Activity recognition from acceleration data using AR model representation and SVM

Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC

Volumn 4, Issue , 2008, Pages 2245-2250

  He, Zhen Yu ^a   Jin, Lian Wen ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Activity recognition; Autoregressive model; Feature extraction; SVM; Tri axial aceelerometer data

Indexed keywords

ARGON; CONTROL THEORY; CYBERNETICS; FORESTRY; KALMAN FILTERS; LEARNING SYSTEMS; MATHEMATICAL MODELS; ROBOT LEARNING; SUPPORT VECTOR MACHINES; VECTORS;

ACTIVITY RECOGNITION; AR COEFFICIENTS; AR MODELS; AUTOREGRESSIVE; AUTOREGRESSIVE MODEL; HUMAN ACTIVITIES; STANDARD DEVIATIONS; SVM; TIME DOMAINS; TRI-AXIAL ACEELEROMETER DATA;

FEATURE EXTRACTION;

EID: 57849153571     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLC.2008.4620779     Document Type: Conference Paper

References (13)

1. Huynh. T. Schiele. B. Analyzing Features for Activity Recognition. Proceedings of the 2005 joint conference on Smart objects, 2005
2. Wang, S., Yang, J., Chen, N., Chen, X., Zhang, Q., "Human Activity Recognition with User-Free Accelerometers in the Sensor Networks", IEEE Int. Conf. Neural Networks and Brain, vol. 2, pp. 1212-1217, 2005.
3. G.D. Abowd, A.K. Dey, R. Orr, J.A. Brotherton, "Context-awareness in wearable and ubiquitous computing". Virtual Reality, vol. 3, pp.200-211, 1998.
4. Sekine, M., Tamura, T., Akay, M., ect al Fujimoto, T., Togawa, T., Fukui, Y., "Discrimination of Walking Patterns using Wavelet-Based Fractal Analysis", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 10, PP.188-196, 2002.
5. Randell C., Muller H., "Context awareness by analyzing accelerometer data". Fourth International Symposium on Wearable Computers, pp. 175-176, 2000.
6. Bao L., Intille S.S., "Activity recognition from user-annotated acceleration data", PERVASIVE 2004. LNCS, vol. 300, PP. 1-17, Apr. 2004.
7. Mantyla J., Himberg J., Seppanen T., "Recognizing Human Motion with Multiple Acceleration Sensors", IEEE International Conference on Systems, Man and Cybernetics, Tucson, USA, vol. 3494, pp. 747-752, 2001.
8. Ravi N., Dandekar N., Mysore P., Littman MX., "Activity Recognition from Accelerometer Data", Proceedings of the Seventeenth Innovative Applications of Artificial Intelligence Conference, pp. 1541-1546, 2005.
9. Zhizeng Luo, Fei Wang, Wenjie Ma, "Pattern Classification of Surface Electromyography Based on AR Model and High-order Neural Network", Proceedings of the 2nd IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, PP. 1-6, Aug. 2006.
10. Hefftner G., Zucchini W., Jaros, G. G., "The Eletromyogram (EMG) as a Control Signal for Functional Neuromuscular Stimulation - Part I: Autoregressive Modeling as a Means of EMG Signature Discrimination", IEEE Transactions on Biomedical Engineering, vol. 35, NO. 34, pp. 230-237, Apr. 1988.
11. Steven M Kay. Modern Spectral Estimation: Theory and Application, Prentice Hall, 1988.
12. Akaike, A New Look at the Statistical Model Identification, IEEE Trans. Autom. Control, Vol. AC19, pp.716-723, 1994
13. Vapnik V. The nature of statistical learning theory, Springer Press, New York, 1999.