Remote Control of an Electrical Car with SSVEP-Based BCI

摘要：

Brain-computer interfaces (BCI) based on Steady State Visual Evoked Potential (SSVEP) can provide higher information transfer rates with minimal user training and require fewer EEG channels than other types of BCIs. The proposed remote control electrical car with SSVEP-Based BCI system combines a customized visual stimulation interface, a brainwave-acquisition platform NeuroScan SynAmps2, a computer for real-time signal processor, RF command transmitter/receiver, handmade remote control electrical car and allows users to use their brainwave to remote control electrical car. In this study, a method combining average and FFT is proposed. The frequency features of the electroencephalogram (EEG) were computed and used in the intention detection. Five healthy subjects participated in the experiment, and the results demonstrated that all the five subjects can successfully control the electrical car with high identification accuracy.

作者: Hongtao Wang Ting Li Zhenfeng Huang

作者单位: School of Information Engineering WuYi University Guangdong, China College of Automation Science and School of Information Engineering WuYi University Guangdong, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Information Theory and Information Security(2010 IEEE 国际信息论与信息安全会议)

会议地点: 北京

会议语种:英文

页码: 837-840

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）