Continuous decoding of finger position from surface EMG signals for the control of powered prostheses.
As development toward multi-fingered dexterous prosthetic hands continues, there is a growing need for more flexible and intuitive control schemes. Through the use of generalized electrode placement and well-established methods of pattern recognition, we have developed a basis for asynchronous decoding of finger positions. With the present method, correlations as large as 0.91 and mean overall decoding errors of approximately 11% have been achieved with average decoding errors of between decoded and actual conformation of the metacarpophalangeal joints of individual fingers. It is hoped that these results will serve as a foundation from which to encourage further investigation into more intuitive methods of myoelectric control of powered upper limb prostheses.
Smith
Ryan J
RJ
Biomedical Engineering department, The Johns Hopkins University, Baltimore, MD, USA. rsmit145@jhu.edu
Tenore
Francesco
F
Huberdeau
David
D
Etienne-Cummings
Ralph
R
Thakor
Nitish V
NV
D000465:Algorithms; D004576:Electromyography / Q000295:instrumentation / Q000379:methods*; D004867:Equipment Design; D005246:Feedback / Q000502:physiology; D005385:Fingers / Q000502:physiology*; D006801:Humans; D009068:Movement / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D019736:Prostheses and Implants; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity