JP2008086479A - Physical activity measuring system - Google Patents

Physical activity measuring system Download PDF

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JP2008086479A
JP2008086479A JP2006269492A JP2006269492A JP2008086479A JP 2008086479 A JP2008086479 A JP 2008086479A JP 2006269492 A JP2006269492 A JP 2006269492A JP 2006269492 A JP2006269492 A JP 2006269492A JP 2008086479 A JP2008086479 A JP 2008086479A
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exercise intensity
steps
behavior
measurement data
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JP4830765B2 (en
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Yoshihiro Matsumura
吉浩 松村
Kenji Nishino
健司 西野
Yutaka Yamanaka
裕 山中
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Panasonic Electric Works Co Ltd
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Matsushita Electric Works Ltd
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Abstract

<P>PROBLEM TO BE SOLVED: To provide a physical activity measuring system which sorts activities of a subject from measurement data acquired by a measuring device and obtains a central value of exercise intensity in the activity to propose activity information which is useful for improving lifestyle habits to the subject. <P>SOLUTION: A data processing apparatus 2 obtains the measurement data of the number of steps or exercise intensity which is related to a time calendar from the measuring device 1, sorts the activities from the measurement data, and calculates the exercise intensity or the number of steps of the sorted activity. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

本発明は、活動量計測システムに関するものである。   The present invention relates to an activity amount measurement system.

従来、例えば歩数等から消費エネルギを予測することにより、健康管理を目的とするものや、加速度及び角加速度センサの情報を用いて人体の行動を分類することにより、消費エネルギを算出する運動測定装置（例えば特許文献１に開示）が提供されている。
特開２００２−２６３０８６号公報（段落００１７〜００２０） Conventionally, an exercise measuring device that calculates energy consumption by predicting energy consumption from the number of steps, for example, for health management purposes, or by classifying human actions using information from acceleration and angular acceleration sensors (For example, disclosed in Patent Document 1).
JP 2002-263086 A (paragraphs 0017 to 0020)

ところで、上述の歩数等から消費エネルギを予測することにより、健康管理を目的とするものでは、歩行状態データを蓄積するようにはなっていなかった。   By the way, by predicting energy consumption from the number of steps as described above, for the purpose of health management, walking state data has not been accumulated.

また、特許文献１に開示されている運動測定装置では、歩数のみを用いて消費エネルギを算出するために、歩行時も走行時も同じ歩数であれば算出される消費エネルギは同じ値となってしまうという問題があった。かように歩行や、走行など行動の類別と運動強度との関係を被測定者に提示することができなかった。   Further, in the exercise measuring device disclosed in Patent Document 1, since the energy consumption is calculated using only the number of steps, the calculated energy consumption is the same value if the number of steps is the same during walking and running. There was a problem that. Thus, it was impossible to present to the measurement subject the relationship between the classification of behavior such as walking and running and the exercise intensity.

本発明は、上述の点に鑑みて為されたもので、その目的とするところは、測定装置で得られた測定データから被測定者の行動を類別と、その行動における運動強度の代表値を求めるができ、その結果被測定者に生活習慣の改善を図るために役立つ行動情報を提示することが可能な活動量計測システムを提供することにある。   The present invention has been made in view of the above points, and the object of the present invention is to classify the actions of the person to be measured from the measurement data obtained by the measuring apparatus and to obtain representative values of exercise intensity in the actions. An object of the present invention is to provide an activity amount measurement system that can be obtained, and as a result, can present behavior information useful for improving lifestyle habits to a subject.

上述の目的を達成するために、請求項１の発明では、被測定者の歩数及び被測定者の運動強度を測定する測定手段及び該測定手段から得られる歩数及び運動強度の測定データを時刻暦に関連付けて記憶する記憶手段を有する測定装置と、時刻暦に関連付けてある前記歩数或いは前記運動強度の測定データを通信により前記測定装置から取得して、該測定データから行動を類別する行動類別手段を有し、該類別された行動の運動強度若しくは歩数を算出するデータ処理装置とを備えていることを特徴とする。   In order to achieve the above-mentioned object, according to the first aspect of the present invention, the measuring means for measuring the number of steps of the person to be measured and the exercise intensity of the person to be measured, and the measurement data of the number of steps and the exercise intensity obtained from the measuring means are used as time calendar A measuring device having a storage means for storing the information in association with the time scale, and a behavior classification means for acquiring the measurement data of the number of steps or the exercise intensity associated with the time calendar from the measuring device by communication and classifying the behavior from the measurement data And a data processing device for calculating the exercise intensity or the number of steps of the classified action.

