Funded Projects

Design of human-computer interfacing has focused heavily on the form of visual feedback provided to users that they may use to voluntarily control actions. Only in the last decade have concerted attempts been made to tap directly into internal signals, such as electrophysiological response patterns, to provide instructions or feedback to computers. We will use ambulatory sensors to record physiological measures of heart-rate, heart-rate variability, electrodermal activity, thermodermal activity, fNIR measurements, and motoric variability while participants perform complex cognitive and sensorimotor tasks using digital feedback to develop new biomarkers predictive of increasing cognitive load and decreasing cognitive plasticity. Aim 1 will be to quantitatively characterize individual differences in physiological responses that are correlated with fluctuations in vigilance and performance accuracy in a simulated driving task. Aim 2 will be to test whether identified biomarkers are also predictive of user performance on an unrelated cognitive task requiring the entry and tracking of detailed medical status information. Empirically-driven customization of human-computer interfaces based on physiological profiles of users can potentially increase usability of existing systems and speed learning of new systems.