DocumentCode :
1416726
Title :
Extracting and visualising human activity patterns of daily living in a smart home environment
Author :
Nam, Y. ; Rho, S. ; Lee, Sang-Rim
Author_Institution :
Dept. of Electr. & Comput. Eng., Stony Brook Univ. - SUNY, Stony Brook, NY, USA
Volume :
5
Issue :
17
fYear :
2011
Firstpage :
2434
Lastpage :
2442
Abstract :
The authors present an approach that extracts human activity patterns of daily living and represents spatiotemporal relations between activities intuitively. In general, customised services are provided based on activity patterns of users. This study focuses on extracting and determining activities that occur simultaneously. In order to determine simultaneous activities, the authors analysed the daily activities that are collected from device applications such as location sensors and electronics. In addition, a context model using the incremental statistical method is organised and temporal relations between the activities patterns are analysed. Furthermore, information visualisation of the spatiotemporal topology with duration and frequency is demonstrated. Also, the authors have experimented on a test-bed called the ubiquitous smart space and compared the accuracy of the incremental statistical method with that of the non-incremental method.
Keywords :
biomedical measurement; data visualisation; feature extraction; health care; medical computing; statistical analysis; context model; daily living human activity patterns; human activity pattern extraction; human activity pattern visualisation; incremental statistical method; information visualisation; location sensors; smart home environment; spatiotemporal relations; spatiotemporal topology; ubiquitous smart space; user activity patterns;
fLanguage :
English
Journal_Title :
Communications, IET
Publisher :
iet
ISSN :
1751-8628
Type :
jour
DOI :
10.1049/iet-com.2010.0936
Filename :
6125455
Link To Document :
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