Establishing the Psychophysiological Variables that can Identify & Predict Operator Subjective State

Abstract

Biocybernetic adaptation describes a system wherein automation is regulated by the operator's physiology. The identification of real-time psychophysiological variables capable of detecting and predicting operator subjective states is an important requisite for biocybernetic control. The present study investigated how psychophysiology may index negative subjective states, namely, task-disengagement, distress and worry.

To encourage negative states, 35 participants performed the (high demand) Multi-Attribute Task Battery (MATB), for 100 minutes in total. Subjective state was assessed using the Dundee Stress State Questionnaire (DSSQ). The psychophysiological measures recorded included: GSR, EOG, EEG, ECG, and respiration. Analysis of the data revealed performance was sustained throughout the task although subjective states became more negative over time. This was accompanied by various psychophysiological changes, e.g. increased respiration rate. Regression analyses indicated that psychophysiological changes were predictive of changes in subjective states. The results and implications for biocybernetic systems are discussed.