Triboelectric Self‐Powered Airflow Sensor with Breakthrough Ultralow Airflow Speed Response for Wind Speed Detection and Respiration Monitoring

High‐sensitivity and high‐accuracy sensors are crucial for environmental and health monitoring. However, traditional distributed wind speed sensors commonly suffer from high start‐up wind speeds and external power dependency. Meanwhile, wearable respiratory monitoring devices face challenges such as limited sensitivity and a lack of adaptive power supply. Herein, this work proposes a self‐powered capacitive high‐sensitivity triboelectric airflow sensor (CHTAS). This sensor exploits triboelectric‐electrostatic induction and fluid‐solid coupling effects to achieve an ultralow start‐up airflow (0.1 m/s) and the corresponding equivalent dynamic pressure is only 0.006 Pa, breaking a new record for TENG‐based airflow speed sensing. CHTAS features expeditious response (response time 29 ms, recovery time 27 ms) and a wide range (0.1–10 m/s). Integrated with self‐developed software, CHTAS achieves high‐precision wind speed detection. Furthermore, its ability to be miniaturized and integrated into face masks enables wireless, real‐time respiratory monitoring, intelligent‐assisted identification of sleep‐disordered respiration and the exploration of potential interventions for sleep paralysis. Notably, by combining deep learning for respiratory state recognition, the system achieved a 91.06% recognition mean accuracy. This work paves a new technological path for the development of airflow sensing technology and wearable medical devices.