請求項１の発明によれば、測定装置で得られた測定データから被測定者の行動を類別するとともに、類別された行動毎における運動強度或いは歩数を求めることができ、それにより各行動毎における運動強度や歩数が生活習慣の改善を図るのに必要な目標値等に達しているいるか否かなどの判断材料を提示することができる。   According to invention of Claim 1, while classifying a to-be-measured person's action from the measurement data obtained by the measuring device, it is possible to obtain the exercise intensity or the number of steps for each classified action. It is possible to present judgment materials such as whether or not the exercise intensity and the number of steps have reached a target value necessary for improving lifestyle habits.

請求項２の発明では、請求項１の発明において、前記行動類別手段は、前記測定データから行動を特徴付ける運動強度の代表値を抽出し、該代表値と、予め設定されている類別抽出対象の行動を特徴付ける運動強度の代表値からなる基準値とを比較して行動の類別を抽出することを特徴とする。   In the invention of claim 2, in the invention of claim 1, the behavior classification means extracts a representative value of the exercise intensity characterizing the behavior from the measurement data, and the representative value and a classification extraction target set in advance are extracted. It is characterized in that a category of behavior is extracted by comparing with a reference value consisting of a representative value of exercise intensity that characterizes the behavior.

請求項２の発明によれば、行動の類別を、測定データから求めた運動強度の代表値と、予め記憶してある基準値と比較するだけで、簡単に抽出することができる。   According to the second aspect of the present invention, it is possible to easily extract the classification of the action simply by comparing the representative value of the exercise intensity obtained from the measurement data with the reference value stored in advance.

請求項３の発明では、請求項２の発明において、前記行動類別手段は、時間枠を設けて前記測定データから各時間枠における運動強度の代表値を求め、各時間枠に対応付けて記憶してある前記基準値とを比較して行動の類別を抽出することを特徴とする。   In the invention of claim 3, in the invention of claim 2, the behavior classification means obtains a representative value of exercise intensity in each time frame from the measurement data by providing a time frame, and stores it in association with each time frame. It is characterized in that a category of behavior is extracted by comparing with a certain reference value.

請求項３の発明によれば、行動の類別抽出の精度を向上させることができる。   According to the invention of claim 3, the accuracy of action classification extraction can be improved.

請求項４の発明では、請求項１の発明において、前記行動類別手段は、歩数或いは運動強度の測定データをクラスター分析するとともに、各種の行動を特徴付ける運動強度或いは歩数の基準となる代表値に対してクラスター分析を行い、両クラスター分析の結果の類似性の比較から行動の類別を抽出することを特徴とする。   According to a fourth aspect of the invention, in the first aspect of the invention, the behavior classification means performs cluster analysis on the measurement data of the number of steps or the exercise intensity, and for a representative value serving as a reference for the exercise intensity or the number of steps characterizing various behaviors. The cluster analysis is performed, and the behavior classification is extracted from the comparison of the similarities between the results of the two cluster analyses.

請求項４の発明によれば、クラスター分析によって、行動の類別の抽出が行え、測定データの代表値の算出などを必要としない。   According to the invention of claim 4, behavior classification can be extracted by cluster analysis, and calculation of a representative value of measurement data is not required.

請求項５の発明では、請求項２乃至４の何れかの発明において、前記データ処理装置は、前記データ処理装置には、前記被測定者の社会的な個人特性に関連付けられたカレンダーを作成して、該カレンダーデータに基づき、類別する行動の基準となる代表値を設定する手段を備え、前記行動類別手段は、設定された該代表値を行動の類別抽出に用いる前記基準値とすることを特徴とする。   According to a fifth aspect of the present invention, in the data processing device according to any one of the second to fourth aspects, the data processing device creates a calendar associated with the social personal characteristics of the measured person. And a means for setting a representative value as a reference for the action to be classified based on the calendar data, wherein the action classification means sets the set representative value as the reference value used for action classification extraction. Features.

