SINGLE-TRIAL EEG ANALYSIS USING AN ADAPTIVE AUTOREGRESSIVE MODEL
INTRODUCTION An important aspect for the realization of a Brain-Computer Interface (BCI) is the analysis of spatio-temporal EEG patterns. Features have to be extracted, which represent the state of the brain. In other words, the differences of the brain-state for different mental processes should be derived. In the research work presented here, the different processes are preparations for left and right finger movement. These should be represented in different brain states. Several effects make it difficult to identify differences of the brain-state. These are: • the Inter-trial variability, the brain state is build up by multiple processes, but only the process preparing the movement is of interest • Inter-individual variability, the brain processes between subjects and/or sessions are not identical. • Limitation of the method used for feature extraction, the evaluation methods have to be applied across trials and across several subjects; a method is superior to others if the error rate across different subjects is low.