Pressure signature of forearm as predictor of grip force.
We studied the relationship between grip force and external forearm pressure in nondisabled subjects using force myography (FMG). FMG uses a sensorized cuff surrounding the forearm to register the distributed mechanical force, detecting pressure on the sensors generated by the volumetric changes of the underlying musculo-tendinous complex. Each of nine nondisabled subjects donned the FMG cuff and applied grip forces to a cylindrical dynamometer; grip forces ranged from 0% to 100% of the subjects' maximum voluntary contraction. The cuff was positioned with seven force sensors located on both the anterior and posterior surfaces of the proximal forearm, but no attempt was made to match sensor placement with particular muscles or sites. Grip prediction was simply encoded as the rectified sum of the FMG sensor outputs. During grip and release cycles, the FMG waveforms of each subject correlated closely with his or her force waveforms (r > 0.89). FMG also correlated highly with the timing of grip onset and release (intraclass correlation coefficient (ICC(A,2)) = 0.99) and time to peak (ICC(A,2) = 0.91), with negligible lag. These results demonstrate that when applied to the forearm, FMG represents a grip force signature that may be useful for near-real-time proportional control of upper-limb prosthetic devices.
Wininger
Michael
M
Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA. wininger@eden.rutgers.edu
Kim
Nam-Hun
NH
Craelius
William
W
D000328:Adult; D000704:Analysis of Variance; D001696:Biomechanical Phenomena; D004576:Electromyography; D005260:Female; D005542:Forearm / Q000502:physiology*; D018737:Hand Strength / Q000502:physiology*; D006801:Humans; D008297:Male; D009213:Myography / Q000379:methods*; D011312:Pressure; D012815:Signal Processing, Computer-Assisted