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Skin-conformal electronics for intelligent gesture recognition

Nature Reviews Electrical Engineering (2025)Cite this article

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Abstract

Skin-conformal electronics that naturally adhere to the body are transforming human–machine interfaces (HMIs) by enabling intuitive, real-time gesture recognition with broad potential in immersive applications such as virtual reality, advanced robotics and remote health care. These devices bridge human intentions and machine responses but still require integrated platforms that collect advances in sensing elements, adaptive signal processing and intelligent decision-making algorithms. In this Review, we identify the component innovations and system-level strategies to define a roadmap for skin-conformal gesture recognition as a core element of next-generation HMIs. Advances in conformal device architectures are overcoming the mechanical and signal stability limitations of conventional wearables, enabling reliable operation during continuous use. Integration of sensing and processing enables adaptive, real-time interpretation of gestures aligned with user intent, while emerging computational approaches deliver efficient, low-latency performance inspired by biological learning. Collectively, these developments are shaping design principles for natural, precise and responsive HMIs.

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Fig. 1: Timeline of developments in gesture recognition electronics.
Fig. 2: Overview of gesture recognition processes.
Fig. 3: Skin-conformal gesture sensor units with distinct sensing modalities.
Fig. 4: Neuromorphic insights on gesture recognition units.
Fig. 5: Summary and outlook of skin-conformal electronics for intelligent gesture recognition.

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Acknowledgements

This research was supported by the National Research Foundation of Korea grant funded by the Ministry of Science and ICT (RS-2024-00403639, RS-2023-00213089, RS-2024-00403163, RS-2025-00520264, RS-2024-00407271 and RS-2024-00451891) and the Ministry of Education (RS-2023-00220077), and by the Technology Innovation Program funded by the Ministry of Trade, Industry and Energy (RS-2022-00154781).

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  1. These authors contributed equally: Inho Lee, Shin Hyojin, Haein Cho.

Authors and Affiliations

  1. Department of Intelligence Semiconductor Engineering, Ajou University, Suwon, Republic of Korea

    Inho Lee & Sungjun Park

  2. KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, Republic of Korea

    Shin Hyojin & Gunuk Wang

  3. Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA

    Haein Cho

  4. Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea

    Jun-Gyu Choi & Sungjun Park

  5. Department of Integrative Energy Engineering, Korea University, Seoul, Republic of Korea

    Gunuk Wang

  6. Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, Republic of Korea

    Gunuk Wang

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Contributions

I.L., S.H. and H.C. researched data for the article. G.W. and S.P. substantially contributed to the discussion of the content. I.L. and J.-G.C. wrote the manuscript. S.H., J.-G.C., G.W. and S.P reviewed and edited the manuscript before submission.

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Lee, I., Hyojin, S., Cho, H. et al. Skin-conformal electronics for intelligent gesture recognition. Nat Rev Electr Eng (2025). https://doi.org/10.1038/s44287-025-00215-0

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