2014 IEEE International Conference on Bioinformatics and Bioengineering (BIBE)
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Abstract

Measurement of cognitive load using brain signalsis an important area of research in human behavior and psychology. Recently, there have been attempts to use low cost, commercially available Electroencephalogram (EEG) devices for the analysis of the cognitive load. Due to the reduced number of leads, these low resolution devices pose major challenges in signal processing as well as in feature extraction. In this paper, we investigate the significant leads or channels that are useful for the analysis of the cognitive load. We use a standard matching test and n-back memory test imparting low and high cognitive loads respectively. The investigation is based on the analysis of variance (ANOVA) of Alpha and Theta frequency band signals for various combinations of leads. Comparisons have been done between the previously reported leads and those obtained using a few feature selection algorithms. Results indicate that for a given stimulus, though the significant leads are very much dependent on the subjects, the leads corresponding to the left frontal lobe and right parieto-occipital lobe are in general most significant across majority of subjects for analysis of the cognitive load.
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