CRII: CPS: Wearable-Machine Interface Architectures

点击翻译按钮获取中文摘要

Wrist-worn wearable devices provide rich sets of pulsatile physiological data under various modalities and circumstances. An unexploited capability is that the pulsatile physiological time series collected by wrist-worn wearable devices can be used for recovering internal brain dynamics. 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 research is integrated with education and outreach activities with an emphasis on increasing the participation of minorities in science and engineering. These activities include hosting hands-on STEM events for elementary school and high school students, hosting undergraduate research interns, and creating educational videos. This proposal presents two design classes of WMI architectures related to mental stress: (1) A decoder that recovers undesired stimuli-triggered brain pulses from wrist-worn wearables and a controller that delivers closed-loop intermittent stimulation to reverse the adverse effect of undesired stimuli; and, (2) a decoder that recovers undesired stimuli-triggered inhibition of pulsatile physiological profile from wrist-worn wearables and a controller that delivers closed-loop intermittent stimulation to generate the desired pulsatile physiological profile. The proposed methods will be validated by analyzing electro-dermal activity as well as concurrent cortisol and adrenocorticotropic hormone pulsatile data in the context of mental-stress-related arousal and fatigue.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.