Hybrid Feature Selection for Myoelectric Signal Classification Using MICA

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Hybrid Feature Selection for Myoelectric Signal Classification Using MICA

This paper presents a novel method to enhance the performance of Independent Component Analysis (ICA) of myoelectric signal by decomposing the signal into components originating from different muscles. First, we use Multi run ICA (MICA) algorithm to separate the muscle activities. Pattern classification of the separated signal is performed in the second step with a back propagation neural network. The focus of this work is to establish a simple, yet robust system that can be used to identify subtle complex hand actions and gestures for control of prosthesis and other computer assisted devices. Testing was conducted using several single shot experiments conducted with five subjects. The results indicate that the system is able to classify four different wrist actions with near 100% accuracy.

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  • ZARDOSHTI-KERMANI M.—WHEELER B. C.—BADIE K.—HASHEMI R. M.: EMG Feature Evaluation for Movement Control of Upper Extremity Prostheses IEEE Transaction on Rehabilitation Engineering 3 (1995) 324-233.

  • HEFFTNER G.—JAROS G.: The Electromyogram (EMG) as a Control Signal for Functional Neuromuscular Stimulation Part I: Autoregressive Modeling as a Mean of EMG Signature Discrimination IEEE Transaction on Biomedical Engineering 35 No. 6 (1998) 228-235.

  • BONIVENTO C.—DAVALLI A.—FANTUZZI C.—SACCHETTI R.—TERENZI S.: Automatic Tuning of Myoelectric Prostheses Journal of Rehab. Research and Develop 35 No. 3 (1998) 294-304.

  • HUDGINS B.—PARKER P.—SCOTT R. N.: New Strategy for Multi-Function Myoelectric Control IEEE Transaction on Biomedical Engineering 40 No. 1 yr1993 82-94.

  • CHANG G. C.—KANG W. J.—LUH J. J.—CHENG C. K.—LAI J. S.—CHEN J. J.—KUO T. S.: Real-Time Implementation of Electromyogram Pattern Recognition as a Control Command of ManMachine Interface Medical Engineering and Physics 18 No. 7 (1996) 529-537.

  • ENGLEHART K.—HUDGINS B.: A Robust Real-Time Control Scheme for Multifunction Myoelectric Control IEEE Trans. Biomed. Eng. 50 No. 7 (July 2003) 848-854.

  • DOERSCHUK P. C.—GUSTAFSON D. E.—WILLSKY A. S.: Upper Extremity Limb Function Discrimination Using EMG Signal Analysis IEEE Transactions on Biomedical Engineering 30 No. 1 (1983) 18-28.

  • KERMANI M. Z.—WHEELER B. C.—BADIE K.—HASHEMI R. M.: EMG Feature Evaluation for Movement Control of Upper Extremity Prostheses IEEE Transactions on Rehabilitation Engineering 2 (1995) 1267-1271.

  • NAKAMURA H.—YOSHIDA M.—KOTANI M.—AKAZAWA K.—MORITANI T.: The Application of Independent Component Analysis to the Multichannel Surface Electromyographic Signals for Separation of Motor Unit Action Potential Trains Journal of Electromyography and Kinesiology 14 No. 4 (Aug 2004) 423-432.

  • NAIK G. R.—KUMAR D. K.—SINGH V. P.—PALANISWAMI M.: SEMG for Identifying Hand Gestures using ICA Workshop on Biosignal Processing and Classification at 2nd International Conference on Informatics in Control Automation and Robotics Setubal Portugal Aug 2006 pp. 61-67.

  • CHLENZIG J.—HUNTER E.—JAIN R.: Vision Based Hand Gesture Interpretation Using Recursive Estimation In Twenty Eighth Asilomar Conference on Signals Systems and Computers volume 2 1994 pp. 1267-1271.

  • REHG J. M.—KANADE D. T.: Vision-Based Hand Tracking for Human-Computer Interaction in Proc. IEEE Workshop on Motion of Non-Rigid and Articulated Objects 1994 pp. 16-22.

  • SCHLENZIG J.—HUNTER E.—JAIN R.: Vision Based Hand Gesture Interpretation Using Recursive Estimation In Twenty-Eighth Asilomar Conference on Signals Systems and Computers 1994 pp. 1267-1271.

  • CHERON G.—DRAYE J. P.—BOURGEIOS M.—LIBERT G.: A Dynamic Neural Network Identification of Electromyography and Arm Trajectory Relationship during Complex Movements IEEE Trans. Biomedical Engg. 43 (1996) 552-558.

  • PAVLOVIC V. I.—SHARMA R.—HUANG T. S.: Visual Interpretation of Hand Gestures for Human Computer Interaction IEEE Trans. Pattern Analysis and Machine Intelligence 19 (1997) 677-695.

  • BASMAJIAN—DELUCA C.: Muscles Alive: Their Functions Revealed by Electromyography 5th Edn. Williams & Wilkins Baltimore 1985.

  • BELL A.—SEJNOWSKI T.: An information Maximisation Approach to Blind Separation and Blind Deconvolution Neural Comput. 7 (1995) 1129-1159.

  • HYVARINEN A.—KARHUNEN J.—OJA E.: Independent Component Analysis John Wiley New York 2001.

  • CICHOCKI A.—AMARI S.: Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications Wiley New York 2003.

  • HAIR J. F.—BLACK W. C.—BABIN B. J.—ANDERSON R. E.—TATHAM R. L.: Multivariate Data Analysis Prentice Hall 2006.

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