JP2017189267A - Activity meter - Google Patents

Abstract

PROBLEM TO BE SOLVED: To solve the problem with a conventional activity meter that it is difficult to acquire an accurate activity amount since an acceleration in a horizontal direction is small as compared with an acceleration in a gravity direction in a motion centering on a vertical motion, and that it is difficult to perform accurate measurement when an activity meter is worn on an arm.SOLUTION: An activity meter includes a triaxial acceleration sensor 10 for detecting a body motion and outputting a triaxial acceleration signal, first filter means 20 for inputting the triaxial acceleration signal output from the triaxial acceleration sensor 10, and outputting a primary step signal, first calculation means 30 for inputting the primary step signal and outputting a composite acceleration signal, second filter means 40, second calculation means 50, region detection means 90 for detecting a region where the activity meter is worn, step detection means 60, motion data calculation means 70, and communication means 80.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an activity meter.

  In order to prevent diets and lifestyle-related diseases, products for measuring the daily consumption power loli are on the market, and the technology for this is disclosed in Patent Document 1 below.

  The prior art disclosed in Patent Document 1 determines an action scene from acceleration in a gravitational direction, acceleration in a horizontal direction, and a norm of each acceleration of an acceleration detection means attached to a person.

The outline of the prior art disclosed in Patent Document 1 will be described with reference to FIG.
FIG. 5 shows a block diagram of the activity meter disclosed in Patent Document 1, which is obtained by the acceleration detection means 300 that is worn on the human body and detects each acceleration in the gravity direction and the horizontal direction, and the acceleration detection means 300. An action scene determination unit 400 that determines a human action scene based on the acceleration; an activity amount calculation unit 500 that calculates an activity amount from the acceleration obtained by the acceleration detection unit 300 based on a determination result by the action scene determination unit 400; The action scene determination unit 400 includes a display unit 600 and a storage unit 700. The action scene determination unit 400 includes a ratio between the acceleration in the gravity direction and the acceleration in the horizontal direction obtained by the acceleration detection unit 300, and each acceleration obtained by the acceleration detection unit 300. It is configured to determine a human action scene based on a norm having a vector component.

JP 2008-246181 A

  In the activity meter of the prior art disclosed in Patent Document 1, the horizontal acceleration is smaller than the gravitational direction in, for example, a jumping movement or a so-called running machine, where the vertical movement is the center, the activity form It becomes difficult to measure the amount of activity accurately. When a pedometer is worn on the arm, the ratio between the acceleration in the gravitational direction and the acceleration in the horizontal direction changes frequently, making it difficult to determine the action scene of the person and to measure the amount of activity accurately.

  The present invention solves the above-mentioned problems of the prior art, and also for movements that move in the vertical direction, such as jumping and so-called running machines, and for movements that move horizontally such as normal walking and running. It is another object of the present invention to provide an activity meter capable of accurately measuring an activity amount even when worn on an arm.

  In the following description, the activity consumption power loli is defined as all energy consumption (unit: kcal) generated by the movement of the body.

  In order to solve the above problems, the activity meter according to the present invention employs the following configuration.

  The activity meter according to the present invention includes a three-axis acceleration sensor that detects a body motion and outputs a three-axis acceleration signal including an x-direction signal, a y-direction signal, and a z-direction signal, and inputs the three-axis acceleration signal. A first filter means for outputting a next step signal; a first computing means for inputting the primary step signal to output a synthetic acceleration signal; and a long-band signal and a medium-band signal for inputting the synthetic acceleration signal. A second filter means having a filter c section, a filter d section and a filter e section for outputting a short band signal and a second step signal by inputting the long band signal, the middle band signal and the short band signal, respectively. A second calculating means for outputting, a part detecting means for inputting a primary step signal output from the first filter means and outputting a part signal, and a secondary step signal output by the second calculating means; Site inspection The part signal output by the means is input, the step detection means for outputting the tertiary step signal, the part signal output by the tertiary step signal and the part detection means is input, and the activity consumption power loli data is obtained. It is characterized by comprising exercise data calculation means for outputting exercise data including communication and communication means.

