2021/06/13 by Soha Rostaminia, S. Zohreh Homayounfar, Rostaminia, Soha +7
Computer Science · Engineering · Neuroscience · #EEG and Brain-Computer Interfaces #FOS: Computer and information sciences #FOS: Electrical engineering #Gaze Tracking and Assistive Technology #Human-Computer Interaction (cs.HC) #Signal Processing (eess.SP) #Sleep and Wakefulness Research #cs.HC #eess.SP #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2106.07645
openalex publication_date 2021/06/13 · arxiv created 2021/08/11 · arxiv updated 2021/08/12 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Clinical-grade wearable sleep monitoring is a challenging problem since it requires concurrently monitoring brain activity, eye movement, muscle activity, cardio-respiratory features and gross body movements. This requires multiple sensors to be worn at different locations as well as uncomfortable adhesives and discrete electronic components to be placed on the head. As a result, existing wearables either compromise comfort or compromise accuracy in tracking sleep variables. We propose PhyMask, an all-textile sleep monitoring solution that is practical and comfortable for continuous use and that acquires all signals of interest to sleep solely using comfortable textile sensors placed on the head. We show that PhyMask can be used to accurately measure sleep stages and advanced sleep markers such as spindles and k-complexes robustly in the real-world setting. We validate PhyMask against polysomnography and show that it significantly outperforms two commercially-available sleep tracking wearables, Fitbit and Oura Ring.