TRIEPOD Tool for Real-time Intelligent Evaluation of Physiological and Operational Data

We propose to develop a Tool for Real-time Intelligent Evaluation of Physiological and Operational Data (TRIEPOD), consisting of a self-contained sensor suite and assessment model for analyzing human and system performance. By combining intelligent behavioral and cognitive performance assessment methods with physiological state measures, the TRIEPOD system will not only identify instances of sub-optimal task performance, but also provide insight into the proficiency of human operators and the effectiveness of the operational system. The objective is to provide an automated tool that can both inform design decisions in the iterative development cycle for an operational environment, and also be leveraged for training with real-time performance feedback and after action review. TRIEPOD will be developed following a methodology that allows us to integrate the assessment model with existing normative behavior data and augment this by deriving additional data for normative expectations. We have assembled a multi-disciplinary team for the proposed research, combining expertise in the fields of cognitive science for model development, artificial intelligence for automated performance assessment, and augmented cognition for collecting and interpreting physiological data. Phase I will result in a system design and concept demonstration that lay the groundwork for full prototype implementation in Phase II.