Self-powered Posture Recognition Based on Thermoelectric Hydrogel

Yu-Hao Zhang; Guo-Shun Cui; Saeed Ahmed Khan; Lang-Hua Shi; Hao-Zhe Zhang; Kun Yang; Xuan-Sen Zhao; Hu-Lin Zhang

doi:10.1007/s10118-025-3440-5

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Self-powered Posture Recognition Based on Thermoelectric Hydrogel

RESEARCH ARTICLE | Updated：2025-12-18

- Self-powered Posture Recognition Based on Thermoelectric Hydrogel
- Chinese Journal of Polymer Science Vol. 43, Pages: 1-10(2025)
- Affiliations：
  
  a.College of Integrated Circuits, Taiyuan University of Technology, Taiyuan 030024, China
  b.Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan
  c.College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China
  d.College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024 China
- Author bio：
  
  yangkun01@tyut.edu.cn (K.Y.)
  zhanghulin@tyut.edu.cn (H.L.Z.)
- Funds：
- DOI：10.1007/s10118-025-3440-5
  CLC：
- Received：30 July 2025，
  
  Accepted：17 August 2025，
  
  Published Online：17 December 2025，
  
  Published：2025-10
- Accepted：
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Zhang, Y. H.; Cui, G. S.; Khan, S. A.; Shi, L. H.; Zhang, H. Z.; Yang, K.; Zhao, X. S.; Zhang, H. L. Self-powered posture recognition based on thermoelectric hydrogel. Chinese J. Polym. Sci. https://doi.org/10.1007/s10118-025-3440-5

Yu-Hao Zhang, Guo-Shun Cui, Saeed Ahmed Khan, et al. Self-powered Posture Recognition Based on Thermoelectric Hydrogel[J/OL]. Chinese Journal of Polymer Science, 2025, 431-10.
Zhang, Y. H.; Cui, G. S.; Khan, S. A.; Shi, L. H.; Zhang, H. Z.; Yang, K.; Zhao, X. S.; Zhang, H. L. Self-powered posture recognition based on thermoelectric hydrogel. Chinese J. Polym. Sci. https://doi.org/10.1007/s10118-025-3440-5 DOI：

Yu-Hao Zhang, Guo-Shun Cui, Saeed Ahmed Khan, et al. Self-powered Posture Recognition Based on Thermoelectric Hydrogel[J/OL]. Chinese Journal of Polymer Science, 2025, 431-10. DOI： 10.1007/s10118-025-3440-5.

摘要

Abstract

Posture recognition technology plays a crucial role in health monitoring

motion analysis

and other related fields. However

traditional recognition devices are limited by a lack of comfort

stability

and environmental adaptability

which significantly restrict their performance and range of applications. In response

this study proposes a self-powered

strain-driven

intelligent posture recognition method based on a thermoelectric hydrogel. This approach enables high-precision posture recognition through simultaneous acquisition of dynamic strain signals from multiple joints. The proposed poly(vinyl alcohol) (PVA)/starch bi-network hydrogel

synthesized in a binary H

O/glycerol solvent system

exhibited outstanding flexibility and tensile strength

allowing it to conform closely to joint movements and ensure wearing comfort. Simultaneously

the hydrogel generated stable electrical signals

via

the redox reaction of [Fe(CN)

]

3–/4-

supporting continuous monitoring and data collection. Moreover

its self-powered nature allows effective joint strain signal acquisition

even in open environments. Using a machine learning algorithm that incorporates signal processing and analysis

the proposed method achieved a posture recognition accuracy of 96.82%. This study presents a novel technological route for posture recognition in wearable devices

demonstrating its strong application potential in real-time feedback for sports rehabilitation and performance analysis of athletes.

关键词

Keywords

references

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