Sensing and Representing Negative Effects of Motion (SERENE)

Exposure to motion degrades operational effectiveness across the Navy, with results ranging from simple motion-induced interruptions (MIIs) to more severe perceptual, cognitive, and motor deficits. Even those who do not suffer from acute motion sickness often experience some level of sopite syndrome, characterized by persistent fatigue and drowsiness. While many research efforts have investigated motion sickness symptoms, there has been little progress in developing real-time sensors for assessing motion exposure and related performance degradation. This capability is needed by the Navy to ensure mission success. To provide this capability, we propose to design and demonstrate a framework for Sensing and Representing Negative Effects of Motion (SERENE). SERENE has three parts: (1) a suite of inexpensive and unobtrusive sensors that synchronously collect physiological, behavioral, and environmental indicators of motion exposure; (2) a fusion engine that combines Complex Event Processing for real-time extraction of indicators from raw sensor inputs, with probabilistic models to detect motion sickness symptoms and MIIs from those indicators; and (3) a hybrid suite of cognitive models that analyze degradation to perceptual, cognitive, and motor performance based on fusion results. Combined, these components provide a real-time assessment framework to detect, predict, and potentially prevent negative effects of motion exposure.