Stretchable and Self-Healable Acoustic Sensor for Fast Respiratory Diseases Identification Based on Biocompatible...

The complex process and high costs of respiratory diseases diagnostic brought a heavy burden on patients. Traditional lung auscultation enables rapid respiratory assessment but is experience-dependent, leading to diagnostic inaccuracy. Wearable sensors acquire accurate pulmonary signals for diagnosis but lack sufficient stretchability to maintain skin contact during breathing, leading to interfacial detachment and data corruption. In this study, a stretchable and self-healable acoustic sensor is fabricated based on bio-based piezoelectric elastomer (BBPE) to realize fast respiratory diseases identification. The BBPE is synthesized with mass of C═O dipoles to achieve high piezoelectricity, and its long backbone and crosslinking network ensure low elastic modulus and high stretchability. Thus, the piezoelectric acoustic sensor can sensitively respond to sound sources with a detection error of less than 0.1%. By converting the pulmonary sounds into voltage signal, the acoustic sensor can effectively identify several types of respiratory diseases. Besides, the acoustic sensor shows a high elongation over 1200% and enables rapid self-healing efficiency over 79% with cut damage at 37°C, ensuring high accuracy and long lifetime. Thus, the stretchable and self-healable acoustic sensor shows great potential in fast respiratory diseases identification fields.