Myoelectric signal processing for control of powered limb prostheses.
Progress in myoelectric control technology has over the years been incremental, due in part to the alternating focus of the R&D between control methodology and device hardware. The technology has over the past 50 years or so moved from single muscle control of a single prosthesis function to muscle group activity control of multifunction prostheses. Central to these changes have been developments in the means of extracting information from the myoelectric signal. This paper gives an overview of the myoelectric signal processing challenge, a brief look at the challenge from an historical perspective, the state-of-the-art in myoelectric signal processing for prosthesis control, and an indication of where this field is heading. The paper demonstrates that considerable progress has been made in providing clients with useful and reliable myoelectric communication channels, and that exciting work and developments are on the horizon.
Parker
P
P
Institute of Biomedical Engineering, Department of Electrical and Computer Engineering, University of New Brunswick, 15 Dineen Drive, P.O. Box 4400, Fredericton, NB, Canada E3B 5A3. pap@unb.ca
Englehart
K
K
Hudgins
B
B
D001186:Artificial Limbs / Q000639:trends; D004576:Electromyography / Q000639:trends; D006801:Humans; D009119:Muscle Contraction; D018482:Muscle, Skeletal / Q000502:physiology; D010363:Pattern Recognition, Automated / Q000639:trends; D011474:Prosthesis Design / Q000639:trends; D012815:Signal Processing, Computer-Assisted; D034941:Upper Extremity / Q000502:physiology