  The part detecting means includes a ranking means, an identification means, and a discrimination means, and the ranking means increases the amplitude of each of the x-direction signal, the y-direction signal, and the z-direction signal constituting the primary step signal. Evaluation data consisting of rank data ranked first and second in order and amplitude difference data between the first and second ranks is output, and the identification means inputs the evaluation data output by the ranking means When the order of the rank data is changed and the amplitude difference data exceeds a predetermined level, an identification signal is output, and the determination means measures the elapsed time each time the identification signal from the identification means is input. It is desirable that a non-armor signal is output as a part signal when a predetermined time or longer, and an armor signal is output if the elapsed time is less than a predetermined time.

  Further, the step detection means includes a frequency threshold value for evaluating the number of times of the secondary step signal and an amplitude threshold value for evaluating the amplitude of the secondary step signal. It is preferable that the exercise data calculation means is configured to change the calculation of the activity consumption power loli data of the exercise data when the arm wearing signal is input.

  Further, the second calculation means selects any one of the long band signal, the middle band signal and the short band signal according to the value of the various exercise data output from the movement data calculation means and outputs it as a secondary step signal. It is desirable to make it so.

  Furthermore, it is desirable that the communication means has a short-range communication function based on the technical standard defined in NFCIP-2.

  According to the present invention, an activity that can accurately measure the amount of activity, even for movements that are centered on vertical movements, movements that involve horizontal movement, and when an activity meter is worn on the arm. A meter can be provided.

It is a block diagram which shows the whole structure of the active mass meter which concerns on this invention. It is a block diagram which shows the structure of a site | part detection means among the active mass meters which concern on this invention. It is sectional drawing which shows the structure of the active mass meter which concerns on this invention. It is an external view which shows the structure of the key security management system comprised with the active mass meter which concerns on this invention, and a personal computer. It is a block diagram which shows the structure of the conventional active mass meter.

Hereinafter, a specific configuration of the activity meter according to the present invention will be described in detail with reference to FIGS. 1 to 3.
[Explanation of block diagram]
The structure of the active mass meter 1 is demonstrated using FIG.1 and FIG.2. FIG. 1 is a block diagram showing the overall configuration of an activity meter 1 according to the present invention, and FIG. 2 is a block diagram showing the configuration of a part detecting means in the activity meter according to the present invention.

  In FIG. 1, an activity meter 1 of the present invention includes a triaxial acceleration sensor 10 that detects a body motion and outputs a triaxial acceleration signal Sa including an x direction signal, a y direction signal, and a z direction signal, and a triaxial acceleration. The first filter means 20 that receives the signal Sa and outputs the primary step signal Sn, the first calculation means 30 that receives the primary step signal Sn and outputs the combined acceleration signal Sg, and the combined acceleration signal Sg The second filter means 40 including the filter c unit 41, the filter d unit 42, and the filter e unit 43, and the long band signal Sf21, the middle band signal Sf22, and the short band signal Sf23, respectively, The second calculation means 50 that inputs Sf21, the middle band signal Sf22, or the short band signal Sf23 and outputs the secondary step signal Sk, and the primary that the first filter means 20 outputs. The part detection means 90 for inputting the step signal Sn and outputting the part signal Suc, the secondary step signal Sk output by the second calculation means 50, and the part signal Suc output by the part detection means 90 are input 3 It comprises step detecting means 60 for outputting the next step signal Ss, movement data calculating means 70 for inputting the third step signal Ss and outputting the movement data Ssc, and communication means 80.

  For the sake of explanation, FIG. 1 also shows a personal computer 81 and a reader / writer 82, which will be described later, and a communication magnetic field M, which is a communication medium, by a broken line.

  The triaxial acceleration sensor 10 detects acceleration in the triaxial direction, that is, x, y, and z directions generated according to the movement of the body of the user carrying the activity meter, and outputs a triaxial acceleration signal Sa. The triaxial acceleration signal Sa has three components: an x direction signal Sax, a y direction signal Say, and a z direction signal Saz. Note that each of the x-direction signal Sax, the y-direction signal Say, and the z-direction signal Saz is a numerical value of 0-255 indicating the amplitude of each direction signal, and the absolute value of the output of the triaxial acceleration sensor 10 is calculated using an electronic circuit technique. It is converted into a numerical value.

