An Improved Activity Recognition Method Based on Smart Watch Data

被引：8
|
作者：
Tian, Dengpan [1 ]
Xu, Xiaowei [1 ]
Tao, Ye [2 ]
Wang, Xiaodong [1 ]
机构：
[1] Ocean Univ China, Dept Informat Engn, Qingdao, Peoples R China
[2] Qingdao Univ Sci & Technol, Dept Comp Sci & Technol, Qingdao, Peoples R China
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE) AND IEEE/IFIP INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (EUC), VOL 1 | 2017年
关键词：
activity recognition; decision tree; smart watch; ubiquitous computing;
D O I：
10.1109/CSE-EUC.2017.148
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Activity recognition is mainly used in health care, authentication and many other fields. Activity recognition based on a smart watch usually performs much better than any other means of activity recognition in these areas. With its small size, high integration and multi-function, smart watch holds more advantages over the devices used in image based activity recognition, for example, a monitor, which is usually location fixed and view limited. In this paper, we collected data of five behaviors, i.e. stand, walk, run, upstairs, downstairs from the accelerometer on a smart watch. These data are classified with CART decision tree. Experimental results prove that the proposed method improves the accuracy of activity recognition.
引用
收藏
页码：756 / 759
页数：4
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