Author: Rostaminia, Soha; Homayounfar, S. Zohreh; Kiaghadi, Ali; Andrew, Trisha L.; Ganesan, Deepak
Title: PhyMask: Robust Sensing of Brain Activity and Physiological Signals During Sleep with an All-textile Eye Mask Cord-id: ulnfzh1s Document date: 2021_6_13
ID: ulnfzh1s
Snippet: 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,
Document: 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.
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