Segil Jacob L, Weir Richard F
Department of Mechanical Engineering, University of Colorado at Boulder, Boulder, CO;
J Rehabil Res Dev. 2015;52(4):449-66. doi: 10.1682/JRRD.2014.05.0134.
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.
肌电控制器(MEC)仍然是多功能假手发展中的一个技术瓶颈。当前的肌电控制器需要生理上不适当的指令来表明意图,并且在临床环境中缺乏有效性。姿势控制方案使用表面肌电信号在连续的二维域中驱动光标,然后将其转换为手部姿势。在此,我们提出了一种用于姿势控制器的新算法,并在涉及11名受试者的两项实验中测试了该系统的功效。在第一个实验中,我们发现使用速度光标控制技术相对于位置光标控制技术时,性能有所提高。此外,使用3个、4个或12个表面电极时,性能没有变化。在第二个实验中,受试者在未经训练的情况下将一个六自由度虚拟手控制到七种功能姿势,完成率为82±4%,移动时间为3.5±0.2秒,路径效率为45±3%。在单次1小时的训练课程后,受试者在数天内仍能高水平地使用姿势控制器。我们的结果证实了用于姿势控制器的新算法是多功能假手肌电控制器的一种稳健且有利的设计。