A Smartphone Location Independent Activity Recognition Method Based on the Angle Feature

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• 作者：Changhai Wang (24)
  Jianzhong Zhang (24)
  Meng Li (24)
  Yuan Yuan (24)
  Yuwei Xu (24)
  
• 关键词：Smartphone ; accelerometer ; activity recognition ; location independent ; angle feature
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8630
• 期：1
• 页码：179-191
• 全文大小：458 KB
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• 作者单位：Changhai Wang (24)
  Jianzhong Zhang (24)
  Meng Li (24)
  Yuan Yuan (24)
  Yuwei Xu (24)
  
  24. College of Computer and Control Engineering, Nankai University, Tianjin, China
  
• ISSN：1611-3349

文摘

The smartphone-based human activity recognition method is helpful in the context awareness, health monitoring and inertial positioning. Comparing with the traditional wearable computing which fixes accelerometers on the specific positions of a user body, the activity recognition method based on a smartphone faces the problem of varying sensor locations. In this paper, we lay emphasis on the study of a feature extraction algorithm which is independent of the phone locations. First, the angle motion model is presented to illustrate the human activities. The model describes the difference among walking, going upstairs and going downstairs. Then, an angle feature extraction algorithm is proposed according to the angle motion model. Our analysis shows that different activities have significantly different angle features. Finally, our experiments are introduced. The experiments include data collecting, analysis of experiments results. The experiments results show that the recognition accuracy improved by 2% through adding the angle feature to original features.