Estimation of the Wrist Movements from EEG Signals using a Brain-Computer Interface

V. Logar and A. Belič (Slovenia)


Brain-computer interface, Dynamic visuo-motor task,EEG, Information coding, Movement prediction


In the past few years a relatively new concept of informa tion coding in the brain has been proposed. It is assumed that the information exchanged between the brain regions is transmitted as a phase coded content in synchronized oscillatory activity. In our previous work this theory has been validated to some level, since we have proved that some information about the current action in the brain can success fully be decoded using phase demodulation approach, brain rhythm filtering and principal component analysis. However, the disadvantage of this approach is its non-causality, since it applies different non-causal methods of signal processing. This work, therefore, investigates whether it is possible to modify the existent methodology to allow the processing of the electroencephalographic (EEG) data in real-time. For this reason we measured EEG signals from four subjects performing a dynamic visuo-motor task and tried to extract the information about their efficiency in real-time. The information to be decoded were the wrist movements as applied by the subjects when following a given continuous curve with a joystick. The study revealed that the EEG data can be processed in real-time with cer tain modifications of the proposed methodology. In this manner, the whole signal processing and information decoding system can be classified as a brain-computer interface, which decodes the information carried by EEG signals and calculates the forthcoming wrist shift. Therefore, we can conclude that the proposed methodology which already proved to be efficient when decoding off-line EEG data from various visuo-motor tasks can (with some modifications) also be used to process the data on-line in real time.

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