A study on the activity classification using a triaxial accelerometer

This paper describes a design of an algorithm for analyzing human activity using a body-fixed triaxial accelerometer on the back. In the first step, we distinguish static and dynamic activity period using AC signal analysis. Then five static activities were classified by applying the threshold in DC signal corresponding to the static activity period. Also, after taking AC signal and negative peak signal in the dynamic activity period, the four dynamic activities were classified by adaptive threshold method. To evaluate the performance of the proposed algorithm, the measured signals obtained from 12 subjects were applied to the proposed algorithm and the results were compared with the simultaneously measured video data. As a result, the activity classification rate of 95.1% on average was obtained. Overall results show that the proposed classification algorithm has a possibility to be used to analyze the static and dynamic physical activity.