  The first filter means 20 performs a moving average of the triaxial acceleration signals Sa of 6 data or more and outputs them as a primary step signal Sn.

  The first calculating means 30 squares and sums the x-direction signal Snx, the y-direction signal Sny, and the z-direction signal Snz, which are components of the primary step signal Sn, and then sums the sum or the square root of the sum. Is output as a synthesized acceleration signal Sg.

The second filter unit 40 includes a filter c unit 41, a filter d unit 42, and a filter e unit 43.
The filter c unit 41 detects a slow walk of less than about 90 steps per minute and outputs it as a long-band signal Sf21.

The filter d unit 42 detects walking at a normal speed of approximately 90 to 140 steps per minute and outputs it as a middle band signal Sf22.
Further, the filter e unit 43 detects an early walking or running operation exceeding approximately 140 steps per minute and outputs it as a short band signal Sf23.

  The second calculation means 50 inputs exercise data Ssc from the exercise data calculation means 70 described later, and a user among the long band signals Sf21 to Sf23 calculated by the second filter means 40. Is selected as the secondary step signal Sk.

  Next, the structure of the site | part detection means 90 is demonstrated using FIG. As shown in FIG. 2, the part detecting means 90 includes a ranking means 91, an identifying means 92, and a discriminating means 93. The part detecting means 90 receives a primary step signal Sn output from the first filter means 20 and receives the part. The signal Suc is output.

  The ranking unit 91 includes rank data S1j in which the amplitudes of the x-direction signal Snx, the y-direction signal Sny, and the z-direction signal Snz constituting the primary step signal Sn are ranked first and second in descending order. Evaluation data S1 including amplitude difference data S1d, which is the difference between the amplitude of the first signal and the amplitude of the second signal, is output.

  For example, if the rank data S1j is the amplitude of the z-direction signal Snz> the amplitude of the x-direction signal Snx> the amplitude of the y-direction signal Sny, the first-order signal and 2 are set as S1j = (z, x). This is data in a symbol string format in which signals of positions are arranged in order using xyz symbols. Of course, other formats may be used as long as the order of amplitude of each signal can be determined.

  The amplitude difference data S1d is a difference between the amplitude of the first signal and the amplitude of the second signal in the evaluation data S1. For example, if S1j = (z, x) and Snz = 128 and Snx = 57, then the amplitude difference data S1d = 128−57 = 71.

  The identification unit 92 receives the evaluation data S1 output from the ranking unit 91, the first signal of the rank data S1j constituting the evaluation data S1 is changed, and the amplitude difference data S1d exceeds a predetermined level. When is satisfied, an identification signal S2 is output.

  For example, the content of the rank data S1j changes from S1j = (z, x) to S1j = (x, z), or S1j = (y, z), and the first rank signal changes from the z direction to the x direction or the y direction. When it is determined that the amplitude 羞 data S1d exceeds S1d = 71 and exceeds a predetermined level, an identification signal S2 is output. The predetermined level is preset in the range of about 10-30.

  The discriminating means 93 starts time measurement from 0 second each time the identification signal S2 from the discrimination means 92 is input, and when the elapsed time reaches a predetermined time or more, the non-arm wearing signal Sucn indicating that the arm is not worn is a part signal. Output as Suc.

  If the identification signal S2 is frequently input from the identification unit 92 and the elapsed time does not reach the predetermined time, the determination unit 93 outputs the arm wearing signal Sucy indicating that the arm is worn as a part signal Suc. Output as.

Returning to FIG. 1, the overall configuration of the activity meter 1 will be described.
As shown in FIG. 1, the step detection means 60 outputs a tertiary step signal Ss from the secondary step signal Sk from the second calculation means 50 and the part signal Suc from the part detection means 90. More specifically, the step detection unit 60 includes a frequency threshold value and an amplitude threshold value for evaluating the number and amplitude of the secondary step signal Sk from the second calculation unit 50, and the secondary step signal Sk is set to these two threshold values. From the comparison result and the part signal Suc from the part detection means 90, the user's wearing part of the activity meter 1 is discriminated and it is judged whether or not the user has clearly performed the step or the body movement action. To do. When the user recognizes that a step or body movement has been performed, a tertiary step signal Ss is output.

