Temporal and Spatial Complexity Measures for Eeg-based Brain- Computer Interfacing
There has been much interest recently in the concept of using information from the motor cortex region of the brain, recorded using non-invasive scalp electrodes, to construct a crude interface with a computer. It is known that movements of the limbs, for example, are accompanied by desynchro-nisations and synchronisations within the scalp-recorded electroencephalogram (EEG). These Event-Related Desynchronisations and Synchronisations (ERD & ERS), however, appear to be present when volition to move a limb occurs, even when actual movement of the limb does not in fact take place. The determination and classiication of the ERD/S ooers many exciting possibilities for the control of peripheral devices via computer analysis. To date most eeort has concentrated on the analysis of the changes in absolute frequency content of signals recorded from the motor cortex. We present results in this paper which tackle the issues of both the interpretation of changes in signals with time and across channels with simple methods which monitor the temporal and spatiaìcomplexity' of the data. Results are shown on synthetic and real data sets.