Portable Classification System of Daily Activity and Exercise Load

提出了一种利用便携式测量系统对人体行走模式和日常活动进行分类记录的新算法，并在该系统中编写了由Inooka等人开发的步态分类方法。该方法将人体步态分为平走、上楼和下楼三种。该系统对人体步态进行实时分类，并将估计的步行模式与人体的心电数据一起记录到动态心电图仪中。通过对加速度和角速度的积分计算得到的步行路径中包含数值误差，提出了人体行走路径的修正算法。这项研究利用了误差椭圆内的估计动作和已知的地标。如果一个地标与估计的动作有关，则修改计算的路径以通过该地标。以座椅作为地标的存在与坐的动作为例，提出了一种将人类活动分为行走、休息、运动和躺卧四种模式的方法。这些活动是根据加速度的统计特征，并将加速度波形与已测量的参考波形进行比较而得出的。此外，连续活动由定义人类行为顺序的行为转换自动机来确定。自动机在运行轨迹和回溯中的应用，对人类活动的可靠估计是有效的。实验结果表明，该自动机能够较好地估计房间内的人类活动。

This study proposes new algorithm to classify and record human walking pattern and daily activity by using a portable measurement system.Classification method of human gait developed by Inooka et al is programd in the system. The method classifies the human gait into walking flat, going up the stairs and going down the stairs. The system performs real-time classification of human gait and records the estimated walking patterns into the Holter ECG recorder with the ECG of human. It is suggested that the system yields the relation between human walking patterns and the ECG.Modification algorithm of human walking path is also proposed because numerical error is included in the estimated walking path calculated by the integration of acceleration and angular velocity. This study utilizes the estimated action and already-known landmarks within an error ellipse. If one landmark has a relation to the estimated action, then the calculated path is modified to pass the landmark. Existence of a chair as a landmark is related to action of sitting down, for example.Moreover, we proposed a method to classify the human activity into four kinds of patterns : walking, rest, movement and lying. These activities are derived by statistical characteristics of acceleration and comparison the acceleration wave form with reference wave form already measured. Furthermore, the continuous activity is determined by an automaton of behavior transition which defines sequence of human behavior. The application of the automaton in running its course and tracing back is effective to the reliable estimation of human activity. The experimental results show that the human activity in a room is favorably estimated by using the automaton.