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Medical & Biological Engineering & Computing

, Volume 37, Issue 1, pp 93–98 | Cite as

Temporal and spatial complexity measures for electroencephalogram based brain-computer interfacing

  • S. J. RobertsEmail author
  • W. Penny
  • I. Rezek
Physiological Signal Analysis

Abstract

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 desynchronisations and synchronisations within the scalp-recorded electroencephalogram (EEG). These event-related desynchronisations and synchronisations (ERD and 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 classification of the ERD/S offers many exciting possibilities for the control of peripheral devices via computer analysis. To date most effort has concentrated on the analysis of the changes in absolute frequency content of signals recorded from the motor cortex. The authors present results 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 spatial ‘complexity’ of the data. Results are shown on synthetic and real data sets.

Keywords

EEG analysis Signal processing Complexity analysis Brain-computer interfacing 

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Copyright information

© IFMBE 1999

Authors and Affiliations

  1. 1.Neural Systems Research Group, Department of Electrical & Electronic EngineeringImperial College of Science, Technology & MedicineLondonUK

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