請求項４の発明によれば、カレンダーに反映させた社会的な個人特性から被測定者がとりえない行動など類別対象外の行動によるノイズを除去することができ、行動の抽出精度を向上させることができる。   According to the invention of claim 4, it is possible to remove noise caused by actions that are not classified, such as actions that the subject cannot take, from the social personal characteristics reflected in the calendar, and improve the accuracy of action extraction. be able to.

本発明は、測定装置で得られた測定データから被測定者の行動を類別するとともに、類別された行動毎における運動強度或いは歩数を求めることができ、それにより各行動毎における運動強度や歩数が生活習慣の改善を図るのに必要な目標値等に達しているいるか否かなどの判断材料を提示することができるという効果がある。   The present invention classifies the measurement subject's actions from the measurement data obtained by the measuring device, and can determine the exercise intensity or the number of steps for each classified action, whereby the exercise intensity and the number of steps for each action are obtained. There is an effect that it is possible to present judgment materials such as whether or not a target value necessary for improving lifestyle is reached.

以下本発明を一実施形態により説明する。   The present invention will be described below with reference to an embodiment.

図１は本発明の活動量計測システムの一実施形態を示し、本実施形態は図示するように被測定者の歩数及び運動強度を測定するための測定装置１と、この測定装置１との間でデータの授受を行い、測定装置１で測定した歩数、運動強度の測定データに基づいて運動強度（或いは歩数）の代表値の算出等の演算処理を行うデータ処理装置２とで構成される。   FIG. 1 shows an embodiment of an activity amount measuring system according to the present invention. In this embodiment, as shown in the figure, a measuring apparatus 1 for measuring the number of steps and exercise intensity of a person to be measured and the measuring apparatus 1 are shown. And a data processing device 2 that performs arithmetic processing such as calculation of a representative value of exercise intensity (or number of steps) based on measurement data of the number of steps and exercise intensity measured by the measuring device 1.

測定装置１は、被測定者が携行できる大きさに形成された本体(図示せず）に、被測定者の動きに応じて加速度を検出する加速度センサ１０、測定装置１での信号処理や制御のためのＣＰＵからなる演算処理部１１、読み書き自在なメモリ部１２ａ、１２ｂ、歩数等の測定データを表示するための表示部１３、データ処理装置２との間でデータ授受を行うために設けた例えばＵＳＢ（Universal Serial Bus）等の汎用の通信部１４と、時刻発生部１５と、測定装置１の動作電源を得るための二次電池や一次電池からなる電池電源（図示せず）等を備えている。   The measuring device 1 includes a body (not shown) formed in a size that can be carried by the measurement subject, an acceleration sensor 10 that detects acceleration according to the movement of the measurement subject, and signal processing and control in the measurement device 1. Is provided to exchange data with the arithmetic processing unit 11 comprising a CPU, a readable / writable memory unit 12a, 12b, a display unit 13 for displaying measurement data such as the number of steps, and the data processing device 2. For example, a general-purpose communication unit 14 such as a USB (Universal Serial Bus), a time generation unit 15, a secondary battery for obtaining an operating power source of the measuring device 1, a battery power source (not shown) including a primary battery, and the like are provided. ing.

演算処理部１１は、加速度センサ１０が検出する例えば上下方向の加速度から歩数をカウントし、また加速度の大きさから運動強度を算出する歩数・強度算出機能を備え、この機能と加速度センサ１０とで測定手段を構成する。また演算処理部１１にはメモリ部１２ａ、１２ｂに対する読み書きの制御、通信部１４の送受信の制御、表示部１３の制御の機能を備えている。   The arithmetic processing unit 11 includes a step count / intensity calculation function that counts the number of steps from, for example, vertical acceleration detected by the acceleration sensor 10 and calculates exercise intensity from the magnitude of the acceleration. Constitutes the measuring means; In addition, the arithmetic processing unit 11 has functions of reading / writing with respect to the memory units 12 a and 12 b, control of transmission / reception of the communication unit 14, and control of the display unit 13.

