Abstract

A brain computer interface presents a direct communication channel from the brain. The BCI processes the brain activity and translates it into system commands using feature extraction and classification algorihms. The overarching goal of this thesis is to make a start in the field of BCI. This thesis starts with an overview of the entire multi-disciplinary field of BCI, covering the basic fundamental ingredients, methods and modalities. EEG-based BCI experiments have been designed and conducted. The experiments are designed to find distinctive brain patterns which are generated voluntary. Next to the experiments an environment is created which offers a structured approach to the analysis of the EEG data from the eperiments and allows for future continuation of BCI research. The workbench contains, among others, the following models: ICA, FFT, AR, CSP and LD. The workbench performed well and produced quality results during testing. The quality of the experimental data after evaluation with the constructed workbench appeared to be mediocre at best, caused by the low spatial resolution of the EEG equipment, appliance errors and experimental design faults. Recommendation for future work are to use different equipment, follow the line of synchronous BCI and construct a classifier to evaluate the data quality and construct an online BCI. This thesis initiates BCI research at the TU Delft.