  More specifically, when the arm wearing signal Sucy is input as the part signal Suc from the part detecting unit 90 to the step detecting unit 60, that is, when it is determined that the user wears the activity meter 1 on the arm. The frequency threshold value of the step detection means 60 is changed to twice the previous value, and the amplitude threshold value of the step detection means 60 is changed to 1.5 times the previous value. The degree of change of the number threshold and the amplitude threshold is not limited to this and may be other values. The reason why the number threshold and the amplitude threshold of the step detection unit 60 are changed is to reduce the detection sensitivity of the step detection unit 60 and prevent erroneous counting due to noise.

  The exercise data calculation means 70 outputs a tertiary step signal Ss output from the step detection means 60 by a user's walking or jogging operation, a part signal Suc from the part detection means 90, and a communication means 80 described later. The personal data Kd to be inputted is inputted, and the exercise data Ssc is outputted. The personal data includes elongation, weight, age, sex, and the like.

The exercise data Ssc mainly includes the number of steps during walking or jogging, walking or running time, walking or running distance, exercise intensity, exercise time, activity consumption power loli data, and basal metabolic rate, but is not limited thereto.
When the arm wear signal Sucy is input as the part signal Suc from the part detection unit 90, that is, when it is determined that the wearing part of the activity meter 1 is the arm, the exercise data calculating unit 70 changes the calculation method of the activity consumption power loli data. The activity consumption power loli data is reduced by a predetermined percentage. The predetermined ratio is in the range of 10% to 50%. The reason for changing the calculation method of the activity consumption power loli data is to prevent the activity consumption power loli data from being excessively calculated due to the swing of the arm.

  As described in the description of FIG. 3, the communication means 80 includes a communication chip 80c, an antenna 80a, and a lead wire 80t. The communication chip 80c is a communication chip generally known as an NFC (Near Field Communication) communication method. The communication means 80 performs data communication with an external information terminal such as a personal computer, a tablet, or a smartphone through the league writer 82 shown in FIG. 4 to be described later, sends the user's personal data to the activity meter 1, and the user's walking Alternatively, the exercise data Ssc in jogging or housework or labor is transmitted to the external information terminal.

[Description of structure]
Next, the structure of the activity meter 1 of the present invention will be described with reference to FIG.
FIG. 3 is a cross-sectional view showing the structure of the activity meter 1. The activity meter 1 is housed in a box made up of an upper case 241 and a lower case 242. Note that the upper case 241 and the lower case 242 are not particularly shown, but are fixed by a set screw or the like via welding or waterproof packing, and have a waterproof structure. An antenna 80a is attached to the inner surface of the upper case 241.

  The button battery 130 is mounted on one surface of the circuit board 210 using battery holding springs 131 and 132, and the three-axis acceleration sensor 10, the signal processing circuit 213, and the communication chip 80c are mounted on the other surface. . The signal processing circuit 213 is a one-chip microcomputer that performs functions from the first filter means 20 to the motion data calculation means 70 shown in FIG.

  The antenna 80a is a flexible printed circuit board in which a copper foil circuit pattern is formed in a coil shape, but can also be realized by winding a thin conductive wire in a coil shape. The antenna 80a and the communication chip 80c are connected via a lead wire 80t. As the antenna 80a, a coiled antenna pattern may be formed on the circuit board 210 using the copper foil of the circuit board 210.

[Description of operation]
Next, operation | movement of the active mass meter 1 is demonstrated based on FIG.1, FIG2 and FIG.4.
FIG. 4 is an external view showing a configuration of a key integrity management system including the activity meter 1, a personal computer as the external information terminal 81, and a reader / writer 82.

  In FIG. 4, the user inputs personal data including height, weight, age, sex, and the like into the activity meter 1 using a personal computer.

  After inputting the personal data, the user wears the activity meter 1 on his / her waist (not shown), and performs activities such as walking and jogging, and housework.

  When the user starts an activity, as shown in FIG. 1, the triaxial acceleration sensor 10 outputs a triaxial acceleration signal Sa, and the first filter means 20 averages the triaxial acceleration signal Sa over a predetermined time. Output as the primary step signal Sn.

