Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Acta Electronica Sinica》 2017-03
Add to Favorite Get Latest Update

Daily Activity Recognition Based on Triaxial Accelerometer of Elderly People

WANG Cheng-liang;WANG Xiao-jun;Key Laboratory of Dependable Service Computing in Cyber Physical Society,Ministry of Education College of Computer Science,Chongqing University;Computer School,Chongqing University;  
In the light of the motion type and characteristics of elderly people,we propose an approach which is based on triaxial accelerometer and hidden Markov model( HMM) for activities recognition. Firstly,we extract standard deviation( SD),energy,correlation coefficients,ratio forward( RAF),ratio vertical forward( RVF) as the features corresponding to different and similar activities of elderly people. Secondly,we define the activities recognition model based on HMMfor elderly people. Finally,we use the Viterbi algorithm to recognize the activities for elderly people after the parameters are trained by Baum-Welch algorithm. The experimental results shows that our approach is can be applied for daily activity recognition of elderly people and the average recognition accuracy is 93. 3%,specifically the accuracy of similar walking activities is 93. 7%.
【Fund】: 国家自然科学基金资助项目(No.61004112);; 中央高校基本科研基金资助项目(No.CDJZR12180006)
【CateGory Index】: TP391.41;TP212.9
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved