DocumentCode
178207
Title
Fingertip force estimation from forearm muscle electrical activity
Author
Pu Liu ; Martel, Francois ; Rancourt, Denis ; Clancy, Edward A. ; Brown, D. Richard
Author_Institution
Worcester Polytech. Inst., Worcester, MA, USA
fYear
2014
fDate
4-9 May 2014
Firstpage
2069
Lastpage
2073
Abstract
Existing commercial hand prostheses can be controlled from the electrical activity (electromyogram or EMG) of remnant muscle tissue within the forearm, but are limited in function to one degree of freedom of proportional control. In a pilot study (N=3 subjects), we used least squares estimation to identify a model between forearm electrical activity recorded by high-resolution (64 channel) electrode arrays (applied over the flexor and, separately, extensor muscles of the forearm) to force in the four fingertips. Average errors ranged from 4.21 to 10.20 %MVCF (flexion maximum voluntary contraction), depending on the muscle contraction task performed, number of EMG electrodes in the model and the electrode montage selected. Results suggest that, at least for intact subjects, 2-4 degrees of freedom of proportional control are available from the EMG signals of the forearm.
Keywords
biomedical electrodes; electromyography; least squares approximations; medical signal processing; prosthetics; EMG; MVCF; electrode montage; electromyogram; fingertip force estimation; flexion maximum voluntary contraction; flexor; forearm extensor muscles; forearm muscle electrical activity; hand prostheses; high-resolution electrode arrays; least squares estimation; muscle contraction task; remnant muscle tissue; Electrodes; Electromyography; Force; Muscles; Spatial filters; Thumb; EMG signal processing; EMG-force; biomedical signal processing; electromyography;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6853963
Filename
6853963
Link To Document