データ処理装置２は、例えば、活動量計測システムのデータ処理に対応したアプリケーションソフトを実行する汎用のパーソナルコンピュータによって構成されるもので、パーソナルコンピュータとして備えている外部記憶装置２０、ＵＳＢ等の通信部２１、演算処理部２２，入力部２３、ディスプレイ装置からなる表示部２４を利用しており、外部記憶装置２０には活動量計測システムとして必要な個人特性データ（被測定者の身長、体重、性別、年齢、職業等、個人ＩＤ、使用する機器ＩＤ）、更に被測定者の行動を類別抽出するために必要な類別対象としている各行動の運動強度（或いは歩数）の代表値、例えば平均値、標準偏差、最大強度（最大歩数）、最小強度（最小歩数）、最大強度（最大歩数）と最小強度（最小歩数）との差、継続する時間の幅などにより行動の波形を特徴付けるパラメータを基準値として記憶している。尚行動が継続する時間幅は行動により異なるため、例えば５分を最小単位として２時間までの５分単位の時間枠で上述の代表値を記憶している。   The data processing device 2 is constituted by, for example, a general-purpose personal computer that executes application software corresponding to the data processing of the activity amount measurement system. The data processing device 2 includes a communication unit such as an external storage device 20 and a USB provided as the personal computer. 21, an arithmetic processing unit 22, an input unit 23, and a display unit 24 including a display device are used, and the external storage device 20 has personal characteristic data (height, weight, gender of the person to be measured) necessary as an activity amount measurement system. Age, occupation, personal ID, device ID to be used), and representative values of exercise intensity (or number of steps) of each action that is necessary for classifying the actions of the person being measured, for example, an average value, Standard deviation, maximum strength (maximum steps), minimum strength (minimum steps), difference between maximum strength (maximum steps) and minimum strength (minimum steps) The parameters characterizing the waveforms of action due time width of continuing stored as a reference value. Since the time duration during which the action continues varies depending on the action, for example, the above representative value is stored in a time frame of 5 minutes up to 2 hours with 5 minutes as a minimum unit.

図２は類別する行動の波形例を示し、（ａ）は卓球・テニスのような行動の運動強度の変化波形、（ｂ）は買物のような行動の運動強度の変化波形、（ｃ）はウォーキングのような行動の運動強度の変化波形を示し、図中縦軸は運動強度の大きさを、横軸は時間を夫々示す。   FIG. 2 shows examples of waveforms of actions to be classified, (a) is a change waveform of exercise intensity of an action like table tennis / tennis, (b) is a change waveform of exercise intensity of an action like shopping, (c) is The change waveform of the exercise intensity of the action such as walking is shown. In the figure, the vertical axis indicates the magnitude of the exercise intensity, and the horizontal axis indicates the time.

次に本実施形態の活動量計測システムについて説明する。   Next, the activity amount measurement system of this embodiment will be described.

まず、被測定者が携行する測定装置１のメモリ部１２ｂには、データ処理装置２でデータベースＤＢに登録されている当該被測定者に対応した個人ＩＤ、機器ＩＤの各データをデータ処理装置２から通信部１４を用いた通信により取得して格納しているものとする。また歩数や、運動強度の算出に必要な演算用係数もメモリ部１２ｂに格納しているものとする。   First, in the memory unit 12b of the measuring device 1 carried by the measurement subject, the data processing device 2 stores the individual ID and device ID data corresponding to the measurement subject registered in the database DB by the data processing device 2. Are acquired and stored by communication using the communication unit 14. Further, it is assumed that calculation coefficients necessary for calculating the number of steps and the exercise intensity are also stored in the memory unit 12b.

このように被測定者は、一日の内の行動期間（活動期間）中、当該測定装置１を装着携行して行動する。これにより被測定者の動きに応じた加速度が加速度センサ１０により検出され、その加速度データに基づいて演算処理部１１は歩数と運動強度を算出し、その算出した結果を夫々の測定データとしてメモリ部１２ａに逐次保存するとともに、時刻発生部１５から取得する時刻データに測定データを対応付けた時刻暦データをメモリ部１２ａに記憶させる。このようにして被測定者の行動に伴う歩数や運動強度のデータが時刻暦データとともに、メモリ部１２ａに蓄積されることになる。   In this way, the person to be measured acts while wearing the measurement apparatus 1 during the action period (activity period) of the day. As a result, acceleration corresponding to the movement of the measurement subject is detected by the acceleration sensor 10, and the arithmetic processing unit 11 calculates the number of steps and the exercise intensity based on the acceleration data, and the calculated results are stored in the memory unit as respective measurement data. The time calendar data in which the measurement data is associated with the time data acquired from the time generation unit 15 is stored in the memory unit 12a. In this way, the number of steps and exercise intensity data accompanying the measurement subject's action are stored in the memory unit 12a together with the time calendar data.

