Electrical and Computer Engineering Commons^™

Supporting Real-Time Cognitive State Classification On A Mobile Individual, Michael C. Dorneich, Stephen D. Whitlow, Santosh Mathan, Patricia May Ververs, Deniz Erdogmus, Andre Adami, Misha Pavel, Tian Lan

Michael C. Dorneich

The effectiveness of neurophysiologically triggered adaptive systems hinges on reliable and effective signal processing and cognitive state classification. Although this presents a difficult technical challenge in any context, these concerns are particularly pronounced in a system designed for mobile contexts. This paper describes a neurophysiologically derived cognitive state classification approach designed for ambulatory task contexts. We highlight signal processing and classification components that render the electroencephalogram (EEG) -based cognitive state estimation system robust to noise. Field assessments show classification performance that exceeds 70% for all participants in a context that many have regarded as intractable for cognitive state classification using …