Abstract
Electronic artificial skin (E-skin) replicates human tactile sensations with exceptional sensitivity and accuracy, enabling the detection of physical properties, including the shape, material, and texture of objects. Current technologies effectively detect slippage on dry surfaces but not on oil- or water-coated wet surfaces. This paper presents a wearable slip sensor featuring a micropatterned structure inspired by human fingerprints, capable of detecting slippage under all surface wetness conditions. The proposed sensor incorporates a randomly patterned fingerprint design, laser-etched onto the topmost layer of a multilayer film. It effectively detects surface slippage, even on oil film-coated low-friction surfaces. Additionally, the sensor captures intricate geometric features of microtextures, including microvibrations and ultrafast signal changes. Its applicability in soft robotic hands is demonstrated by its high-speed detection of the sliding motion of various objects. The findings will aid in advancing digital-on-demand technologies by enabling the precise reconstruction of digital tactile data within cyber-physical systems.
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Acknowledgements
We thank the staff of the Research Center for Organic Electronics (ROEL) and Dr. Shizuo Tokito at Yamagata University. This study was partially supported by JSPS KAKENHI Grant Number JP25K01190, the Tohoku Initiative for Fostering Global Researchers for Interdisciplinary Sciences (TI-FRIS) of MEXT’s Strategic Professional Development Program for Young Researchers, Program for Forming Japan’s Peak Research Universities (J-PEAKS), and the JGC-S Scholarship Foundation. The authors would like to thank Editage (www.editage.jp) for the English language review.
Funding
This work was partially supported by JSPS KAKENHI Grant Number JP25K01190, the Tohoku Initiative for Fostering Global Researchers for Interdisciplinary Sciences (TI-FRIS) of MEXT’s Strategic Professional Development Program for Young Researchers, and the JGC-S Scholarship Foundation.
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T.A: Original draft writing, Software, Methodology, Investigation, K.O., H.M.: Software, Methodology, Formal analysis, S.K., J.Y., R.S., Y.M., Y.T., Y.T.: Methodology, Investigation, F.D.D.S. T.H. A.M.: Material supply, Methodology, T.S.: Review and editing of draft, Original draft writing, Supervision, Software, Investigation, Formal analysis, Conceptualization.
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This study was conducted as part of a formal collaborative research project among the authors. As part of this collaboration, three co-authors (Dr. F. D. D. Fabrice, Dr. T. Huang, and Dr. A. Miyabo) provided research funding to the corresponding author (Dr. T. Sekine) under an established joint research agreement. The authors declare this financial relationship as a competing interest, in accordance with Nature Research policy. The funding supported the execution of the research but did not influence the study design, data analysis, interpretation, or the decision to publish.
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Adachi, T., Ozawa, K., Kamanoi, S. et al. AI-integrated bionic fingertip E-Skin for precision slippage detection in wet environments. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41096-z
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DOI: https://doi.org/10.1038/s41598-026-41096-z
