A Moisture‐Proof, Anti‐Fouling, and Low Signal Attenuation All‐Nanofiber Triboelectric Sensor for Self‐Powered Respiratory Health Monitoring - Chen, Xiao; Peng, Xiao; Wei, Chuanhui; Wang, Zixun; He, Jin; Sheng, Hengrui; Jiang, Tao; Dong, Kai (Advanced functional materials, 2025)
Breathing is an important physiological health indicator of the human body. Real time and long‐term monitoring with low attenuation of human respiratory health status is of great significance. However, the working performance of respiratory sensors typically placed at the mouth and nose of the human body is greatly affected by exhaled moisture and small pollutants. Here, an all‐nanofiber self‐powered respiratory sensor (ASRS) with a multi‐layer stacking structure is developed based on contact electrification or triboelectrification effect. By spraying method to chemically graft low surface energy octadecyltrichlorosilane (OTS) small molecules onto the surface of nanofibers, the ASRS is endowed with excellent superhydrophobicity and self‐cleaning properties, making it free from the influence of high humidity and small particle pollutants in exhaled gas. Due to the gradient variation of contact interface with increasing pressure, the ASRS exhibits a multi‐stage linear sensitivity response trend, which has high pressure response sensitivity of 0.048 kPa−1. In addition, the ASRS is further integrated on a smart mask for real‐time and long‐term monitoring of respiratory health status, including age and gender of subjects, physical activity status, and sleep apnea syndrome. This work provides an effective self‐powered sensing strategy for daily physiological monitoring, proactive healthcare, and early disease warning. An all‐nanofiber self‐powered respiratory sensor (ASRS) with moisture‐proof, anti‐fouling, high sensitivity, and low signal attenuation ability has been developed based on triboelectric effect, which can avoid the influence of high humidity and small particle pollutants in exhaled gas. The ASRS is further integrated on a smart mask for real‐time and long‐term monitoring of multiple respiratory health states.