Identifying Adverse Modes via Human-Machine Cybernetic Modeling
Abstract
System for Efficient, Accurate, and Precise Clinical Vestibular Threshold Testing. With our proposed basic science studies, we aim to understand, quantify, and model each of the fore-mentioned elementary components. In addition, we aim to combine these elements into a novel comprehensive cybernetic model. Finally, we aim to use models and experimental data to identify signatures of human-machine coupling that predict adverse modes using mathematical methods including critical transition approaches.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 08, 2020
- Source ID
- N000142012163
Entities
People
- Daniel Merfeld
Organizations
- Office of Naval Research
- Ohio State University
- United States Navy