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A finger force reaction at a latency less of than 60 ms from the mechanical event can be taken as evidence for a spinal (rather than a brain) mechanism (Garnett and Stephens 1980).
However, because higher porosity can reduce the mechanical strength, and thus limit a finger force pushing a plunger piston, parametric investigations for various porosities will be needed for commercial adoption of the HSSM.
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We specifically conducted a continuous finger force feedback experiment on a group of healthy volunteers.
For the force estimation, filtered sEMG signals from a sensor array and finger force data of a healthy subject are acquired.
Individual finger force (FF) in a grip task is a vital concern in rehabilitation engineering and precise control of manipulators because disorders in any of the fingers will affect the stability or accuracy of the grip force (GF).
In both orientations, torque increased as the handle diameter increased, whereas total finger force showed a decreasing pattern which can explain the positive and non-linear correlation between torque output and handle diameter.
This paper presents a real-time embedded framework for finger force control of upper extremity prostheses.
In this study, we performed temporal decomposition analysis on a group of subjects who performed finger force feedback tasks and revealed different modes combined by various brain networks.
A non-uniform finger/phalange force distribution, in which finger force was proportional to finger muscle capabilities, exhibited a stronger correlation with subjective ratings of comfort than a uniform finger/phalange force distribution.
A LQG controller is designed to control the finger force of the prostheses utilizing the force estimate from the OLMFA as a reference.
Thus, we performed the fMRI experiment by employing a continuous paradigm, that is, continuous feedback of finger force.
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