Bionic Ultra‐Sensitive Self‐Powered Electromechanical Sensor for Muscle‐Triggered Communication Application

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.

Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems

“…The authors further utilized this sEMG patch for the HMI application, where the emotion instructions from voice loss/impaired person can be vividly represented by a virtual character (Figure 7i). In another example reported by Zhou et al, [ 117 ] they decoded the muscle motions information using a bionic triboelectric nanogenerator‐based electromechanical sensor. Because of this triboelectric sensor's high sensitivity (54.6 mV mm −1 ), the signal intensity from face muscles is much higher (i.e., 206 times) than that of the sEMG approach aforementioned above.…”

“…Functionalities loss, either for newborn babies or for impaired people for various reasons such as accidents or aging effects, is becoming a great burn for the disabled themselves and their families and society. [117][118][119] Wearable devices provide an efficient and straightforward way for the disabled to interact and communicate with environments. For instance, one way for speech-impaired persons to communicate with others is sign language which is conveyed by the hands, face and body.…”

Progress in the Triboelectric Human–Machine Interfaces (HMIs)-Moving from Smart Gloves to AI/Haptic Enabled HMI in the 5G/IoT Era

“…Apart from the eye movements, fluctuations induced by the movements of other facial muscles, e.g., masseter muscle, etc., are also good choices to be translated into control command as communication aid HMI for the disabled [160]. Inspired by the frogs' croaking behavior, Zhou et al reported a bionic TENG-based sensor for masseter muscle motion monitoring as illustrated in Figure 3c [161]. By imitating the oral structure and acoustic capsule, the flexible PDMS elastomer was made into a sensing membrane and a deformable vibrating membrane, with an air layer as the spacer, to amplify the small fluctuations of the masseter muscle into a significant movement of the vibrating membrane, due to the varying deformations of films with different radiuses under the same volume change.…”

Recent Advances in Self-Powered Piezoelectric and Triboelectric Sensors: From Material and Structure Design to Frontier Applications of Artificial Intelligence

“…This friction nanogenerator can be used to capture the energy of wind and raindrops in the natural environment. Zhou et al [119], inspired by frogs' croaking behavior, a developed a bionic TENG. The TENG consisted of a bottom electrode based on Ag NWs, a composite triboelectric layer based on Ag NWs/BaTiO 3 NPs/PDMS, and a top electrode based on carbon.…”

“…(c) Working principle of the bionic structure reflecting morphology of the frog when it croaks. Reprinted from Ref [119]…”