SBIR-STTR Award

The Screen-ADAPT system utilizes advances in brain-based sensory technology to develop an advanced training system for baggage screeners that will substantially improve initial and sustainment training over current practices by providing simulated training using real-world data pinpointing specific training deficiencies related to visual inspection skills. Screen-ADAPT incorporates a suite of measurement tools, including cognitive state and behavioral metrics, and system metrics to quantify and diagnose screening skills/deficiencies in real-time, triggering adaptive feedback within a scenario and AAR. Screen-ADAPT provides next-generation neurophysiology-driven, individualized training that ensures appropriate cognitive training states and targets specific training deficits identified, optimizing training sessions with the goal of increased threat detection accuracy and efficiency. Screen-ADAPT will be one of the first real-time, closed-loop training systems that incorporate considerate adaptations as well as AAR feedback that effectively diagnoses training deficiencies, root cause(s) of error patterns, and provides individualized training recommendations to optimize training effectiveness and efficiency. The proposer`s commercialization strategy centers on marketing a completed Screen-ADAPT tool to domestic airports; security and screening checkpoints throughout the US will also be targeted. There are also a wide variety of visual monitoring/inspection tasks that could benefit from a Screen-ADAPT training system: container screening, border patrol personnel, video surveillance security.

Transportation Security Administration (TSA) Officers are at the forefront of our nation`s security, and are tasked with screening every bag boarding commercial aircraft within the United States. It is a repetitive visual search task that has a very low probability of encountering a threat, but extremely high consequences if a serious threat is missed. Currently, training instructors base their assessments of trainee progress solely on performance outcomes and observation from classroom and on the job performance. This effort will develop an advanced adaptive training system for baggage screeners using a combination of physiological and neurophysiological measures, including EEG, eye tracking, and heart rate to gain insights into an officer`s `unobservable` behavior, and advanced training science to diagnose and mitigate training deficiencies/inefficiencies in real-time to optimize individualized, precision training. measures can provide insights into cognitive processing during baggage screening tasks and indicate training proficiency via continuous monitoring of workload, drowsiness, and distraction, as well as expertise level. Performance, cognitive state, expertise level, and eye tracking will be used to drive real time training adaptations and after-action reviews. The goal of the proposed adaptive training system is to provide individualized, tailored training to optimize training, effectiveness and efficiency.