Open AccessBionic Ultra‐Sensitive Self‐Powered Electromechanical Sensor for Muscle‐Triggered Communication Application
Author(s) -
Zhou Hong,
Li Dongxiao,
He Xianming,
Hui Xindan,
Guo Hengyu,
Hu Chenguo,
Mu Xiaojing,
Wang Zhong Lin
Publication year - 2021
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.202101020
Subject(s) - bionics , triboelectric effect , nanogenerator , signal (programming language) , computer science , interface (matter) , sensitivity (control systems) , embedded system , electrical engineering , electronic engineering , materials science , engineering , piezoelectricity , artificial intelligence , bubble , maximum bubble pressure method , parallel computing , composite material , programming language
Abstract The past few decades have witnessed the tremendous progress of human–machine interface (HMI) in communication, education, and manufacturing fields. However, due to signal acquisition devices’ limitations, the research on HMI related to communication aid applications for the disabled is progressing slowly. Here, inspired by frogs’ croaking behavior, a bionic triboelectric nanogenerator (TENG)‐based ultra‐sensitive self‐powered electromechanical sensor for muscle‐triggered communication HMI application is developed. The sensor possesses a high sensitivity (54.6 mV mm −1 ), a high‐intensity signal (± 700 mV), and a wide sensing range (0–5 mm). The signal intensity is 206 times higher than that of traditional biopotential electromyography methods. By leveraging machine learning algorithms and Morse code, the safe, accurate (96.3%), and stable communication aid HMI applications are achieved. The authors' bionic TENG‐based electromechanical sensor provides a valuable toolkit for HMI applications of the disabled, and it brings new insights into the interdisciplinary cross‐integration between TENG technology and bionics.