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用于皮层脑电图脑机接口的对侧和同侧手指运动分类

Classification of contralateral and ipsilateral finger movements for electrocorticographic brain-computer interfaces.

作者信息

Scherer Reinhold, Zanos Stavros P, Miller Kai J, Rao Rajesh P N, Ojemann Jeffrey G

机构信息

Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98105, USA.

出版信息

Neurosurg Focus. 2009 Jul;27(1):E12. doi: 10.3171/2009.4.FOCUS0981.

Abstract

Electrocorticography (ECoG) offers a powerful and versatile platform for developing brain-computer interfaces; it avoids the risks of brain-invasive methods such as intracortical implants while providing significantly higher signal-to-noise ratio than noninvasive techniques such as electroencephalography. The authors demonstrate that both contra- and ipsilateral finger movements can be discriminated from ECoG signals recorded from a single brain hemisphere. The ECoG activation patterns over sensorimotor areas for contra- and ipsilateral movements were found to overlap to a large degree in the recorded hemisphere. Ipsilateral movements, however, produced less pronounced activity compared with contralateral movements. The authors also found that single-trial classification of movements could be improved by selecting patient-specific frequency components in high-frequency bands (> 50 Hz). Their discovery that ipsilateral hand movements can be discriminated from ECoG signals from a single hemisphere has important implications for neurorehabilitation, suggesting in particular the possibility of regaining ipsilateral movement control using signals from an intact hemisphere after damage to the other hemisphere.

摘要

皮层脑电图(ECoG)为开发脑机接口提供了一个强大且通用的平台;它避免了诸如皮层内植入等脑侵入性方法的风险,同时提供了比脑电图等非侵入性技术显著更高的信噪比。作者证明,从单个脑半球记录的ECoG信号可以区分对侧和同侧手指运动。在记录的半球中,发现对侧和同侧运动的感觉运动区域上的ECoG激活模式在很大程度上重叠。然而,与对侧运动相比,同侧运动产生的活动不太明显。作者还发现,通过选择高频带(>50Hz)中患者特定的频率成分,可以改善运动的单次试验分类。他们发现同侧手部运动可以从单个半球的ECoG信号中区分出来,这对神经康复具有重要意义,特别表明在一个半球受损后,利用来自完整半球的信号恢复同侧运动控制的可能性。

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