Feature selection based on mutual information for human activity recognition

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2012, Pages 1729-1732

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

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Accelerometers; Activity Classification; Feature Selection

Indexed keywords

FEATURE SELECTION ALGORITHM; HUMAN ACTIVITY RECOGNITION; INTERNAL NODES; MUTUAL INFORMATIONS; PHYSICAL ACTIVITY; TREE-BASED; TRIAXIAL ACCELEROMETER;

ACCELEROMETERS; ALGORITHMS; BODY SENSOR NETWORKS; FEATURE EXTRACTION; FORESTRY; SIGNAL PROCESSING;

TREES (MATHEMATICS);

ALGORITHMS; FORESTRY; MATHEMATICS; TREES;

EID: 84867606937     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2012.6288232     Document Type: Conference Paper

References (18)

1. D.K. White, R.C. Wagenaar, M.E. Del Olmo, and T.D. Ellis, "Test-retest reliability of 24 hours of activity monitoring in individuals with parkinsons disease in home and community," Neurorehabil Neural Repair, 2007.
2. F. M. Impellizzeri, S. M. Marcora, C. Castagna, T. Reilly, A. Sassi, F. M. Iaia, and E. Rampinini, "Physiological and performance effects of generic versus specific aerobic training in soccer players," International Journal of Sports Medicine, 2006.
3. J. Lester, T. Choudhury, G. Borriello, S. Consolvo, J. Landay, K. Everitt, and I. Smith, "Sensing and modeling activities to support physical fitness," Proceedings of UbiComp, 2005.
4. L. Bao and S. Intille, "Activity recognition from user-annotated acceleration data," Pervasive Computing, 2004.
5. N. Ruchansky, C. Lochner, E. Do, T. Rawls, N. Hajj Chehade, J. Chien, G. Pottie, and W Kaiser, "Monitoring workspace activities using accelerometers," Proceedings of ICASSP, 2011.
6. Zhongtang Zhao, Yiqiang Chen, Junfa Liu, Zhiqi Shen, and Mingjie Liu, "Cross-people mobile-phone based activity recognition," International Joint Conference on Artificial Intelligence, 2011.
7. L. Atallah, B. Lo, R. King, and G. Yang, "Sensor placement for activity detection using wearable accelerometers," International Conference on Body Sensor Networks (BSN), 2010.
8. K. Aminian, Ph. Robert, E. Buchser, B. Rutschmann, D. Hayoz, and M. Depairon, "Physical activity monitoring based on accelerometry: validation and comparison with video observation," Medical and Biological Engineering and Computing, 1999.
9. J. Lester, T. Choudhury, and G. Borriello, "A practical approach to recognizing physical activities," Pervasive Computing, 2006.
10. N. Kern, B. Schiele, and A. Schmidt, "Multi-sensor activity context detection for wearable computing," in Ambient Intelligence.
11. J.Y. Jhun-Ying Yang, J.S. Wang, and Y.P. Chen, "Using acceleration measurements for activity recognition: An effective learning algorithm for constructing neural classifiers," Pattern Recognition Letters, 2008.
12. Kenji Kira and Larry A. Rendell, "A practical approach to feature selection," Proceedings of the ninth international workshop on Machine learning, 1992.
13. R. Battiti, "Using mutual information for selecting features in supervised neural net learning," IEEE Transactions on Neural Networks, 1994.
14. Gulf Coast Data Concepts: http://www.gcdataconcepts.com.
15. S. Roberts and R. Everson, Independent component analysis: principles and practice, Cambridge University Press, 2001.
16. T.M. Cover and J.A. Thomas, Elements of information theory, Wiley Series in Telecommunications and Signal Processing. Wiley-Interscience, 2006.
17. H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005.
18. M.F. Huber, T. Bailey, H. Durrant-Whyte, and U.D. Hanebeck, "On entropy approximation for gaussian mixture random vectors," in IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2008.