Remote control of an electrical car with SSVEP-Based BCI

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.