  The first computing means 30 squares and sums the x-direction signal Snx, the y-direction signal Sny and the z-direction signal Snz constituting the signal of the primary step signal Sn, and then sums the sum or the square root of the sum. It outputs as a synthetic acceleration signal Sg. Therefore, even when the user performs a motion that involves movement such as walking or jogging, or when the user performs a centering motion that does not involve movement such as a jumping motion, the change in acceleration caused by the movement of the body is in the x direction. It occurs in at least one of the signal Snx, the y-direction signal Sny, and the z-direction signal Snz.

  Next, the second filter means 40 discriminates the speed of the step or the body movement operation based on the synthesized acceleration signal Sg. For example, in the case of walking or jogging, the values of the long band signal Sf21 to the short band signal Sf23 change according to the pitch. As an example, when the user walks at an intermediate pitch of approximately 120 steps per minute, the value of the medium band signal Sf22 is large and the values of the other long band signals Sf21 and short band signals Sf23 are small.

  When the user walks at a low speed of approximately 80 steps per minute, the value of the long band signal Sf21 is large and the values of the medium band signal Sf22 and the short band signal Sf23 are small.

  In this way, the magnitudes of the long band signal Sf21 to the short band signal Sf23 change according to the speed of walking or jogging by the user, and are input to the second computing means 50.

  Next, the second calculating means 50 inputs the long band signal Sf21 to the short band signal Sf23 from the second filter means 40 and the motion data Ssc from the motion data calculating means 70 to be described later. Any one of the signals Sf21 to Sf23 is selected and is output as the secondary step signal Sk. When there is no data at the beginning of the exercise, the middle band signal Sf22 is selected by the function built in the second calculating means 50 and is output as the secondary step signal Sk.

  The secondary step signal Sk output from the second calculation means 50 is basic data for recognizing movements such as walking and jogging from the movement of the user's body captured by the acceleration sensor 10 of the activity meter 1. When the user wears the activity meter 1 on the waist, the secondary step signal Sk is a stable waveform with little change in waveform over time, and the user wears the activity meter 1 on the arm. In this case, acceleration due to the swinging direction and swing direction of the arm is applied, so that the secondary step signal Sk becomes an unstable waveform with a large waveform change in time series.

  Next, the operation of the site detection means 90 will be described.

[Operation when worn on waist]
First, a case where the user wears the activity meter 1 on the waist will be described.
First, an example of the wearing posture of the activity meter 1 is defined. In other words, in the state of being initially worn on the waist, the direction that the activity meter 1 recognizes as the z direction is the direction of gravity, and the direction that the activity meter 1 recognizes as the x direction is the direction of walking or jogging of the user. It is assumed that the direction that the quantity meter 1 recognizes as the y direction is a direction that is perpendicular to and horizontal to the user's walking or jogging direction. In this case, if a general pedestrian is walking or jogging, the magnitude relationship between the x-direction signal Snx, the y-direction signal Sny and the z-direction signal Snz of the primary step signal Sn output by the first filter means 20 is as follows. Gravity acceleration is the largest, and the next is the body traveling direction during walking or jogging or the direction perpendicular and horizontal to the body traveling direction during walking or jogging, so Snz>Snx> Sny or Snz>Sny> Snx The signal is the z direction of gravity, and this magnitude relationship does not change unless the user moves the body extremely.
Although the posture of the active mass meter 1 has been described with a specific example, the same applies to other postures.

  The ranking means 91 of the part detecting means 90 is ranked first in descending order of the amplitudes of the x-direction signal Snx, the y-direction signal Sny, and the z-direction signal Snz of the primary step signal Sn output from the first filter means 20. Ranking data S1j ranked in the second place is output, but if the activity meter 1 is attached to the waist, the signal with the largest amplitude is fixed in the z direction, and the first place signal in the ranking data S1j is replaced. Therefore, the identification unit 92 does not output the identification signal S2.

  Then, the determination means 93 continues the time measurement because the identification signal S2 from the identification means 92 is not input, and as a result, the elapsed time becomes equal to or longer than the predetermined time, and the determination means 93 indicates that the part signal Suc is not wearing the arm. A non-wearing signal Sucn is output, and this non-arming signal Sucn is input to the step detecting means 60.

