JOURNAL ARTICLE

A Self-Powered, Skin Adhesive, and Flexible Human–Machine Interface Based on Triboelectric Nanogenerator

Xujie WuZiyi YangYu DongLijing TengDan LiHang HanSimian ZhuXiaomin SunZhu ZengXiangyu ZengQiang Zheng

Year: 2024 Journal:   Nanomaterials Vol: 14 (16)Pages: 1365-1365   Publisher: Multidisciplinary Digital Publishing Institute

Abstract

Human–machine interactions (HMIs) have penetrated into various academic and industrial fields, such as robotics, virtual reality, and wearable electronics. However, the practical application of most human–machine interfaces faces notable obstacles due to their complex structure and materials, high power consumption, limited effective skin adhesion, and high cost. Herein, we report a self-powered, skin adhesive, and flexible human–machine interface based on a triboelectric nanogenerator (SSFHMI). Characterized by its simple structure and low cost, the SSFHMI can easily convert touch stimuli into a stable electrical signal at the trigger pressure from a finger touch, without requiring an external power supply. A skeleton spacer has been specially designed in order to increase the stability and homogeneity of the output signals of each TENG unit and prevent crosstalk between them. Moreover, we constructed a hydrogel adhesive interface with skin-adhesive properties to adapt to easy wear on complex human body surfaces. By integrating the SSFHMI with a microcontroller, a programmable touch operation platform has been constructed that is capable of multiple interactions. These include medical calling, music media playback, security unlocking, and electronic piano playing. This self-powered, cost-effective SSFHMI holds potential relevance for the next generation of highly integrated and sustainable portable smart electronic products and applications.

Keywords:
Nanogenerator Triboelectric effect Computer science Microcontroller Electronics Electronic skin Wearable computer Robotics Wearable technology Embedded system Materials science Electrical engineering Nanotechnology Artificial intelligence Voltage Robot Engineering

Metrics

8
Cited By
2.94
FWCI (Field Weighted Citation Impact)
51
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Sensor and Energy Harvesting Materials
Physical Sciences →  Engineering →  Biomedical Engineering
Tactile and Sensory Interactions
Life Sciences →  Neuroscience →  Cognitive Neuroscience
Conducting polymers and applications
Physical Sciences →  Materials Science →  Polymers and Plastics
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