EEG-based communication: analysis of concurrent EMG activity

Theresa M. Vaughan, Laurie A. Miner, Dennis J. McFarland, Jonathan R. Wolpaw
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引用次数: 44

Abstract

Objective: Recent studies indicate that people can learn to control the amplitude of mu or beta rhythms in the EEG recorded from the scalp over sensorimotor cortex and can use that control to move a cursor to targets on the computer screen. While subjects do not move during performance, it is possible that inapparent or unconscious muscle contractions contribute to the changes in the mu and beta rhythm activity responsible for cursor movement. We evaluated this possibility.

Methods: EMG was recorded from 10 distal limb muscle groups while five trained subjects used mu or beta rhythms to move a cursor to targets at the bottom or top edge of a computer screen.

Results: EMG activity was very low during performance, averaging 4.0±4.4% (SD) of maximum voluntary contraction. Most important, the correlation, measured as r2, between target position and EMG activity averaged only 0.01±0.02, much lower than the correlation between target position and the EEG activity that controlled cursor movement, which averaged 0.39±0.18.

Conclusions: These results strongly support the conclusion that EEG-based cursor control does no depend on concurrent muscle activity. EEG-based communication and control might provide a new augmentative communication option for those with severe motor disabilities.

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基于脑电图的交流:并发肌电活动的分析
目的:最近的研究表明,人们可以学会控制从头皮感觉运动皮层记录的脑电图的mu或beta节律的振幅,并可以利用这种控制将光标移动到计算机屏幕上的目标。虽然实验对象在执行过程中不移动,但可能是隐性或无意识的肌肉收缩导致了负责光标移动的mu和beta节律活动的变化。我们评估了这种可能性。方法:记录10个远端肢体肌群的肌电图,同时5个训练对象使用mu或beta节奏将光标移动到计算机屏幕底部或顶部边缘的目标。结果:运动时肌电活动很低,平均最大自主收缩4.0±4.4% (SD)。最重要的是,目标位置与肌电活动的相关系数r2平均仅为0.01±0.02,远低于控制光标运动的目标位置与脑电活动的相关系数0.39±0.18。结论:这些结果有力地支持了基于脑电图的光标控制不依赖于并发肌肉活动的结论。基于脑电图的交流和控制可能为严重运动障碍患者提供一种新的辅助交流选择。
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