DocumentCode :
536173
Title :
Estimating energy expenditure of mobile device users using HMM
Author :
Su, Yancong ; Murao, Hajime
Author_Institution :
Grad. Sch. of Intercultural Studies, Kobe Univ., Kobe, Japan
Volume :
2
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
493
Lastpage :
496
Abstract :
In this paper, we apply HMM to estimate amount of energy expenditure of mobile device users using a 3-axes acceleration sensor. HMM is used to recognize user´s contexts from a time-series of acceleration data obtained by SunSPOT attached to the user. The energy expenditure can be calculated based on MET values corresponding to the contexts. In the preliminary experiments, we tried to distinguish between two contexts of “running” and “walking”. We observed acceleration data for 20 minutes with 100Hz for each context. As a result, HMM could recognize more than 90% cases correctly.
Keywords :
hidden Markov models; medical computing; mobile handsets; pattern recognition; 3-axes acceleration sensor; MET values; acceleration data; hidden Markov models; mobile device users; user context recognition; user energy expenditure estimation; Acceleration; Hidden Markov models; Acceleration; Context; Energy Expenditure; HMM; MET; Mobile Device;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658269
Filename :
5658269
Link To Document :
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