Accelerometer Signal Processing for User Activity Detection

사용자 운동 상태 추정을 위한 가속도센서 신호처리 기술

Estimation of human motion states is important enabling technologies for realizing a pervasive computing environment. In this paper, an improved method fur estimating human motion state from accelerometer data is introduced. Our method fur estimating human motion state utilizes various statistics of accelerometer data, such as mean, standard variation, skewness, kurtosis, eccentricity, as features for classification, and therefore is expected to be more robust than other existing methods that rely on only a few simple statistics. A series of experiments fur testing the effectiveness of the proposed method has been performed, and its result is presented.