Discrimination of Rest, Motor Imagery and Movement for Brain-Computer Interface Applications

Nedime Öztürk, Bülent Yilmaz
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引用次数: 1

Abstract

Brain-computer interface (BCI) is a system that provides a means to control prosthesis, wheelchair, or similar devices using brain waves without direct motor nervous system involvement. For this purpose, brain waves obtained from multiple electrodes placed on the scalp (EEG, Electroencephalogram) are used. Emotiv Epoc used to obtain EEG signals is a low-cost device and has real-time applications. The aim of this study is the detection of rest, imagination and real movement using EEG signals obtained by Emotiv Epoc headset. As a result, As a result, the data obtained from 39 trials from a female subject were classified resting, motion imagination and movement, according to 97.4% accuracy by using the statistical features of distortion, logarithm energy entropy, energy, Shannon entropy and kurtosis. In this study, it has been shown that this system can be remarkably successful for BCI applications.
基于脑机接口的休息、运动意象和运动识别
脑机接口(BCI)是一种利用脑电波控制假肢、轮椅或类似装置而不直接涉及运动神经系统的系统。为此,使用从放置在头皮上的多个电极获得的脑电波(EEG,脑电图)。Emotiv Epoc是一种低成本、实时性强的EEG信号采集设备。本研究的目的是利用Emotiv Epoc头戴式耳机获得的脑电图信号来检测休息、想象和真实运动。结果,利用失真、对数能量熵、能量、香农熵和峰度的统计特征,对女性受试者39次试验的数据进行静息、运动想象和运动分类,准确率为97.4%。在这项研究中,已经证明该系统可以非常成功地用于脑机接口应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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