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The myoelectric controller (MEC) remains a technological bottleneck in the development of multifunctional prosthetic hands. Current MECs require physiologically inappropriate commands to indicate intent and lack effectiveness in a clinical setting. Postural control schemes use surface electromyography signals to drive a cursor in a continuous two-dimensional domain that is then transformed into a hand posture. Here, we present a novel algorithm for a postural controller and test the efficacy of the system during two experiments with 11 total subjects. In the first experiment, we found that performance increased when a velocity cursor-control technique versus a position cursor-control technique was used. Also, performance did not change when using 3, 4, or 12 surface electrodes. In the second experiment, subjects commanded a six degree-of-freedom virtual hand into seven functional postures without training, with completion rates of 82 +/- 4%, movement times of 3.5 +/- 0.2 s, and path efficiencies of 45 +/- 3%. Subjects retained the ability to use the postural controller at a high level across days after a single 1 hr training session. Our results substantiate the novel algorithm for a postural controller as a robust and advantageous design for a MEC of multifunction prosthetic hands.
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Segil et al. (2015) studied this question.
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