QUASAR‘s dry sensor technology was designed with the intent of enabling easy comfortable physiological and cognitive monitoring in real-world environments.

The following is a select list of QUASAR research projects investigating a few possible applications of this ambulatory wearable sensor technology.

• EEG and Eye-Tracking Based Measures for Enhanced Screener Training

  The goal of this research project is to develop an improved Transportation Security Officers (TSO) training system, which will apply real-time brain-based measurements to provide a customized training experience that is optimally suited to the specific trainee. Specifically, this project is investigating the combination of Electroencephalography (EEG) and eye-tracking metrics for improving performance assessment on X-ray interpretation tasks. The effects of training on performance is being explored by comparing novice and expert screeners

• Hybrid EEG Sensor Array for Brain/Computer Interfaces

  Independent BCI use requires easily acquired, good-quality electroencephalographic (EEG) signals maintained over long periods in less-than-ideal electrical environments. Conventional, wet-sensor, electrodes require careful application. Faulty or inadequate preparation, noisy environments, or gel evaporation can result in poor signal quality. Poor signal quality produces poor user performance, system downtime, and user and caregiver frustration. This study demonstrates that a hybrid dry electrode sensor array (HESA) performs as well as traditional wet electrodes and may help propel BCI technology to a widely accepted alternative mode of communication.

• A Closed-Loop Neuroergonomic System for Adaptive Training

  The objective of this project is to demonstrate the feasibility of developing an integrated system that monitors and provides feedback on cognitive states to enhance and expedite warfighter training. The system collects, cleans, and processes neurophysiologic, physiological, and performance-based data in real-time from individuals and teams during training in a currently fielded simulation-based training environments.

• Integrated Adaptive Aiding System for UAV Control and Related Applications

  The main goal of this Phase II program is to develop a Closed-Loop Adaptive Aiding System (CLAAS) that improves UAV mission performance by adaptively reducing operator cognitive workload. We utilize QUASAR’s breakthrough wearable dry-electrode based physiological monitoring system to classify two operators’ cognitive states during a multi-UAV simulation task. Each operator’s cognitive states are combined with present and future mission context to predict the probability of failure (POF) due to operator error. To close the loop in this project, a supervisor is presented mission information along with each operator’s POF, and is then able to shift tasks from one operator to the other in order to reduce operator cognitive workload and hence enhance team mission performance.

• Real-Time Bio-Sensors for Enhanced C2ISR Operator Performance

  QUASAR has built an EEG headset for use in Command and Control, Intelligence, Surveillance, and Reconnaissance (C2ISR) missions, and developed software to classify workload and engagement. This system combines physiological real-time measurements with simulation context information to predict operator’s future Probability of Failure (POF).

• Wearable Electrophysiologic Sensor Suite for Detection of Neurotoxic Effects

  The goal of this STTR program was to develop and validate a gauge for impending cognitive dysfunction, especially that induced by neurotoxins, using only wearable sensors. A gauge is a set of algorithms that combines information from a number of indicators of brain and central nervous system activity to give a simple, one-dimensional alarm output. The term “wearable sensors” means that the component of the device that collects the signal does not have to be in intimate contact with the skin, and is small and lightweight.