This study examined the utility of an airplane adaptive automation piloting system that determines optimal task allocation based on pilot EEG data. In a replication and expansion of the study of A.T. Pope et al. (1995), EEG data were recorded for 48 undergraduate and graduate students (aged 18-40 years) while completing a modified version of the Multiattribute Task Battery (J.R. Comstock and R.J. Arnegard, 1992), which comprised monitoring, compensatory tracking, communication, and resource management activities similar to those undertaken by airplane crew members during flight. The system made allocation decisions as a function of the level of operator engagement based on EEG data. Results show that it was possible to moderate an operator's level of engagement through a closed-loop system driven by the operator's own EEG. More task allocations were made under multiple-compared with single-task conditions. The system exerted a significant impact on behavioural, subjective, and psychophysiological correlates of workload as task load increased. (A)
Samenvatting