Human operators continue to be subject to workload, and predicting their load levels becomes important in time and safety critical operations. This study is a pilot research investigating the effects of short-term memory retrieval, cognitive set shifting, and visual monitoring on the electrodermal response of humans, since electrodermal activity is one of the first responses in critical scenarios. 9 participants, 8 males and 1 female undergraduate student (Mean age = 22 years) from UTEP Industrial Engineering department participated in the study. Sternberg short-term working memory task, Wisconsin card sorting task and a standard tracking task respectively were used as the experimental tasks for each of the independent variables. Biosemi and Brain Products system was used for data acquisition and analysis. A linear mixed model fit to the data indicated that short-term memory retrieval (with amplitude as dependent variable Mean = 0.012μS, SD = 0.141μS, p = 0.022 ), (with reaction time as the dependent variable Mean = 1136.8030μS, SD = 472.705μS, p = 0.001 ) was significant. Significant correlations ( p = 0.022 ) were obtained between GSR amplitude and reaction time. Visual monitoring significantly affected the electrodermal response ( Mean = 0.0975μS, SD = 0.09290μS; p = 0.000 ). Electrodermal activity was also significantly affected by task novelty ( Mean = -2.65079E-4μS, SD = 0.025μS, p = 0.001 ). Electrodermal responses were integrated into an artificial neural network for classification of load levels. Neuroshell 2 software was used for modeling the neural architecture. Artificial neural network classified the electrodermal responses into task load levels namely, low, medium and high.
