Collaborative Technology Alliance (CTA) funded by US Army Research Lab
1) Neurocognitive Performance: Research efforts under this area are designed to ascertain key ‘signatures’ of how soldier neurocognitive state (i.e., emotional, perceptual-cognitive, physical, and physiological) varies in the face of the sensory, perceptual and cognitive demands of the operational environment.
2) Advanced Computational Approaches: Research within the second area is to provide novel computational, statistical modeling, and data visualization techniques for the extraction of the signatures of soldier neurocognitive performance, including novel analytic/algorithmic approaches to the individualized assessment of soldier neurocognitive state and performance.
3) Neurotechnologies: The third area efforts focus on the research underlying cutting-edge technologies for the real-time recording and analysis of environmental, behavioral, and functional brain dynamics, and on techniques for exploiting natural human neurocognitive function in technological solutions that enhance Soldier-system performance and safety.
I am the PI of the Neurotechnology area, and he is focusing on the following 2 topics:
1) Effects of Vehicle Motion and Cognitive Fatigue: True understanding of human behavioral decision-making under stress and cognitive fatigue in complex operational environments such as car driving with kinesthetic stimuli requires the direct study of the interactions between brain, behavioral, sensory, and performance dynamics – based on their simultaneous measurement and joint analysis. The goal of this study is to explore the principles and methods that can be used to design individualized real-time neuroergonomic systems to enhance operator situational awareness and decision making under several forms of stress and cognitive fatigue, and thereby, improve total human-system performance. Several research topics of driving performance including kinesthetic effect, arousal feedback, and the development of drowsiness prediction system has been conducted by me and my team. Regarding to investigate EEG dynamics in response to kinesthetic stimuli during driving, I used Virtual Reality (VR) based driving simulator with a motion platform to produce somatic sensation as in real-world situations. For arousal feedback study, I has investigated the brain dynamics and behavioral changes in response to arousing auditory feedback presented to individuals experiencing momentary cognitive lapses during a sustained-attention task. The results of this study demonstrated the amount of cognitive state information that can be extracted from noninvasively recorded EEG data and the feasibility of online assessment and rectification of brain networks exhibiting characteristic dynamic patterns in response to cognitive challenges. In terms to the drowsiness prediction system, I proposed a brain-computer interface based approach using spectra dynamics to classify driver’s alertness level and predict response time.
2) Wearable EEG Development and Testing: The goal of this research thrust is to design, develop and test the wearable and wireless dry-electrode (WWD) EEG human machine interface that can allow assessment of brain activities of participants actively performing ordinary tasks in natural body positions and situations within a real operational environment. Monitoring the neurophysiological activities of soldiers in an operational environment poses a severe measurement challenge using current laboratory-oriented biosensor technology. This research is to address the following scientific barriers: (1) the restriction of experimental designs to highly controlled and impoverished stimulus/response paradigms and environments, (2) the lack of portable, user-acceptable (e.g., comfortably wearable), and robust systems for routinely monitoring brain and body dynamics, (3) the failure to record the whole of physical, mental, and physiological behavior that the brain controls, and the physical and socio-cultural effects of the environment that impact brain function, in sufficient detail and across a sufficient breadth of circumstances. In this project, I and my team had successfully investigated and developed methods for assessing individual cognitive status and performance in military environments using his WWD EEG devices. He also developed and evaluated on-line signal-processing methods for artifact removal of the EEG data acquired by the WWD EEG devices. In addition, motion-induced artifacts will heavily contaminate EEG recordings acquired by either wet or dry sensors in real-world applications. It was found that the amplitudes of motion-induced artifacts could be 10 times larger than those arising from blinks, eye-movements, and muscle activities in conventional EEG laboratories. I and my team incorporated wearable motion (inertial) sensors into the WWD EEG devices by integrating dry EEG sensors, 3D accelerometers, 3D gyros, and 3D compass to track the head/neck potions and postures, making possible to regress out the overwhelming motion-induce artifacts from the EEG recordings. This task truly enabled monitoring of neural activities in unconstrained, freely-moving participants performing ordinary tasks in natural head/body positions and situations, and studying participants involving in active cognition.