Feature selection based on mutual information for human activity recognition

Author

Fish, Benjamin ; Khan, Ammar ; Chehade, Nabil Hajj ; Chien, Chieh ; Pottie, Greg

Author_Institution

Center for Embedded Networked Sensing, Univ. of California, Los Angeles, CA, USA

fYear

2012

fDate

25-30 March 2012

Firstpage

1729

Lastpage

1732

Abstract

In this work, we consider a classification problem of 14 physical activities using a body sensor network (BSN) consisting of 14 tri-axial accelerometers. We use a tree-based classifier, and develop a feature selection algorithm based on mutual information to find the relevant features at every internal node of the tree. We evaluate our algorithm on 31 features per accelerometer (total of 434), and we present the results on 8 subjects with a 96% average accuracy.

Keywords

accelerometers; body sensor networks; decision trees; gesture recognition; image classification; activity classification problem; body sensor network; feature selection; human activity recognition; mutual information; tree based classifier; triaxial accelerometers; Accelerometers; Accuracy; Approximation algorithms; Humans; Monitoring; Mutual information; Training; Accelerometers; Activity Classification; Feature Selection;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on

Conference_Location

Kyoto

ISSN

1520-6149

Print_ISBN

978-1-4673-0045-2

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2012.6288232

Filename

6288232