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 sub-sets of channels sampling electromyograms associated to the actuation of four phantom arm DOFs. We created a large-scale 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.
Original language | English |
---|---|
Pages (from-to) | 58-64 |
Number of pages | 7 |
Journal | IEEE Transactions on Medical Robotics and Bionics |
Volume | 1 |
Issue number | 1 |
DOIs | |
Publication status | Published - 28 Jan 2019 |
Keywords
- 2022 OA procedure