  The step detection means 60 receives the non-arm wearing signal Sucn from the discrimination means 93 and does not change the frequency threshold value and the amplitude threshold value of the step detection means 60, and uses the initial frequency threshold value and the amplitude threshold value to change the secondary step signal. When Sk is evaluated and it is recognized that the user has performed a step or body motion, a tertiary step signal Ss in a state where the activity meter 1 is worn on the waist is output.

[Operation when worn on arm]
Next, a case where the user changes the wearing part of the activity meter 1 from the waist to the arm will be described.
First, the example about the mounting posture of the active mass meter 1 is prescribed | regulated. That is, the posture in which the activity meter 1 is worn on the arm is, for example, in a state where the user is stationary, and the z direction and the gravity direction of the three-axis acceleration sensor 10 of the activity meter 1 are the same. Assume that the jogging direction is the same as the x direction, and the direction perpendicular to and horizontal to the user's walking or jogging direction is the same as the y direction.
In this case, when the user starts walking or jogging, acceleration due to the swinging direction of the arm or the swinging direction is applied in the x direction or the y direction. Therefore, the x-direction signal Snx of the primary step signal Sn and the walking step or jogging step The magnitude relationship between the y-direction signal Sny and the z-direction signal Snz frequently changes.

  Then, the ranking means 91 of the site detecting means 90 ranks the amplitudes of the x-direction signal Snx, the y-direction signal Sny, and the z-direction signal Snz of the primary step signal Sn in the descending order of the first and second ranks. Although the rank data S1j is output, since the active site of the active mass meter 1 is the arm, the acceleration sensor 10 is subjected to acceleration depending on how and how the arm is swung, and as a result, the first rank signal of the rank data S1j is frequently changed. The amplitude difference data S1d of the evaluation data S1 output by the ranking unit 91 frequently exceeds a predetermined level. As a result, the identification unit 92 frequently outputs the identification signal S2.

  Since the identification signal S2 is frequently input from the identification means 92, the determination means 93 is frequently repeated from 0 seconds and the elapsed time does not reach a predetermined time. The arm wearing signal Sucy indicating this is output as the part signal Suc and input to the step detecting means 60. When the arm detection signal Sucy is input, the step detection means 60 changes the number of times value and the amplitude threshold to 2 times and 1.5 times from the initial values, respectively.

  Then, the step detecting means 60 evaluates the secondary step signal Sk based on the changed number of times threshold value and the amplitude threshold value. When the step detecting means 60 recognizes that the user has performed the step or the body movement operation, the activity meter 1 is worn on the arm. The tertiary step signal Ss is output. Since the detection sensitivity of the step detection unit 60 is lowered by changing the number threshold and the amplitude threshold of the step detection unit 60, the influence of the swinging direction and swinging direction of the arm when the user wears the activity meter 1 on the arm is minimized. It can be suppressed to the limit.

  Next, by the exercise data calculation means 70, from the tertiary step signal Ss, the personal data Kd, and the part signal Suc, the number of steps during walking or jogging, running time, walking distance, exercise intensity, exercise time, activity consumption power loli data. Data relating to the basal metabolic rate is output as exercise data Ssc and transmitted to the external information terminal by the communication means 80. When it is determined that the activity meter 1 is worn on the arm, the activity consumption power loli data is reduced by a predetermined rate.

  Further, the exercise data calculation means 70 inputs the exercise data Ssc to the second calculation means 50. The second calculation means 50 selects any one of the long band signal Sf21 to the short band signal Sf23 input from the second filter means 40 based on the input motion data Ssc. When the user walks at a pitch of approximately 120 steps per minute, the middle band signal Sf22 is selected.

  As described above, the activity meter according to the present invention includes the part detection means 90 for discriminating the wearing part of the activity meter 1, and when the part detecting part 90 determines that the wearing part is an arm, Two kinds of threshold values, which are judgment criteria for recognizing walking and jogging, are changed to improve the accuracy of recognizing walking and jogging, and an active meter with high calculation accuracy can be realized by preventing excessive calculation of activity consumption power loli.

