Janus triboelectric–LIG integrated smart mask for humidity-resistant dual-modal respiratory monitoring and intelligent analysis

Wearable respiratory monitoring systems capable of reliable operation under humid conditions are highly desirable for personalized healthcare, yet remain challenging due to moisture-induced signal instability and limited multimodal integration. Herein, we present an airflow–temperature dual-modal respiratory monitoring system (ATDM) integrated into a wearable mask for synchronized acquisition of respiratory airflow and thermal signals. The system integrates a Janus-structured triboelectric nanogenerator for airflow sensing and a flexible laser-induced graphene-based temperature sensor for thermal monitoring. The Janus structure effectively suppresses humidity-induced signal degradation, enabling stable operation even under high respiratory moisture conditions. Beyond sensing functionality, the device also exhibits efficient particulate filtration and antibacterial activity, ensuring practical wearing safety. By fusing airflow and temperature signals through a convolutional neural network model, the system achieves an overall classification accuracy of 99.17% for multiple respiratory states, including normal, slow, deep, fast breathing, and apnea. This work demonstrates a robust strategy for self-powered, humidity-resistant respiratory monitoring and highlights the potential of multimodal wearable systems for intelligent health management.