A brain-computer interface (BCI) is a system that allows a person to communicate or control the surroundings without depending on the brain's normal output pathways of peripheral nerves and muscles. A lot of successful applications have arisen utilizing the advantages of BCI to assist disabled people with so-called assistive technology. Considering using BCI has fewer limitations and huge potential, this project has been proposed to control the movement of an electronic wheelchair via brain signals. The goal of this project is to help disabled people, especially paralyzed people suffering from motor disabilities, improve their life qualities. In order to realize the project stated above, Steady-State Visual Evoked Potential (SSVEP) is involved. It can be easily elicited in the visual cortical with the same frequency as the one is being focused by the subject. There are two important parts in this project. One is to process the EEG signals and another one is to make a visual stimulator using hardware. The EEG signals are processed in Matlab using the algorithm of Butterworth Infinite Impulse Response (IIR) bandpass filter (for preprocessing) and Fast Fourier Transform (FFT) (for feature extraction). Besides, a harmonics-based classification method is proposed and applied in the classification part. Moreover, the design of the visual stimulator combines LEDs as flickers and LCDs as information displayers on one panel. Microcontrollers are employed to control the SSVEP visual stimuli panel. This project is evaluated by subjects with different races and ages. Experimental results show the system is easy to be operated and it can achieve approximately a minimum 1-second time delay. So it demonstrates that this SSVEP-based BCI-controlled wheelchair has a huge potential to be applied to disabled people in the future.

翻译：脑机接口（BCI）是一种无需依赖大脑外周神经和肌肉的正常输出通路，即可实现人与周围环境通信或控制的系统。借助BCI的优势，许多成功的应用已通过所谓的辅助技术帮助残障人士。考虑到BCI具有较少的限制和巨大的潜力，本项目旨在通过脑电信号控制电动轮椅的运动。项目目标是为残障人士（尤其是患有运动障碍的瘫痪患者）改善生活质量。为实现上述项目，采用了稳态视觉诱发电位（SSVEP）。当受试者注视特定频率的刺激时，视觉皮层可轻松诱发出相同频率的SSVEP。本项目包含两个重要部分：一是处理脑电图（EEG）信号，二是利用硬件制作视觉刺激器。EEG信号在Matlab中通过巴特沃斯无限脉冲响应（IIR）带通滤波器（预处理）和快速傅里叶变换（FFT）（特征提取）算法进行处理。此外，提出并应用了一种基于谐波的分类方法。同时，视觉刺激器的设计将发光二极管（LED）作为闪烁光源，液晶显示器（LCD）作为信息显示器集成于同一面板，并采用微控制器控制SSVEP视觉刺激面板。本项目由不同种族和年龄的受试者进行评估。实验结果表明，该系统易于操作，且最小时间延迟约为1秒。因此，该基于SSVEP的BCI控制轮椅在未来具有应用于残障人士的巨大潜力。