Skin preparation-free, stretchable microneedle adhesive patches for reliable electrophysiological sensing and exoskeleton robot control.

Journal: Science advances
PMID: 38232166

Abstract

High-fidelity and comfortable recording of electrophysiological (EP) signals with on-the-fly setup is essential for health care and human-machine interfaces (HMIs). Microneedle electrodes allow direct access to the epidermis and eliminate time-consuming skin preparation. However, existing microneedle electrodes lack elasticity and reliability required for robust skin interfacing, thereby making long-term, high-quality EP sensing challenging during body movement. Here, we introduce a stretchable microneedle adhesive patch (SNAP) providing excellent skin penetrability and a robust electromechanical skin interface for prolonged and reliable EP monitoring under varying skin conditions. Results demonstrate that the SNAP can substantially reduce skin contact impedance under skin contamination and enhance wearing comfort during motion, outperforming gel and flexible microneedle electrodes. Our wireless SNAP demonstration for exoskeleton robot control shows its potential for highly reliable HMIs, even under time-dynamic skin conditions. We envision that the SNAP will open new opportunities for wearable EP sensing and its real-world applications in HMIs.

Authors

  • Heesoo Kim
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Juhyun Lee
    Department of Bioengineering, University of Texas, Arlington, TX, USA.
  • Ung Heo
    Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Dhileep Kumar Jayashankar
    Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO 80309, USA.
  • Karen-Christian Agno
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Yeji Kim
    Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering, KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Choong Yeon Kim
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Youngjun Oh
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Sang-Hyuk Byun
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Bohyung Choi
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Hwayeong Jeong
    Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
  • Woon-Hong Yeo
    George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Zhuo Li
    Biostatistics Unit, Mayo Clinic, Jacksonville, FL, United States.
  • Seongjun Park
    Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
  • Jianliang Xiao
    Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 310000, China.
  • Jung Kim
    Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
  • Jae-Woong Jeong
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.

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