そして、例えば一日の行動が終了した時点で、被測定者は、測定装置１の通信部１４をデータ処理装置２の通信部２１に通信ケーブル（図示せず）により接続して、演算処理部１１及びデータ処理装置２の演算処理部２２の制御下で通信を行わせることで、メモリ部１２ａに記憶されている時刻暦データ及び測定データを個人ＩＤ及び機器ＩＤのデータとともにデータ処理装置２に転送させる。   Then, for example, when the action of one day is finished, the person to be measured connects the communication unit 14 of the measuring device 1 to the communication unit 21 of the data processing device 2 by a communication cable (not shown), and the arithmetic processing unit 11 and the communication processing under the control of the arithmetic processing unit 22 of the data processing device 2, the time calendar data and the measurement data stored in the memory unit 12a are transmitted to the data processing device 2 together with the personal ID and the device ID data. Let it be transferred.

データ処理装置２では、演算処理部２２の制御下で、測定装置１から送られてきた個人ＩＤ及び機器ＩＤの認証を行い、この認証後、通信により取得した時刻暦データ及び測定データを当該個人ＩＤに対応する被測定者のデータとしてデータベースＤＢの保存する処理を行う。   In the data processing device 2, under the control of the arithmetic processing unit 22, the personal ID and the device ID sent from the measuring device 1 are authenticated, and after this authentication, the time calendar data and measurement data obtained by communication are used as the personal information. A process of storing in the database DB as the data of the measurement subject corresponding to the ID is performed.

また演算処理部２２の制御下で、例えば表示部２４にはデータ処理のための操作画面が表示されており、被測定者は、表示部２４の表示された操作画面に基づいて入力部２３を操作し、演算指示を行う。   Further, under the control of the arithmetic processing unit 22, for example, an operation screen for data processing is displayed on the display unit 24, and the measured person moves the input unit 23 based on the operation screen displayed on the display unit 24. Operate and give calculation instructions.

この演算指示があると、演算処理部２２は被測定者の行動類別抽出のための手段としてまず測定装置１から転送させてきた歩数及び運動強度のデータ並びに時刻暦データから、行動抽出のために例えば運動強度データの時間暦を５分毎と、１０分毎というように時間窓を定め、２時間までの窓単位について、各時間枠単位基準値と対応する代表値を運動強度データから算出する。次にこの算出した代表値とデータベースＤＢに記憶してある各行動毎の基準値とを比較し、算出した代表値が各時間枠の基準値を越えているかをチェックする。そしてどの行動の類別を決定する係数として、各時間枠における基準値と測定データから求めた代表値との残差が全て所定値範囲（運動強度での残差であれば例えば±１ＭＥＴｓ）内であれば、その２時間の窓枠単位での行動の類別を決定抽出する。   When there is this calculation instruction, the calculation processing unit 22 extracts the action from the step count and exercise intensity data and the time calendar data transferred from the measuring apparatus 1 as means for extracting the action category of the person to be measured. For example, a time window is set such that the time calendar of exercise intensity data is every 5 minutes and every 10 minutes, and for window units up to 2 hours, a representative value corresponding to each time frame unit reference value is calculated from the exercise intensity data. . Next, the calculated representative value is compared with the reference value for each action stored in the database DB to check whether the calculated representative value exceeds the reference value for each time frame. As a coefficient for determining which action category, the residuals between the reference value in each time frame and the representative value obtained from the measurement data are all within a predetermined value range (for example, ± 1 METs if the residual is an exercise intensity residual). If there is, the classification of the action in the window frame unit for 2 hours is determined and extracted.

