Electric Double Layer Based Epidermal Electronics for Healthcare and Human-Machine Interface

Yuan Gao, Hanchu Zhang, Bowen Song, Chun Zhao, Qifeng Lu*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

3 Citations (Scopus)


Epidermal electronics, an emerging interdisciplinary field, is advancing the development of flexible devices that can seamlessly integrate with the skin. These devices, especially Electric Double Layer (EDL)-based sensors, overcome the limitations of conventional electronic devices, offering high sensitivity, rapid response, and excellent stability. Especially, Electric Double Layer (EDL)-based epidermal sensors show great potential in the application of wearable electronics to detect biological signals due to their high sensitivity, fast response, and excellent stability. The advantages can be attributed to the biocompatibility of the materials, the flexibility of the devices, and the large capacitance due to the EDL effect. Furthermore, we discuss the potential of EDL epidermal electronics as wearable sensors for health monitoring and wound healing. These devices can analyze various biofluids, offering real-time feedback on parameters like pH, temperature, glucose, lactate, and oxygen levels, which aids in accurate diagnosis and effective treatment. Beyond healthcare, we explore the role of EDL epidermal electronics in human-machine interaction, particularly their application in prosthetics and pressure-sensing robots. By mimicking the flexibility and sensitivity of human skin, these devices enhance the functionality and user experience of these systems. This review summarizes the latest advancements in EDL-based epidermal electronic devices, offering a perspective for future research in this rapidly evolving field.

Original languageEnglish
Article number787
Issue number8
Publication statusPublished - Aug 2023


  • electric double layer
  • epidermal electronics
  • flexible devices
  • healthcare
  • human-machine interface
  • physiological signal monitoring


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