Detection of self-paced reaching movement intention from EEG signals.

Frontiers in neuroengineering Pub Date : 2012-07-12 eCollection Date: 2012-01-01 DOI:10.3389/fneng.2012.00013
Eileen Lew, Ricardo Chavarriaga, Stefano Silvoni, José Del R Millán
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引用次数: 202

Abstract

Future neuroprosthetic devices, in particular upper limb, will require decoding and executing not only the user's intended movement type, but also when the user intends to execute the movement. This work investigates the potential use of brain signals recorded non-invasively for detecting the time before a self-paced reaching movement is initiated which could contribute to the design of practical upper limb neuroprosthetics. In particular, we show the detection of self-paced reaching movement intention in single trials using the readiness potential, an electroencephalography (EEG) slow cortical potential (SCP) computed in a narrow frequency range (0.1-1 Hz). Our experiments with 12 human volunteers, two of them stroke subjects, yield high detection rates prior to the movement onset and low detection rates during the non-movement intention period. With the proposed approach, movement intention was detected around 500 ms before actual onset, which clearly matches previous literature on readiness potentials. Interestingly, the result obtained with one of the stroke subjects is coherent with those achieved in healthy subjects, with single-trial performance of up to 92% for the paretic arm. These results suggest that, apart from contributing to our understanding of voluntary motor control for designing more advanced neuroprostheses, our work could also have a direct impact on advancing robot-assisted neurorehabilitation.

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从脑电信号中检测自节奏到达运动意图。
未来的神经假肢设备,特别是上肢,不仅需要解码和执行用户预期的运动类型,还需要解码和执行用户打算执行运动的时间。本研究探讨了非侵入性记录的大脑信号的潜在用途,用于检测自定节奏到达运动开始前的时间,这可能有助于设计实用的上肢神经假肢。特别是,我们展示了在单次试验中使用准备电位检测自定节奏到达运动意图,这是一种脑电图(EEG)慢皮质电位(SCP)在窄频率范围内(0.1-1 Hz)计算。我们对12名志愿者进行了实验,其中2名是中风受试者,在运动开始前的检测率很高,而在非运动意图期的检测率很低。使用该方法,运动意图在实际开始前500 ms左右被检测到,这明显符合先前关于准备电位的文献。有趣的是,其中一名中风受试者获得的结果与健康受试者获得的结果一致,双亲病组的单次试验表现高达92%。这些结果表明,除了有助于我们理解自主运动控制以设计更先进的神经假体外,我们的工作还可以对推进机器人辅助的神经康复产生直接影响。
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