Adaptive Aiding Implemented by

Psychophysiological monitoring of operator state has been developed over the past decades as measures of mental workload, fatigue, and inattention. This paper provides examples of the application of these measures to classify operator functional state (OFS) and further to implement adaptive aiding. Examples using several levels of mental workload are presented to show that combinatorial classifiers can utilize the information from several psychophysiological measures to provide highly accurate correct classification of OFS. An example of adaptive aiding, using on-line assessment of OFS, demonstrated that highly accurate classification could be achieved and that using this information to control adaptive aiding enhanced performance of a complex task. A model of how psychophysiological and performance data could be used to provided continuous OFS monitoring and adaptive aiding is presented.