A novel pattern classification method for multivariate EMG signals using neural network

Lecture Notes in Computer Science

Volumn 3611, Issue PART II, 2005, Pages 165-174

  Bu, Nan ^a   Arita, Jun ^a   Tsuji, Toshio ^a  

^a HIROSHIMA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTROMYOGRAPHY; FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS; PROBABILISTIC LOGICS; SET THEORY;

FREQUENCY FEATURES; PROBABILISTIC NEURAL NETWORK; REDUCED-DIMENSIONAL LOG-LINEARIZED GAUSSIAN MIXTURE NETWORK;

PATTERN RECOGNITION;

EID: 26844511791     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11539117_26     Document Type: Conference Paper

References (14)

1. Bu, N., Tsuji, T.: Multivariate Pattern Classification based on Local Discriminant Component Analisys. Proc. of IEEE International Conference on Robotics and Biomimetics (2004) Paper-ID: 290
2. Fukuda, O., Tsuji, T., Kaneko, M., Ohtsuka, A.: A Human-Assisting Manipulator Teleoperated by EMG Signals and Arm Motions, IEEE Trans. on Robotics and Automation 19 (2003) 210-222
3. Englehart, K., Hudgins, B., Chen, A.D.C.: Continuous Multifunction Myoelectric Control using Pattern Recognition. Technology and Disability 15 (2003) 95-103
4. Du, Y.C., Hu, W.O., Shyu, L.Y.: The Effect of Data Reduction by Independent Component Analysis and Principal Component Analysis in Hand Motion Identification. Proc. of the 26th Annual International Conference of the Engineering in Medicine and Biology Society 1 (2004) 84-86
5. Verikas, A., Bacauskiene, M.: Feature Slection with Neural Networks. Pattern Recognition Letters 23 (2002) 1323-1335
6. Bishop, C.: Neural Networks for Pattern Recognition. New York: Oxford University Press, 1995.
7. Jain, A.K., Duin, R.P.W., Mao, J.C.: Statistical Pattern Recognition: A Review. IEEE Trans. on Pattern Analysis and Machine Intelligence 22 (2000) 4-37
8. Englehart, K., Hudgins, B., Parker, P.A., Stevenson, M.: Classification of the Myoelectric Signal using Time-frequency based Representations. Medical Engineering & Physics 21 (1999) 431-438
9. Lotlikar, R., Kothari, R.: Bayes-Optimality Motivated Linear and Multilayered Perceptron-Based Dimensionality Reduction. IEEE Trans. on Neural Networks 11 (2000) 452-463
10. Tsymbal, A., Puuronen, S., Pechenizkiy, M., Baumgarten, M., Patterson, D.: Eigenvector-based Feature Extraction for Classification. Proc. of International FLAIRS Conference on Artificial Intelligence (2002) 354-358
11. Juang, B-H., Katagiri, S.: Discriminative Learning for Minimum Error Classification. IEEE Trans, on Signal Processing 40 (1992) 3043-3054
12. Ohga, M., Takeda, M., Matsuba, A., Koike, A., Tsuji, T.: Development of A Five-finger Prosthetic Hand using Ultrasonic Motors Controlled by Two EMG Signals. Journal of Robotics and Mechatronics 14 (2002) 565-572
13. Tsuji, T., Fukuda, O., Ichinobe, H., Kaneko, M.: A Log-Linearized Gassian Mixture Network and Its Application to EEC Pattern Classification. IEEE Trans. on Systems, Man, and Cybernetics-Part C: Application and Reviews 29 (1999) 60-72
14. Rumelhart, D.E., McClell, J.L., Williams, R.J.: Learning Internal Representations by Error Propagation. Parallel Distributed Processing I (1986) 318-362