation information specifying unit that specifies the daily fluctuation information corresponding to the attribute information of the user;
Based on the daily fluctuation information specified by the daily fluctuation information specifying unit and the weight information of the user, a weight estimation unit that estimates the weight of the user at a predetermined time;
A body motion detecting unit for detecting body motion information indicating the body motion of the user;
Based on the weight of the user estimated by the weight estimation unit and the body movement information detected by the body movement detection unit in a predetermined period including the predetermined time within the period, the user activity in the predetermined period An activity amount calculator for calculating the amount;
An activity meter characterized by comprising. The weight information indicates the weight of the user at a reference time,
The weight estimating unit estimates the weight of the user at the predetermined time from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information.
The activity meter according to claim 1. The predetermined period is a period from a start time to an end time,
The predetermined time is the start time and the end time,
The weight estimation unit includes
A first calculation unit that calculates a first weight that is the weight of the user at the start time from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information;
A second calculation unit that calculates a second weight, which is the weight of the user at the end time, from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information;
An estimation unit that estimates an average value of the first weight and the second weight as the weight of the user in the predetermined period;
The activity meter according to claim 2, further comprising: The predetermined period is a period from a start time to an end time,
The predetermined time is a start time;
The weight estimation unit includes
A calculating unit that calculates the weight of the user at the start time from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information;
An estimation unit that estimates the weight calculated by the calculation unit as the weight of the user in the predetermined period;
The activity meter according to claim 2, further comprising: The predetermined period is a period from a start time to an end time,
The predetermined time is an end time,
The weight estimation unit includes
A calculating unit that calculates the weight of the user at the end time from the weight of the user at the reference time based on the daily fluctuation of the weight indicated by the daily fluctuation information;
An estimation unit that estimates the weight calculated by the calculation unit as the weight of the user in the predetermined period;
The activity meter according to claim 2, further comprising: When the maximum value of the user's weight in the daily fluctuation is a reference weight,
The daily fluctuation information indicates the relationship between the time of the user's weight relative to the reference weight and time,
The activity meter according to any one of claims 1 to 5, characterized in that: A communication unit that communicates with an external device;
The weight information includes information indicating the reference time,
The weight information acquisition unit can acquire the weight information from the external device via the communication unit.
The activity meter according to any one of claims 2 to 6, wherein the activity meter. The attribute information includes at least any one of information indicating the gender of the user, information indicating the age of the user, and information indicating a living situation. The activity meter according to item 1.

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