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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 all the signals required for precise sleep stage tracking and to extract advanced sleep markers such as spindles and K-complexes robustly in the real-world setting. We validate PhyMask against polysomnography (PSG) and show that it significantly outperforms two commercially-available sleep tracking wearables—Fitbit and Oura Ring. 

Wearable electromechanical sensors are essential to improve health monitoring and off‐site point‐of‐care applications. However, their practicality is restricted by narrow ranges of detection, failure to simultaneously sense static and dynamic pressures, and low durability. Here, an all‐fabric pressure sensor with high sensitivity in a broad range of pressures, from subtle heart pulses to body posture, exceeding that of previously‐reported sensors is introduced. By taking advantage of chemical vapor deposition of p‐doped poly(3,4‐ethylenedioxythiophene) chloride (PEDOT‐Cl) on two natural textiles (cotton gauze and cotton balls), multiscale tunable pressure sensitivity with low power demand for data read‐out is obtained. To protect the sensor against humidity induced degradations, the sensor is encapsulated with a hydrophobic coating that leads to ultrastability of the sensor performance even after 1 week of exposure to 100% relative humidity and 20 laundry cycles. The sensor reveals excellent performance retention of >99% over 70 000 bending cycles under ambient conditions. The varied utility of this sensor for health monitoring is demonstrated by recording heartbeats, respiration, and joint movements. Furthermore, using this sensor, grip strength is successfully detected by 93.6% accuracy as compared to commercial dynamometer, speaking of its potential as the first fabric‐based sensor allowing for personalized real‐time grip strength analysis.

 

The strategy of detecting physiological signals and body movements using fabric-based pressure sensors offers the opportunity to unobtrusively collect multimodal health metrics using loose-fitting, familiar garments in natural environments. (A. Kiaghadi, S. Z. Homayounfar, J. Gummeson, T. Andrew, and D. Ganesan,Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.,3, 1–29 (2019)). However, many sensing scenarios, such as sleep and posture monitoring, involve an added static pressure from exerted body weight, which overpowers weaker pressure signals originating from heartbeats, respiration and pulse and phonation. Here, we introduce an all-fabric piezoionic pressure sensor (PressION) that, on account of its ionic conductivity, functions over a wide range of static and dynamic applied pressures (from subtle ballistic heartbeats and pulse waveforms, to larger-scale body movements). This piezoionic sensor also maintains its pressure responsivity in the presence of an added background pressure and upon integration into loose-fitting garments. The broad ability of PressION to record a wide variety of physiological signals in realistic environments was confirmed by acquiring heartbeat, pulse, joint motion, phonation and step data from different body locations. PressION’s sensitivity, along with its low-cost fabrication process, qualifies it as a uniquely useful sensing element in wearable health monitoring systems.