A new strategy for multifunction myoelectric control

A novel approach to the control of a multifunction prosthesis based on the classification of myoelectric patterns is described. It is shown that the myoelectric signal exhibits a deterministic structure during the initial phase of a muscle contraction. Features are extracted from several time segments of the myoelectric signal to preserve pattern structure. These features are then classified using an artificial neural network. The control signals are derived from natural contraction patterns which can be produced reliably with little subject training. The new control scheme increases the number of functions which can be controlled by a single channel of myoelectric signal but does so in a way which does not increase the effort required by the amputee. Results are presented to support this approach.<<ETX>>

[1]  J. Basmajian.  Muscles Alive—their functions revealed by electromyography , 1963 .

[2]  Daniel Graupe,et al.  Functional Separation of EMG Signals via ARMA Identification Methods for Prosthesis Control Purposes , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[3]  Laveen N. Kanal,et al.  Structural pattern recognition of Carotid pulse waves using a general waveform parsing system , 1976, CACM.

[4]  Harry E. Stephanou,et al.  A Hierarchical Approach to the Control of a Prosthetic Arm , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  H. Schmidl.  The I.N.A.I.L. experience fitting upper-limb dysmelia patients with myoelectric control. , 1977, Bulletin of prosthetics research.

[6]  P.A. Parker,et al.  Signal processing for the multistate myoelectric channel , 1977, Proceedings of the IEEE.

[7]  Taylor Dr,et al.  Pattern-recognition arm prosthesis: a historical perspective-a final report. , 1978 .

[8]  C. D. De Luca.  Physiology and Mathematics of Myoelectric Signals , 1979, IEEE Transactions on Biomedical Engineering.

[9]  Carlo J. De Luca,et al.  Physiology and Mathematics of Myoelectric Signals , 1979 .

[10]  Hsi-Ho Liu,et al.  A syntactic pattern recognition approach to seismic discrimination , 1982 .

[11]  George N. Saridis,et al.  EMG Pattern Analysis and Classification for a Prosthetic Arm , 1982, IEEE Transactions on Biomedical Engineering.

[12]  R. De Mori,et al.  An Electrocardiographic Signal Understanding System , 1982 .

[13]  D Graupe,et al.  Multifunctional prosthesis and orthosis control via microcomputer identification of temporal pattern differences in single-site myoelectric signals. , 1982, Journal of biomedical engineering.

[14]  King-Sun Fu,et al.  A Syntactic Approach to Seismic Pattern Recognition , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Richard T. Johnson,et al.  Development of the Utah Artificial Arm , 1982, IEEE Transactions on Biomedical Engineering.

[16]  Paul Cordo,et al.  CONTROLLING MULTIPLE DEGREE-OF-FREEDOM POWERED PROSTHESES. , 1983 .

[17]  R. Scott,et al.  Multistate myoelectric control: the feasibility of 5-state control. , 1983, Journal of rehabilitation R&D.

[18]  A. Willsky,et al.  Upper Extremity Limb Function Discrimination Using EMG Signal Analysis , 1983, IEEE Transactions on Biomedical Engineering.

[19]  D Graupe,et al.  Stochastic analysis of myoelectric temporal signatures for multifunctional single-site activation of prostheses and orthoses. , 1985, Journal of biomedical engineering.

[20]  B. Hannaford,et al.  Short Time Fourier Analysis of the Electromyogram: Fast Movements and Constant Contraction , 1986, IEEE Transactions on Biomedical Engineering.

[21]  R. Scott,et al.  Myoelectric control of prostheses. , 1986, Critical reviews in biomedical engineering.

[22]  R. Engelhorn,et al.  Effects of skill practice on electromyographic activity patterns and frequency spectra , 1987 .

[23]  R N Scott,et al.  Myoelectric prostheses: state of the art. , 1988, Journal of medical engineering & technology.

[24]  Robert A. Jacobs,et al.  Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.

[25]  Yoh-Han Pao,et al.  Functional link nets: removing hidden layers , 1989 .

[26]  Y.-F. Huang,et al.  Learning algorithms for perceptions using back-propagation with selective updates , 1990, IEEE Control Systems Magazine.

[27]  R.N. Scott,et al.  The application of neural networks to myoelectric signal analysis: a preliminary study , 1990, IEEE Transactions on Biomedical Engineering.

[28]  T W Williams,et al.  Practical methods for controlling powered upper-extremity prostheses. , 1990, Assistive technology : the official journal of RESNA.

[29]  C.S. Pattichis,et al.  Artificial neural nets in computer-aided macro motor unit potential classification , 1990, IEEE Engineering in Medicine and Biology Magazine.