Design and evaluation of a P300-ERP based BCI system for real-time control of a mobile robot

2017 5th International Winter Conference on Brain-Computer Interface (BCI) Pub Date : 2017-02-16 DOI:10.1109/IWW-BCI.2017.7858177

Damir Nurseitov, Abzal Serekov, A. Shintemirov, B. Abibullaev

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引用次数: 21

Abstract

With the development of Brain-Computer Interface (BCI) systems people with motor disabilities are able to control external devices using their thoughts. To control a device through BCI, brain activities of the user must be accurately translated to meaningful commands and a design of appropiate BCI paradigms play important roles in such tasks. This work presents a design and evaluation of a BCI system that is based on P300 Event-Related Potentials (ERP) in order to control a mobile robot platform into four directions (left, right, front, back). The ultimate goal of this research is to provide convienient way of controlling a mobile robot as an assistive home technology for disabled people. Low cost EPOC Emotiv headset was used in the BCI system to acquire brain signals with a Jaguar 4x4 Wheel robot as a control platform. We discuss a set of signal processing steps employed in detail and the utility of a regularized logistic regression classifier to detect visual stimuli induced P300 ERPs and, to control the Jaguar robot.

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基于P300-ERP的移动机器人BCI实时控制系统的设计与评价

随着脑机接口(BCI)系统的发展，运动障碍患者可以用他们的思想控制外部设备。为了通过脑机接口控制设备，必须将用户的大脑活动准确地转化为有意义的命令，设计合适的脑机接口范式在这一任务中起着重要作用。这项工作提出了一个基于P300事件相关电位(ERP)的脑机接口系统的设计和评估，以控制移动机器人平台到四个方向(左，右，前，后)。本研究的最终目标是提供一种方便的控制移动机器人的方法，作为残疾人的辅助家庭技术。BCI系统采用低成本EPOC Emotiv头戴式耳机，以捷豹四轮驱动机器人为控制平台，采集脑信号。我们详细讨论了一组信号处理步骤，并使用正则化逻辑回归分类器来检测视觉刺激引起的P300 erp，并控制美洲虎机器人。

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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2017 5th International Winter Conference on Brain-Computer Interface (BCI)

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