Logo image
Clothing-Integrated Multifunctional Ultrasensitive Triboelectric Acoustic Textile for Real-Time Heart Sound Monitoring, Remote Communication, and Voice Assistant
期刊文章   同儕審查

Clothing-Integrated Multifunctional Ultrasensitive Triboelectric Acoustic Textile for Real-Time Heart Sound Monitoring, Remote Communication, and Voice Assistant

Beibei Shao, Zhi-Xian Yan, Tai-Chen Wu, Tien-Yu Ko, Wei-Chen Peng, Wei-Chun Yang, Kai-Yuan Hsiao, Jiun-Wei Fong, Ming-Han Lu, Cheng-Hung Tsai, …
Advanced functional materials, 卷.36(8), e21860
01/01/2026
Web of Science ID: WOS:001597493500001

摘要

Chemistry Chemistry, Multidisciplinary Chemistry, Physical Materials Science, Multidisciplinary Nanoscience & Nanotechnology Physics, Applied Physics, Condensed Matter Science & Technology Science & Technology - Other Topics Materials Science Physical Sciences Physics Technology
Real-time acoustic detection is critical for auscultation, communication, and human-artificial intelligence (AI) interactions. However, conventional acoustic sensors are bulky, rigid, and power-hungry, limiting their applicability in wearables. Developing sound perception into textiles presents a promising yet challenging pathway for intuitive and imperceptible interfaces. Here, a multifunctional, scalable, ultrasensitive, and self-powered triboelectric acoustic textile (MTA-Textile) that enables real-time sound sensing while possessing fabric properties including light weight, flexibility, and washability is reported. It supports diverse functionalities, including real-time cardiac auscultation, remote communication, voice recognition, and voice assistants, seamlessly integrated into everyday clothing. The multilayered MTA-Textile comprises a MoS2 nanocomposite coating for charge trapping and transport and a graphite-like textile for charge storage. This synergistic architecture maximizes charge generation and retention, delivering high output (18.3 V), exceptional sensitivity (3 V Pa-1) at low-intensity, low-frequency regions (<80 dB, <250 Hz), high signal-to-noise ratio (SNR) (57.5 dB), fine resolution (1 Hz), and long-term stability (36600 s retention, >10 000 cycles). The first garments serving as textile-based stethoscopes and voice intercom systems are demonstrated. With deep learning (DL)-enabled vocal command recognition, users can engage computing systems by speaking directly to the textile. This work advances next-generation acoustic wearables for healthcare, smart clothing, and human-AI interfaces.

相關連結

詳細資料

Logo image