PhyMask: Robust Sensing of Brain Activity and Physiological Signals During Sleep with an All-textile Eye Mask
This addresses the problem of uncomfortable and inaccurate sleep monitoring for users needing clinical-grade data, offering a practical and comfortable alternative.
The researchers tackled the challenge of clinical-grade wearable sleep monitoring by developing PhyMask, an all-textile eye mask that accurately measures sleep stages and markers like spindles and k-complexes, outperforming Fitbit and Oura Ring in validation against polysomnography.
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.