DocumentCode
2993846
Title
Research on Classification of Human Daily Activities Based on a Single Tri-Axial Accelerometer
Author
Wang, Feng ; Wang, Meiling ; Feng, Nan
Author_Institution
Sch. of Biol. Sci. & Med. Eng., Southeast Univ., Nanjing, China
fYear
2011
fDate
24-28 Sept. 2011
Firstpage
121
Lastpage
124
Abstract
In this paper, a multi-layers method with multi-parameters based on the characteristics of the human movements acceleration signals is proposed to recognize the human daily activities. We calculate some features of the acceleration signals that are less dependent on the individuals. The features are successfully used to divide signals into different groups which are related to the human daily activities. Our experiments demonstrate the effectiveness of the proposed method, and the overall recognition accuracy is higher than 90%.
Keywords
accelerometers; discrete wavelet transforms; medical signal processing; discrete wavelet transformation; human daily activities; human movements acceleration; multilayers method; single tri-axial accelerometer; Acceleration; Accelerometers; Accuracy; Classification algorithms; Heuristic algorithms; Humans; Legged locomotion; Accelerometer; Activity recognition; Hierarchical recognition; Step counting; the discrete wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Complexity and Data Mining (IWCDM), 2011 First International Workshop on
Conference_Location
Nanjing, Jiangsu
Print_ISBN
978-1-4577-2007-9
Type
conf
DOI
10.1109/IWCDM.2011.35
Filename
6128446
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