Intelligent Breathing Electronic Skin Inspired by Nepenthes for Active Sweat Management, Multimodal Sensing and High-Fidelity Electromyographic Teleoperation Using Machine Learning
Abstract Electronic skin (e-skin), a stretchable, conformable, and multimodal sensing platform, is rapidly advancing in healthcare, robotics, and human–machine interaction (HMI). However, prolonged wear and sweat accumulation at the e-skin-skin interface can introduce signal artifacts, cause discomfort, and eventually lead to interfacial failure. Inspired by the unidirectional liquid transport of the Nepenthes peristome, we constructed an intelligent breathing e-skin (SPTL) featuring a Janus bilayer structure that creates a “liquid diode” effect for active sweat transport, achieving a remarkable cumulative one-way transport index of 956.36 while maintaining a dry interface even under profuse perspiration. This device exhibits a high tensile strain of 627%, a breathability of 20.02 mm s −1 , and a pressure sensitivity of 7.39 kPa −1 . Furthermore, the SPTL demonstrates versatile multimodal sensing capabilities, including real-time Morse code and non-contact capacitive sensing, while sustaining stable performance over 10,000 pressing cycles (capacitance decay < 3%). As a bio-integrated electrode, SPTL enables high-fidelity acquisition of electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG) signals, significantly outperforming commercial Ag/AgCl electrodes. Integrated with machine learning algorithms and EMG signals captured by the SPTL, it facilitates precise teleoperation of a quadruped robot and handwritten letter recognition with over 95% accuracy. This bionic strategy provides a versatile solution for intelligent, breathable, and multimodal bio-integrated interfaces.
Authors
- Chengtan Liu
- G Y Zhang
- W C Chen
- Ran Cai (ORCID: https://orcid.org/0009-0009-1821-7498)
- Yichen Li (ORCID: https://orcid.org/0009-0009-8370-644X)
- Kai Zheng (ORCID: https://orcid.org/0000-0003-4983-3604)
- Bihai Yang (ORCID: https://orcid.org/0009-0009-5980-4330)
- SEONHO SHIN
- Bin Hu
Institutions
- Beijing Institute of Technology (CN)
Publication Details
- Journal
- Nano-Micro Letters
- Published
- 2026-06-12
- DOI
- https://doi.org/10.1007/s40820-026-02252-2
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00