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Abstract
This study focuses on physical activity recognition of elder people using a single triaxial accelerometer attached on waist. With accelerations data acquired continuously by a wearable wireless device, a motion pattern recognition method based on acceleration time series analysis of human activity states is proposed. We use Hidden Markov Model (HMM) to identify physical activity series. Experimental result shows that the activity recognition rate is 95.7% using this method, which can play an important role in the adjuvant therapy.
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