Flexible multichannel muscle impedance sensors for collaborative human-machine interfaces.

Journal: Science advances
Published Date:

Abstract

The demand for advanced human-machine interfaces (HMIs) highlights the need for accurate measurement of muscle contraction states. Traditional methods, such as electromyography, cannot measure passive muscle contraction states, while optical and ultrasonic techniques suffer from motion artifacts due to their rigid transducers. To overcome these limitations, we developed a flexible multichannel electrical impedance sensor (FMEIS) for noninvasive detection of skeletal muscle contractions. By applying an imperceptible current, the FMEIS can target multiple deep muscles by capturing electric-field ripples generated by their contractions. With an ultrathin profile (~220 micrometers), a low elastic modulus (212.8 kilopascals) closely matching human skin, and engineered adhesive sensor surfaces, the FMEIS conforms nicely to human skin with minimized motion artifacts. The FMEIS achieved high accuracy in both hand gesture recognition and muscle force prediction using machine learning models. With demonstrated performance across multiple HMI applications, including human-robot collaboration, exoskeleton control, and virtual surgery, FMEIS shows great potential for future real-time collaborative HMI systems.

Authors

  • Junwei Li
    Department of Medical Oncology, Phase I Clinical Trial Centre, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangzhou.
  • Kunlin Wu
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore, Singapore.
  • Jingcheng Xiao
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore, Singapore.
  • Tianyu Chen
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore.
  • Xudong Yang
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore.
  • Jie Pan
  • Yu Chen
    State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
  • Yifan Wang
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.