Downloads & Free Reading Options - Results

Determining operator cognitive or functional state is a critical component of adaptive aiding systems. To determine cognitive state, we must decide which measured features will assist in distinguishing different levels of mental activity. Psychophysiological signals were collected for two levels of cognitive workload from which 43 measures were derived. Three feature reduction methods were applied, and the results were used as inputs to an artificial neural network for training and classification. Average classification accuracies up to 89.7% were achieved and the number of input features required was reduced by up to 84 percent.