Abstract
Upper limb amputation deprives individuals of their innate ability to manipulate objects. Such disability can be restored with a robotic prosthesis linked to the brain by a human-machine interface (HMI) capable of decoding voluntary intentions, and sending motor commands to the prosthesis. Clinical or research HMIs rely on the interpretation of electrophysiological signals recorded from the muscles. However, the quest for an HMI that allows for arbitrary and physiologically appropriate control of dexterous prostheses, is far from being completed. Here we propose a new HMI that aims to track the muscles contractions with implanted permanent magnets, by means of magnetic field sensors. We called this a myokinetic control interface. We present the concept, the features and a demonstration of a prototype which exploits six 3-axis sensors to localize four magnets implanted in a forearm mockup, for the control of a dexterous hand prosthesis. The system proved highly linear (R2 = 0.99) and precise (1% repeatability), yet exhibiting short computation delay (45 ms) and limited cross talk errors (10% the mean stroke of the magnets). Our results open up promising possibilities for amputees, demonstrating the viability of the myokinetic approach in implementing direct and simultaneous control over multiple digits of an artificial hand.
Highlights
Upper limb amputation deprives individuals of their innate ability to manipulate objects
Still today the most reliable and clinically viable technique is the use of the electromyogram (EMG), picked up by surface electrodes to control the movements of an electromechanical prosthesis
In order to assess Emodel, Ecross-talk, Esensor, affecting the myokinetic interface, each magnetic markers (MMs), one at a time, was moved along the entire range of motion (ROM) of the emulated muscle, and data was collected at ten equidistant points in space (P0, ..., P9 corresponding to relaxed muscle, ..., maximum contraction) along the muscle trajectory (Fig. 2, lower panel)
Summary
Upper limb amputation deprives individuals of their innate ability to manipulate objects. Novel techniques aiming to improve the number of accessible and independent signals for control have been, and are being, developed and assessed in the last decade[10] Such new approaches span from implantable interfaces that record the signals closer to their biological sources (like the implantable myoelectric sensors – IMES11 or epimysial electrodes12), to surgical techniques that create additional sites for sEMG (i.e. targeted muscle reinnervation – TMR13) or that regain access to the natural neuromuscular structures (e.g. the osseointegrated human-machine gateway[12,14]). In several instances these approaches are combined
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