Decoding of Individuated Finger Movements Using Surface Electromyography
Tenore, F.V.G.
Ramos, A.
Fahmy, A.
Acharya, S.
Etienne-Cummings, R.
Thakor, N.V.
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD;
This paper appears in: Biomedical Engineering, IEEE Transactions on
Publication Date: May 2009
Volume: 56,
Issue: 5
On page(s): 1427-1434
ISSN: 0018-9294
INSPEC Accession Number: 10666099
Digital Object Identifier: 10.1109/TBME.2008.2005485
First Published: 2008-10-10
Current Version Published: 2009-05-26
Abstract
Upper limb prostheses are increasingly resembling the limbs they seek to replace in both form and functionality, including the design and development of multifingered hands and wrists. Hence, it becomes necessary to control large numbers of degrees of freedom (DOFs), required for individuated finger movements, preferably using noninvasive signals. While existing control paradigms are typically used to drive a single-DOF hook-based configurations, dexterous tasks such as individual finger movements would require more elaborate control schemes. We show that it is possible to decode individual flexion and extension movements of each finger (ten movements) with greater than 90%accuracyinatransradialamputeeusingonlynoninvasivesurfacemyoelectricsignals. Further, comparison of decoding accuracy from a transradial amputee and able-bodied subjects shows nostatisticallysignificantdifference ( p < 0.05) between these subjects. These results are encouraging for the development of real-time control strategies based on the surface myoelectric signal to control dexterous prosthetic hands.
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