この類別抽出した後、演算処理部２２は抽出した行動における運動強度の平均値或いは歩数の平均値を算出し、この算出結果を更にデータベースＤＢに登録している運動目標基準値と比較し、行動が運動目標基準値に達しているか否かの判断を行い、その判断結果を表示部２４に表示する。この場合行動毎に算出した歩数の平均値或いは運動強度の平均値をも合わせて表示する。被測定者はこの表示を今後の行動の指標として生活習慣の改善を図ることができるのである。   After the classification is extracted, the arithmetic processing unit 22 calculates the average value of the exercise intensity or the average value of the number of steps in the extracted action, and compares the calculation result with the exercise target reference value registered in the database DB. Is determined whether or not the exercise target reference value has been reached, and the determination result is displayed on the display unit 24. In this case, the average value of the number of steps calculated for each action or the average value of exercise intensity is also displayed. The measured person can use this display as an indicator of future behavior to improve lifestyle.

尚上述の測定データから求めた代表値と、基準値との残差を求める方法以外に、クラスター分析によって行動の類別抽出を行っても良い。   In addition to the method of obtaining the residual between the representative value obtained from the measurement data and the reference value, behavior classification may be extracted by cluster analysis.

この場合、演算処理部２２は、例えばクラスター分析のパラメータを上述の２時間の窓枠内の各時間枠毎の運動強度を用い、例えば測定データから求めた各窓枠内の時間枠毎のの運動強度のユークリッド距離を求めて、その距離が近いものがあれば、同じクラスターとする。同様にデータベースＤＢに記憶している各行動に対応する基準値についてもクラスター分析を行ってユークリッド距離を求め、両クラスター分析の結果を比較して基準値側で求めたユークリッド距離に近い測定データ側のクラスターを当該基準値に対応する行動であると判定し、類別抽出を行うのである。   In this case, the arithmetic processing unit 22 uses the exercise intensity for each time frame in the above-described 2-hour window frame as the cluster analysis parameter, for example, for each time frame in each window frame obtained from the measurement data, for example. The Euclidean distance of the exercise intensity is obtained, and if there is something close to the distance, the same cluster is assumed. Similarly, the reference value corresponding to each action stored in the database DB is also subjected to cluster analysis to determine the Euclidean distance, and the measurement data side close to the Euclidean distance calculated on the reference value side by comparing the results of both cluster analyzes It is determined that the cluster is an action corresponding to the reference value, and category extraction is performed.

また、データ処理装置２において、演算処理部２２の制御下で、図３に示すような入力画面を用いて、被測定者自身が居住地、職業、職種、家族構成等の個人特性データを入力することでデータベースＤＢに登録し、且つ被測定者毎に、その社会的な個人特性に対応した図４に示すようにカレンダーＡのデータ作成を行うことができるようにするとともに、個人特性データやカレンダーＡのデータに基づいて、類別する行動の上述する代表値を定めてデータベースＤＢに記憶するようにしても良い。これにより演算処理部２２が上述の行動の類別抽出するときに、当該被測定者が勤務中の平日にとりえない行動や、或いは自転車や乗り物を通勤時に利用する場合になどにとりえない行動等は、類別対象外の行動として判定し、ノイズによる行動を除去し、行動の類別抽出の精度を高めることができる。   Further, in the data processing device 2, under the control of the arithmetic processing unit 22, the measured person inputs personal characteristic data such as residence, occupation, occupation, family structure, etc. using an input screen as shown in FIG. As shown in FIG. 4 corresponding to the social personal characteristics of each person to be measured, the calendar A data can be created for each person to be measured. Based on the data of the calendar A, the above-described representative value of the action to be classified may be determined and stored in the database DB. As a result, when the arithmetic processing unit 22 extracts the above-described behavior classification, an action that cannot be taken when the person under measurement is taken on a working weekday or when a bicycle or a vehicle is used for commuting. Etc. can be determined as behaviors that are not classified, and behaviors due to noise can be removed to improve the accuracy of behavioral category extraction.

一実施形態のシステム構成図である。It is a system configuration figure of one embodiment. 一実施形態のデータ処理装置において類別抽出する行動の運動強度の変化波形例図である。It is a change waveform example figure of the exercise intensity of the action which carries out classification extraction in the data processor of one embodiment. 一実施形態のデータ処理装置の表示部で表示される個人特性データ入力画面の表示例図である。It is a display example figure of the personal characteristic data input screen displayed on the display part of the data processor of one embodiment. 一実施形態のデータ処理装置の表示部で表示されるカレンダーデータ作成用画面の表示例図である。It is a display example figure of the screen for calendar data creation displayed on the display part of the data processor of one embodiment.

符号の説明Explanation of symbols

１ 測定装置
１０ 加速度センサ
１１ 演算処理部
１２ａ，１２ｂ メモリ部
１３ 表示部
１４ 通信部
１５ 時刻発生部
２ データ処理装置
２０ 外部記憶装置
２１ 通信部
２２ 演算処理部
２３ 入力部
２４ 表示部
ＤＢ データベース DESCRIPTION OF SYMBOLS 1 Measurement apparatus 10 Acceleration sensor 11 Arithmetic processing part 12a, 12b Memory part 13 Display part 14 Communication part 15 Time generation part 2 Data processing apparatus 20 External storage device 21 Communication part 22 Operation processing part 23 Input part 24 Display part DB Database

Claims (5)

被測定者の歩数及び被測定者の運動強度を測定する測定手段及び該測定手段から得られる歩数及び運動強度の測定データを時刻暦に関連付けて記憶する記憶手段を有する測定装置と、
時刻暦に関連付けてある前記歩数或いは前記運動強度の測定データを通信により前記測定装置から取得して、該測定データから行動を類別する行動類別手段を有し、該類別された行動の運動強度若しくは歩数を算出するデータ処理装置とを備えていることを特徴とする活動量計測システム。 A measuring device having measuring means for measuring the number of steps of the person to be measured and exercise intensity of the person to be measured, and storage means for storing the measurement data of the number of steps and exercise intensity obtained from the measuring means in association with the time calendar;
The measurement data of the number of steps or the exercise intensity associated with the time calendar is acquired from the measurement device by communication, and has action classification means for classifying the action from the measurement data, and the exercise intensity of the classified action or An activity amount measuring system comprising a data processing device for calculating the number of steps. 前記行動類別手段は、予め類別抽出対象の行動を特徴付ける運動強度或いは歩数の代表値を基準値として記憶し、該基準値に対応する運動強度或いは歩数代表値を前記測定データから求めて、この求めた代表値と前記基準値とを比較して行動の類別を抽出することを特徴とする請求項１記載の活動量計測システム。 The behavior classification means stores in advance a representative value of the exercise intensity or the number of steps characterizing the behavior of the category extraction target as a reference value, and obtains the exercise intensity or the representative number of steps corresponding to the reference value from the measurement data. The activity amount measuring system according to claim 1, wherein the representative value and the reference value are compared to extract a category of behavior. 前記行動類別手段は、時間枠を設けて前記測定データから各時間枠における運動強度の代表値を求め、各時間枠に対応付けて記憶してある前記基準値とを比較して行動の類別を抽出することを特徴とする請求項２記載の活動量計測システム。 The behavior classification means obtains a representative value of exercise intensity in each time frame from the measurement data by providing a time frame, compares the reference value stored in association with each time frame, and classifies the behavior The activity amount measuring system according to claim 2, wherein the activity amount measuring system is extracted. 前記行動類別手段は、歩数或いは運動強度の測定データをクラスター分析するとともに、各種の行動を特徴付ける運動強度或いは歩数の基準となる代表値に対してクラスター分析を行い、両クラスター分析の結果の類似性の比較から行動の類別を抽出することを特徴とする請求項１の活動量計測システム。 The behavior classification means performs cluster analysis on the measurement data of the number of steps or exercise intensity, and also performs cluster analysis on the representative values serving as the reference of exercise intensity or number of steps characterizing various actions, and the similarity of the results of both cluster analysis The activity amount measuring system according to claim 1, wherein a classification of behavior is extracted from the comparison of the two. 前記データ処理装置は、前記データ処理装置には、前記被測定者の社会的な個人特性に関連付けられたカレンダーを作成して、該カレンダーデータに基づき、類別する行動の基準となる代表値を設定する手段を備え、前記行動類別手段は、設定された該代表値を行動の類別抽出に用いる前記基準値とすることを特徴とする請求項２乃至４の何れか記載の活動量計測システム。 The data processing device creates a calendar associated with the social personal characteristics of the measured person and sets a representative value as a reference for categorizing actions based on the calendar data. 5. The activity amount measuring system according to claim 2, wherein the behavior classification unit uses the set representative value as the reference value used for behavior classification extraction.
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