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Fingertip force estimation from forearm muscle electrical activity
13
Citations
23
References
2014
Year
Unknown Venue
Neuromuscular CoordinationEmg ElectrodesEngineeringWearable TechnologyMovement BiomechanicsUpper ExtremityMotor ControlRemnant Muscle TissueSensorimotor RehabilitationEmg SignalsKinesiologyBiomechanicsApplied PhysiologyMotor NeuroscienceProsthesisPhysical MedicineSensorimotor ControlHealth SciencesRehabilitationHand TherapyGesture RecognitionElectromyographyElectrophysiologyMusculoskeletal InteractionHuman MovementFingertip Force EstimationFine Motor Control
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 %MVC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</sub> (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.
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