Design and Implementation of a Two-Phase Activity Recognition System Using Smartphone`s Accelerometers

KIPS Transactions on Software and Data Engineering, Vol. 3, No.2, pp.87-92, February 2014
10.3745/KTSDE.2014.3.2.087, Full Text

Abstract

In this paper, we present a two-phase activity recognition system using smartphone`s accelerometers. To consider the unique temporal pattern of accelerometer data for each activity, our system executes the decision-tree(DT) learning in the first phase, and then, in the second phase, executes the hidden Markov model(HMM) learning based on the sequences of classification results of the first phase classifier. Moreover, to build a robust recognizer for each activity, we trained our system using a large amount of data collected from different users, different positions and orientations of smartphone. Through experiments using 6720 examples collected for 6 different indoor activities, our system showed high performance based on its novel design.


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Cite this paper

[KIPS Transactions Style]
J. H. Kim and I. C. Kim, "Design and Implementation of a Two-Phase Activity Recognition System Using Smartphone`s Accelerometers," KIPS Transactions on Software and Data Engineering, Vol.3, No.2, pp.87-92, 2014, DOI: 10.3745/KTSDE.2014.3.2.087.

[IEEE Style]
Jong Hwan Kim and In Cheol Kim, "Design and Implementation of a Two-Phase Activity Recognition System Using Smartphone`s Accelerometers," KIPS Transactions on Software and Data Engineering, vol. 3, no. 2, pp. 87-92, 2014. DOI: 10.3745/KTSDE.2014.3.2.087.

[ACM Style]
Kim, J. H. and Kim, I. C. 2014. Design and Implementation of a Two-Phase Activity Recognition System Using Smartphone`s Accelerometers. KIPS Transactions on Software and Data Engineering, 3, 2, (2014), 87-92. DOI: 10.3745/KTSDE.2014.3.2.087.