Muscle Fiber-Inspired High-Performance Strain Sensors for Motion Recognition and Control

  • Bangbang Nie
  • , Yihong Zhu
  • , Zongxu Luo
  • , Jingjiang Qiu
  • , Mingfu Zhu
  • , Ming Zhai
  • , Guobi Chai
  • , Xiangming Li
  • , Jinyou Shao
  • , Ronghan Wei

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The rapid development of wearable technology, flexible electronics, and human-machine interaction has brought about revolutionary changes to the fields of motion analysis and physiological monitoring. Sensors for detecting human motion and physiological signals have become a hot topic of current research. Inspired by the muscle fiber structure, this paper proposed a highly stable strain sensor that was composed of stretchable Spandex fibers (SPF), multiwalled carbon nanotubes (MWCNTs), and silicone rubber (Ecoflex). This sensor adopted an immersion coating process in which MWCNTs were conformally deposited on SPF, and Ecoflex was filled into the fiber interstices, completing the encapsulation and filling of the SPF to construct a stable three-dimensional conductive network. Thanks to the filling of Ecoflex, contact between conductive fibers during the stretching process was avoided, resulting in a significant change in the resistance. The sensitivity of the sensor reached 54.84, which is 10 times higher than before the Ecoflex filling with a stretchable strain range of up to 70%. The encapsulation of Ecoflex also prevented the detachment of MWCNTs on the fibers during stretching, improving the mechanical stability. The sensor can be easily attached to the surface of human skin to rapidly monitor various human motion signals. Furthermore, the sensor was related to the manipulator through wireless Bluetooth to realize the intelligent control of the manipulator. This work not only provided a more precise data monitoring method for medical and motion analysis fields but also offered an innovative solution for manipulator control.

Original languageEnglish
Pages (from-to)2053-2064
Number of pages12
JournalLangmuir
Volume41
Issue number3
DOIs
StatePublished - 28 Jan 2025

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