Efficient Extraction of Visual Evoked Potentials from EEG
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Algorithms for efficient extraction of evoked potentials are developed. The primary goal of this book is to introduce temporal artifact detection strategy to detect non responsive channels and trials in evoked potentials by tracing out the signals with very low energy and to remove artifacts in multichannel evoked potentials. The non responsive channels and trials are identified by calculating the energy of the N - trial average evoked potential of each channel, and the energy of the M - channel average evoked potential of each trial. Then channel wise and trial wise median test is conducted t...
Algorithms for efficient extraction of evoked potentials are developed. The primary goal of this book is to introduce temporal artifact detection strategy to detect non responsive channels and trials in evoked potentials by tracing out the signals with very low energy and to remove artifacts in multichannel evoked potentials. The non responsive channels and trials are identified by calculating the energy of the N - trial average evoked potential of each channel, and the energy of the M - channel average evoked potential of each trial. Then channel wise and trial wise median test is conducted to detect and remove non-responsive channels and trials. Temporal domain artifact detection tests include: a standard deviation (STD) test that can detect signals with little or abnormal variations in each channel, a clipping (CL) test detect amplitude clipped EPs in each channel, a kurtosis (KU) test to detect artifacts that are not identified by STD test, mode deviation test to detect the signals with large mode deviation and correlation test to detect the signals with less correlation. An attempt has been made to apply these techniques to 14-channel and 6-channel visual evoked potentials.
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