1: Activity meter 10: Three-axis acceleration sensor 20: First filter means 30: First calculation means 40: Second filter means 41: Filter c part 42: Filter d part 43: Filter e part 50: First 2 calculating means 60: step detecting means 70: motion data calculating means 80: communication means 80a: antenna 80c: communication chip 80T: lead wire 81: external information terminal 82: reader / writer 90: part detecting means 91: ranking means 92 : Discriminating means 93: Discriminating means 130: Button battery 131: Battery holding spring 132: Battery holding spring 210: Circuit board 213: Signal processing circuit 241: Upper case 242: Lower case 213: Signal processing circuit 300: Acceleration detecting means 400: Action scene determination means 500: activity amount calculation means 600: display means 700: storage means Kd: personal data Sa: triaxial acceleration signal Sax, Snx: x direction signal Say, Sny: y direction signal Saz, Snz: z direction signal Suc: part signal Sucy: arm wearing signal Sucn: non-arm wearing signal Sl: evaluation data Slj: rank data Sld: amplitude difference data S2 : Identification signal Sn: primary step signal Sf21: long-band signal Sf22: middle-band signal Sf23: short-band signal Sg: composite acceleration signal Sk: secondary step signal Ss: tertiary step signal Ssc: motion data W: for communication magnetic field

Claims (5)

A triaxial acceleration sensor (10) that detects a body motion and outputs a triaxial acceleration signal (Sa) including an x direction signal, a y direction signal, and a z direction signal;
First filter means (20) for inputting the triaxial acceleration signal (Sa) and outputting a primary step signal (Sn);
First calculation means (30) for inputting the primary step signal (Sn) and outputting a composite acceleration signal (Sg);
A filter c section (41), a filter d section (42) and a filter for inputting the combined acceleration signal (Sg) and outputting a long band signal (Sf21), a middle band signal (Sf22) and a short band signal (Sf23), respectively. a second filter means (40) comprising an e section (43);
Second computing means (50) for inputting the long band signal (Sf21), the middle band signal (Sf22) and the short band signal (Sf23) and outputting a secondary step signal (Sk);
A part detecting means (90) for inputting a primary step signal (Sn) output from the first filter means (20) and outputting a part signal (Suc);
The secondary step signal (Sk) output from the second calculation means (50) and the part signal (Suc) output from the part detection means (90) are input to input a tertiary step signal (Ss). Step detection means (60) for outputting
Exercise data calculation that inputs the tertiary step signal (Ss) and the region signal (Suc) output from the region detection means (90) and outputs exercise data (Ssc) including activity consumption data. Means (70);
Communication means (80);
An activity meter characterized by comprising The part detection means (90) comprises a ranking means (91), an identification means (92), and a discrimination means (93).
The ranking means (91) ranks data in which the amplitudes of the x-direction signal, the y-direction signal and the z-direction signal constituting the primary step signal (Sn) are ranked first and second in descending order. (S1j) and evaluation data (S1) consisting of amplitude difference data (S1d) between the first and second positions are output,
The identification means (92) receives the evaluation data (S1) output from the ranking means (91), the rank of the rank data (S1j) is changed, and the amplitude difference data (S1d) has a predetermined level. When it exceeds, an identification signal (S2) is output, and the discriminating means (93) measures an elapsed time each time the identification signal (S2) from the discriminating means (92) is inputted, and the elapsed time is a predetermined time. A non-arm wearing signal (Sucn) is output as the part signal (Suc) when the time is over, and an arm wearing signal (Sucy) is output if the elapsed time is less than a predetermined time. The activity meter according to claim 1. The step detecting means (60) includes a frequency threshold value for evaluating the number of times of the secondary step signal (Sk) and an amplitude threshold value for evaluating the amplitude of the secondary step signal (Sk), and the arm wearing signal (Sucy). ) Is changed, the number threshold and the amplitude threshold are changed,
The exercise data calculation means (70) is configured to change the calculation of the activity consumption power loli data of the exercise data (Ssc) when the arm wearing signal (Sucy) is input. The active mass meter of Claim 1 or Claim 2 to do.   The second calculation means (50) is configured to select the long band signal (Sf21), the middle band signal (Sf22), The activity according to any one of claims 1 to 3, wherein any one of the short-band signals (Sf23) is selected and output as the secondary step signal (Sk). Quantity meter.   The activity meter according to claim 1, wherein the communication means (80) has a short-range communication function based on a technical standard defined in NFCIP-2.

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