Massimo Sartori , Justin van de Riet, and Dario Farina , Fellow, IEEE

 

Abstract:  The intuitive control of bionic arms requires estimation of amputee’s phantom arm movements from residual muscle bio-electric signals. The functional use of myoelectric arms relies on the ability of controlling large sets of degrees of freedom (>3 DOFs) spanning elbow, forearm, and wrist joints. This would assure optimal hand orientation in any environment. As part of this paper we recorded high-density electromyograms with >190 electrodes from the residual stump of a trans-humeral amputee who underwent targeted muscle reinnervation. We employed clustering to determine eight spatially separated subsets of channels sampling electromyograms associated to the actuation of four phantom arm DOFs. We created a largescale musculoskeletal model of the phantom arm encompassing 33 musculo-tendon units. For the first time, this enabled the accurate electromyography-driven simulation of complex phantom joint rotations about elbow flexion–extension, forearm pronation– supination, wrist flexion–extension, and radial–ulnar deviation. These results support the potential for a new class of bionic limbs that are controlled as natural extensions of the body, an important step toward next-generation prosthetics that mimic human biological functionality and robustness.