NIH Maximizing Investigator’s Research Award – MESH: Multimodal Estimators for Sensing Health
- Project Overview (NIH #1R35GM151353-01)
The goal of this project is to develop an interdisciplinary research program and a foundational algorithmic framework for reliably inferring health states from physiological signals acquired using wearable and portable physiological monitoring devices to address a compelling but unfulfilled need to quantify hidden health states of inflammation, metabolism, fatigue and interoceptive awareness. The proposed research will use de-identified data both from publicly available datasets and those collected by the medical collaborators (e.g., endocrinology, rheumatology, neurosurgery, psychiatry, neuroscience) using wearable or portable devices to perform signal analysis and compare the results against previously published results, known experimental settings, and clinical knowledge to validate the models and provide new insight.
NSF CAREER Project – MINDWATCH
The goal of this project is to pioneer a closed-loop brain-aware wearable architecture called MINDWATCH. This enables (1) decoding multidimensional brain states from noninvasive wearable devices and (2) applying corrective control. MINDWATCH will transform healthcare delivery (e.g., aging, autism, dementia) as well as human performance and productivity enhancement (e.g., online learning, smart workplaces). The proposed framework will (1) infer discrete brain-related events in real-world settings, (2) decode multidimensional latent neurobehavioral states based on inferred brain activity, and (3) apply robust adaptive control to maintain the neurobehavioral states within desired ranges. The closed-loop framework will be rigorously validated using experiments on interactive human-technology environments and mental health.
NSF CRII: CPS: Wearable-Machine Interface Architectures
- Project Overview (NSF #1755780)
The goal of this project is to present wearable machine-interface (WMI) architectures related to mental stress and their potential applications for tracking fatigue and arousal states. Decoding brain states using wrist-worn wearables will transform how mental-stress-related diseases are diagnosed and treated. The proposed methods will be validated by analyzing electrodermal activity as well as concurrent cortisol and adrenocorticotropic hormone pulsatile data in the context of mental-stress-related arousal and fatigue.