Strain-Temperature Dual Sensor Based on Deep Learning Strategy for Human-Computer Interaction Systems.

Journal: ACS sensors
PMID: 39068608

Abstract

Thermoelectric (TE) hydrogels, mimicking human skin, possessing temperature and strain sensing capabilities, are well-suited for human-machine interaction interfaces and wearable devices. In this study, a TE hydrogel with high toughness and temperature responsiveness was created using the Hofmeister effect and TE current effect, achieved through the cross-linking of PVA/PAA/carboxymethyl cellulose triple networks. The Hofmeister effect, facilitated by Na and SO ions coordination, notably increased the hydrogel's tensile strength (800 kPa). Introduction of Fe/Fe as redox pairs conferred a high Seebeck coefficient (2.3 mV K), thereby enhancing temperature responsiveness. Using this dual-responsive sensor, successful demonstration of a feedback mechanism combining deep learning with a robotic hand was accomplished (with a recognition accuracy of 95.30%), alongside temperature warnings at various levels. It is expected to replace manual work through the control of the manipulator in some high-temperature and high-risk scenarios, thereby improving the safety factor, underscoring the vast potential of TE hydrogel sensors in motion monitoring and human-machine interaction applications.

Authors

  • Xiaolong Wu
    Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
  • Xiaoyu Yang
    Beijing Jishuitan Hospital, Beijing, China.
  • Peng Wang
    Neuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Zinan Wang
    School of Energy, Power and Mechanical Engineering, North China Electric Power University, Baoding 071000, China.
  • Xiaolong Fan
  • Wei Duan
    School of Medicine, Deakin University, Victoria, Australia.
  • Ying Yue
    Department of Anesthesiology, Zhongshan hospital, Fudan University, Shanghai, China.
  • Jun Xie
    Information Technology Center, West China Hospital of Sichuan University, Chengdu, China.
  • Yunpeng Liu
    e Faculty of Electronics & Computer , Zhejiang Wanli University , Ningbo , 315000 , China.

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