利用脑电图检测自主步态启动/终止意图

2018 6th International Conference on Brain-Computer Interface (BCI) Pub Date : 2018-01-01 DOI:10.1109/IWW-BCI.2018.8311532

Junhyuk Choi, S. Lee, Seung-jong Kim, Jong Min Lee, Hyungmin Kim

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引用次数: 5

摘要

在这项研究中，我们使用线性分类器来掌握脑电图(EEG)的抽象特征，以识别自主步态的意图和终止。我们监测mu波段脑电图来发现步态意图，并试图检测运动/偏移。因此，大量的步态相关(非)同步发生，并被共同空间模式(CSP)放大。分类器的性能根据分类成功率和假阳性率进行评估。

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Detecting voluntary gait initiation/termination intention using EEG

In this study, we employed a linear classifier to grasp the abstract features of electroencephalography (EEG) for recognizing voluntary gait intention and termination. We monitored Mu-band EEG to find gait intention and tried to detect a movement on/offset. Considerable gait-related (de) synchronization occurred hence, amplified by common spatial pattern (CSP). Performance of the classifier was evaluated in terms of classification success rates and false positive rates.

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来源期刊

2018 6th International Conference on Brain-Computer Interface (BCI)

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