An in-flight multimodal data collection method for assessing pilot cognitive states and performance in general aviation

This paper presents a comprehensive in-flight multimodal data collection methodology designed for assessing pilot cognitive states and performance in general aviation settings. The method integrates multiple data streams including physiological measurements, eye tracking, flight performance metrics, and behavioral observations to provide a holistic assessment of pilot cognitive states during actual flight operations. The approach enables researchers to capture real-world pilot performance data that can inform training program development, workload assessment, and safety enhancement initiatives. This methodology serves as a practical guide for researchers and practitioners seeking to implement multimodal data collection in aviation contexts.