Sensitive Brain-Computer Interface to help manoeuvre a Miniature Wheelchair using Electroencephalography

P. Tiwari, Abhishek Choudhary, Saurabh Gupta, J. Dhar, P. Chanak
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引用次数: 6

Abstract

Brain-Computer Interface (BCI) serves as the pathway of communication between the brain and any other external entity. It’s an emerging field and has its applications in various industries including bio-medicines. The Electroencephalographs (EEG) or brainwaves are captured and analysed using NeuroSky Mind-wave mobile headset to yield Attention, Meditation and Eye Blink Strength. EEGs are first non-invasive technique to efficiently record the various electric signals produced by neurons. The EEG signals are utilised to design BCI using Arduino micro-controller to help manoeuvre a miniature wheelchair. The system was developed with minimal cost and ensures minimal setup time. Three different combinations of attention, meditation and eye blink strength were used to design algorithms for comparative analysis of the reliability of the system. Three experiments with four trials each were conducted on the six subjects. The experimental results show that attention and meditation are not easily controlled and the system has minimum deviation of merely 1.22 turns in case of eyeblink strength experiment.
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利用脑电图帮助操纵微型轮椅的灵敏脑机接口
脑机接口(BCI)是大脑与任何其他外部实体之间的通信途径。这是一个新兴的领域,在包括生物医药在内的各个行业都有应用。脑电图(EEG)或脑电波被捕获,并使用NeuroSky Mind-wave移动耳机进行分析,以产生注意力、冥想和眨眼强度。脑电图是第一个有效记录神经元产生的各种电信号的非侵入性技术。利用脑电图信号设计脑机接口,利用Arduino微控制器帮助操纵微型轮椅。该系统的开发成本最低,并确保了最短的安装时间。采用三种不同的注意力、冥想和眨眼强度组合设计算法,对系统的可靠性进行比较分析。对6个被试进行了3个实验,每个实验4个试验。实验结果表明,在眨眼强度实验中,注意力和冥想不容易被控制,系统的最小偏差仅为1.22转。
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