A conformable sensory face mask for decoding biological and environmental signals

Face masks are used to reduce exposure to viruses and other environmental hazards such as air pollution, and integrating wearable electronics into face masks could provide valuable insights into personal and public health. However, relevant wearable devices are typically designed only to monitor biological information such as breathing patterns, and do not provide information about the status of the face mask. Here we report a conformable sensory interface that can be attached to the inside of any user-supplied face mask and used to monitor signals related to infectious diseases, environmental conditions and wear status of the face mask. Multimodal signals from the sensory face mask are wirelessly transmitted to a server through a custom-made mobile app. The system can simultaneously monitor multiple signals, including skin temperature, humidity, verbal activity, breathing pattern and fit status of the face mask. We also develop a machine learning algorithm that can be used to reliably decode the face mask position.