Human Activity Recognition using On-body Sensing
نویسندگان
چکیده
Human Activity Recognition (HAR) based on wearable sensors is gaining increasing attention by the pervasive computing research community, especially for development of context-aware systems. This paper presents our approach for HAR based on wearable accelerometers and supervised learning algorithms. We present the HARwear device, a wearable for HAR. Using HARwear we collected data and we developed a classifier for postures and movements. The classifier is able to identify 2 postures and 3 types of movements with an accuracy of 99.4%. Based on the lessons from experimental evaluation, we propose an improved version, the HARwear version 2, which is also presented on this paper.
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