Smith Lauren H, Kuiken Todd A, Hargrove Levi J
Center for Bionic Medicine at the Rehabilitation Institute of Chicago, Chicago, IL, USA. Department of Biomedical Engineering at Northwestern University, Evanston, IL, USA.
J Neural Eng. 2014 Dec;11(6):066013. doi: 10.1088/1741-2560/11/6/066013. Epub 2014 Nov 14.
Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG.
We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs.
Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts' Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts' Law tasks with high levels of path efficiency.
These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control.
肌电假肢利用肌电图(EMG)信号来控制假肢关节的运动。临床上可用的肌电控制策略不允许同时控制多个自由度(DOF);然而,使用可记录肌肉内EMG信号的植入式设备可以克服这一限制。本研究的目的是评估使用肌肉内EMG对三个自由度(手腕旋转、手腕屈伸和手的开合)进行实时同步控制。
我们使用两种带细丝EMG的控制策略,在虚拟环境中评估了五名身体健全受试者的任务表现:(i)并行双位点差分控制,可实现对三个自由度的同时控制;(ii)模式识别控制,需要按顺序控制自由度。
在实验过程中,使用并行双位点控制的受试者在菲茨定律测试中表现出更多地使用同步控制且性能有所提高。到实验结束时,对于需要多个自由度的任务,使用并行双位点控制的性能明显更好(吞吐量提高了25%),优于使用顺序模式识别控制时的性能。并行双位点控制的学习趋势表明性能指标有可能进一步提高。受试者在使用并行双位点控制进行孤立的单自由度运动时偶尔会遇到困难,但能够以较高的路径效率完成相关的菲茨定律任务。
这些结果表明,以并行双位点配置使用的肌肉内EMG可以提供对多自由度假手腕和手的同步控制,并且可能优于当前实施顺序控制的方法。