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Information 2016, 7(4), 72; doi:10.3390/info7040072

PACP: A Position-Independent Activity Recognition Method Using Smartphone Sensors

1,* and 1,2,3,*
1
School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China
2
Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing 210044, Jiangsu, China
3
Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 21 October 2016 / Revised: 5 December 2016 / Accepted: 12 December 2016 / Published: 15 December 2016
View Full-Text   |   Download PDF [2412 KB, uploaded 15 December 2016]   |  

Abstract

Human activity recognition has been a hot topic in recent years. With the advances in sensor technology, there has been a growing interest in using smartphones equipped with a set of built-in sensors to solve tasks of activity recognition. However, in most previous studies, smartphones were used with a fixed position—like trouser pockets—during recognition, which limits the user behavior. In the position-independent cases, the recognition accuracy is not very satisfactory. In this paper, we studied human activity recognition with smartphones in different positions and proposed a new position-independent method called PACP (Parameters Adjustment Corresponding to smartphone Position), which can markedly improve the performance of activity recognition. In PACP, features were extracted from the raw accelerometer and gyroscope data to recognize the position of the smartphone first; then the accelerometer data were adjusted corresponding to the position; finally, the activities were recognized with the SVM (Support Vector Machine) model trained by the adjusted data. To avoid the interference of smartphone orientations, the coordinate system of the accelerometer was transformed to get more useful information during this process. Experimental results show that PACP can achieve an accuracy over 91%, which is more effective than previous methods. View Full-Text
Keywords: activity recognition; smartphone; position-independent; adjustment activity recognition; smartphone; position-independent; adjustment
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yang, R.; Wang, B. PACP: A Position-Independent Activity Recognition Method Using Smartphone Sensors. Information 2016, 7, 72.

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