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Novel single trial movement classification based on temporal dynamics of EEG

Wairagkar, M., Daly, I., Hayashi, Y. and Nasuto, S. (2014) Novel single trial movement classification based on temporal dynamics of EEG. In: 6th International Brain-Computer Interface Conference, September 16-19 2014, Graz University of Technology, Austria.

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Various complex oscillatory processes are involved in the generation of the motor command. The temporal dynamics of these processes were studied for movement detection from single trial electroencephalogram (EEG). Autocorrelation analysis was performed on the EEG signals to find robust markers of movement detection. The evolution of the autocorrelation function was characterised via the relaxation time of the autocorrelation by exponential curve fitting. It was observed that the decay constant of the exponential curve increased during movement, indicating that the autocorrelation function decays slowly during motor execution. Significant differences were observed between movement and no moment tasks. Additionally, a linear discriminant analysis (LDA) classifier was used to identify movement trials with a peak accuracy of 74%.

Item Type:Conference or Workshop Item (Paper)
Divisions:Life Sciences > School of Biological Sciences > Department of Bio-Engineering
ID Code:37412
Uncontrolled Keywords:Movement detection, BCI, EEG, temporal dynamics of EEG, Autocorrelation


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