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Meeting	ACGS Committee Meeting 126 - Virtual - March 2021
Agenda Location	4 GENERAL COMMITTEE TECHNICAL SESSION 4.1 STI
Title	STI
Presenter	Dave Klyde
Available Downloads*	presentation
	Downloads are available to members who are logged in and either Active* or attended this meeting.
Abstract	For the decades that followed the publishing of the Cooper-Harper report that resulted in the handling qualities pilot rating scale, researchers have sought to correlate pilot compensation – as well as physical and mental workload – with the assigned rating, though a quantitative correlation between workload and handling qualities ratings remains elusive. In recent years, new physiological measurement devices have been developed that together with software processing tools can provide accurate measures of psychophysiological measures including cognitive workload, distraction, and high/low engagement based on electroencephalogram (EEG) and electrocardiogram (ECG) measures (i.e., brain waves and heart rate variability). The pilot compensation referred to in the Cooper-Harper scale is also a function of task performance measures that reflect aircraft characteristics and inceptor activity that reflects upon physical workload. Using a flight test database generated in the Calspan Learjet In-Flight Simulator with five experienced test pilots, a machine learning-based software algorithm that integrates a disparate mix of pilot-vehicle system, physiological, and task performance measures was used to demonstrate feasibility of an approach to predict handling qualities level and ratings.