We propose to use physiological sensors to measure the quality of a trainees interaction with a virtual environment (VE) as a function of VE fidelity to enable design improvements in VEs and to enhance training effectiveness through feedback of physiological-based performance information. Currently, VE design is guided by subjective design models that involve multiple design iterations and focus on trial and error. Our approach is innovative and new because it quantifies VE fidelity requirements in terms of desired behavioral patterns in the trainee as quantified by recordable brain and peripheral bioelectrical signals. Our team has a proven track record in physiological measurement and operator performance modeling. Our team consists of a small business, a research institution, a large business commercialization partner, and a DoD collaborator. We will collaborate with the Naval Air Warfare Center Training Systems Division to enhance Navy training effectiveness through integration of physiological assessment modules into existing training systems. Our approach will test VE fidelity from simulation to real-world flight. We have a tentative, additional Phase II funding commitment in the amount of $200k over the two years of phase II from an outside industrial partner.
Benefit: We call the proposed tool the Quality of Training Effectiveness Assessment (QTEA) system. It provides designers of virtual environments (VEs) with a physiological-based quantitative method to determine VE fidelity requirements by comparing behavioral patterns collected in the virtual environment with the desirable behavioral patterns associated with good transfer of training. A recent report by Frost & Sullivan indicates that reducing the cost of simulators and VEs is key to market growth and we are confident that quantitative assessment of simulator/VE fidelity requirements with a tool such as QTEA will save the government millions if not billions of training related dollars by avoiding over-specification of training systems hardware and software. Also, since the QTEA system will be able to quantify a trainees performance on the basis of real-time physiological based measures, it will be possible to modify a given training scenario in real-time to enhance the learning experience.
Keywords: brain signals, brain signals, bioelectrical signals, Physiological-based training effectiveness assessment, Electroencephalogram (EEG), Eye Tracking, virtual environment fidelity requirements, transfer of training
