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Real-time Human Activity Pattern Recognition Based on Time Domain Features of Acceleration |
LIU Yu,JIANG Hongyi,WANG Shiliang,WANG Yibing,CHEN Yanping |
(Chongqing Municipal Level Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China) |
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Abstract Abstract: An algorithm of activity pattern recognition based on the time domain feature of acceleration was proposed for realtime human activity pattern recognition with high accuracy. Time-domain analysis was used as the only method for extracting features. Computation of feature extraction was simplified to achieve realtime recognition of activity, and the ideal result with high accuracy was acquired at the same time. The data tests on Android smart phone indicate that the average accuracy of realtime activity recognition is above 80%. The result proves that this algorithm has a much more high accuracy of realtime recognition compared with the existing algorithms, which has great application prospect in hand-held terminal areas.
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Received: 12 May 2014
Published: 28 February 2015
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