Direct Integration of Ionic Liquid Gel Sensors onto Microfibrous Face Mask Substrates for Wearable Respiratory Health Monitoring.

Mask-integrated respiratory sensors are promising for noninvasive monitoring of respiratory health outside of clinical settings, for example, to support at-home patient monitoring and telemedicine. Studies have shown the feasibility of attaching flexible and off-the-shelf sensors to face masks; however, the potential benefits of incorporating sensor materials directly onto the breathable microfibrous mesh of face masks have hardly been explored. In this work, we integrate respiratory sensors on flat polyethylene terephthalate substrates and microfibrous polypropylene face masks using an ionic liquid gel (ILG) to detect changes in local humidity during breathing. Under a DC voltage, the ILG sensors exhibit a superlinear dependence of current on humidity, resulting in enhanced sensitivity at the high humidity levels found in exhaled breath. By varying the composition of the ILG, we find an inverse relationship between the sensing signal strength and sensing kinetics, offering insights into the sensing mechanisms. Freestanding ILG films are found to be resilient under mechanical strain with humidity sensing still possible at 120% strain. Devices that are scalably integrated onto face masks produce sensors that are four times less sensitive to extreme bending at an angle of 150°. Preliminary artificial intelligence (AI) analysis of breathing patterns identifies coughs that are interspersed with regular breathing with 91% accuracy, showing the potential of AI-supported wearable masks for autonomous symptom tracking.