Control of multifunctional prosthetic hands by processing the electromyographic signal.
The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements is quite small (albeit after an appropriate and lengthy training). On the contray, prosthetic hands are just a pale replication of the natural hand, with significantly reduced grasping capabilities and no sensory information delivered back to the user. Several attempts have been carried out to develop multifunctional prosthetic devices controlled by electromyographic (EMG) signals (myoelectric hands), harness (kinematic hands), dimensional changes in residual muscles, and so forth, but none ofthese methods permits the "natural" control of more than two DoFs. This article presents a review of the traditional methods used to control artificial hands by means of EMG signal, in both the clinical and research contexts, and introduces what could be the future developments in the control strategy of these devices.
ARTS Lab, Scuola Superiore Sant'Anna, Pontedera, Italy.
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Zecca
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Micera
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MC
Carrozza
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Dario
D000465:Algorithms; D001186:Artificial Limbs; D004576:Electromyography / Q000379:methods*; D005246:Feedback; D006225:Hand / Q000503:physiopathology / Q000601:surgery; D006230:Hand Injuries / Q000503:physiopathology / Q000534:rehabilitation*; D006801:Humans; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D011474:Prosthesis Design / Q000379:methods; D011786:Quality Control; D012815:Signal Processing, Computer-Assisted