Stretchable Self-Powered TENG Sensor Array for Human-Robot Interaction Based on Conductive Ionic Gels and LSTM Neural Network

被引:6
|
作者
Dong, Wentao [1 ,2 ]
Sheng, Kaiqi [1 ]
Huang, Bo [1 ]
Xiong, Kun [1 ]
Liu, Kun [1 ]
Cheng, Xiao [1 ]
机构
[1] East China Jiaotong Univ, Sch Elect & Automat Engn, Nanchang 330013, Peoples R China
[2] Huazhong Univ Sci & Technol, State Key Lab Intelligent Mfg Equipment & Technol, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Sensors; Hydrogels; Rubber; Robot sensing systems; Monitoring; Neck; Human-robot interaction; Electrodes; Sensor arrays; Long short term memory; Conductive ionic gels; human-robot interaction (HRI); long and short time memory (LSTM) neural network; self-powered sensor; triboelectric nanogenerator sensor array (TENG-SA);
D O I
10.1109/JSEN.2024.3464633
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The flexible and stretchable self-powered sensors are widely applied to the Internet of Things (IoT), human motion monitoring, and human-robot interaction (HRI), and it reveals more and more attentions due to the flexibility and self-powered function. This article focuses on the stretchable triboelectric nanogenerator (TENG) sensor for human gesture monitoring and HRI application based on conductive ionic gels and machine learning. Stretchable self-powered TENG sensor is fabricated by solution method based on polyacrylamide (PAAM)/NaCl conductive hydrogel and silicone rubber. The self-powered TENG sensor array (TENG-SA) is applied to gesture detection at different parts (wrist, elbow, knee, and neck) of human body successfully without external power supply. Conductive PAAM/NaCl hydrogel could be stretched up to 307%, which satisfies the deformation of the human joints. Intelligent sensing system is designed and developed to control the motion of two-wheeled robot through TENG-SA and long and short time memory (LSTM) neural network via Bluetooth. Experiments have demonstrated that the neck motion signals are collected and recognized by intelligent TENG-SA system with LSTM neural network during the neck rotation process, which is applied to control the motion of two-wheeled robot successfully. HRI based on self-powered TENG sensor will promote the interaction among humans and machines/robots to improve the disabled for rehabilitation, medical monitoring, and human-robot cooperation.
引用
收藏
页码:37962 / 37969
页数:8
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