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Vol. 172, Issue 6, June 2014, pp. 1-6




The Improvement of Behavior Recognition Accuracy of Micro Inertial Accelerometer
by Secondary Recognition Algorithm

1 Yu Liu, 1 Le Wang, 1 Yang Cao, 2 Zhen Fang, 3 Yi Ou

1 Institute of Optical Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2 The Department of Inertial, China Electronics Technology Group Corporation 26
th Research Institute, Chongqing 400060, China
3 Silicon Device & Integrated Technology Department, Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
1 Tel.: 13883158002, fax: 021-62460380

E-mail: wslcqupt@sina.com


Received: 2 April 2014 /Accepted: 30 May 2014 /Published: 30 June 2014

Digital Sensors and Sensor Sysstems


Abstract: Behaviors of “still”, “walking”, “running”, “jumping”, “upstairs” and “downstairs” can be recognized by micro inertial accelerometer of low cost. By using the features as inputs to the well-trained BP artificial neural network which is selected as classifier, those behaviors can be recognized. But the experimental results show that the recognition accuracy is not satisfactory. This paper presents secondary recognition algorithm and combine it with BP artificial neural network to improving the recognition accuracy. The Algorithm is verified by the Android mobile platform, and the recognition accuracy can be improved more than 8 %. Through extensive testing statistic analysis, the recognition accuracy can reach 95 % through BP artificial neural network and the secondary recognition, which is a reasonable good result from practical point of view.


Keywords: Secondary recognition, Micro inertial accelerometer, Behavior recognition, BP artificial neural network.


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