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A soft magnetoelastic sensor to decode levels of fatigue

Nature Electronics volume 8, pages 709–720 (2025)Cite this article

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Abstract

Fatigue is a complex condition characterized by a decline in a person’s mental or physical performance. Methods to gauge fatigue include self-reported questionnaires, electroencephalography and camera-based technologies. However, these methods are typically restricted to laboratory settings, which limits their wider accessibility. Here we report a soft on-eyelid magnetoelastic sensor that can capture eye-blink parameters in real time and quantitatively decode fatigue levels. The sensor, which works in a self-powered manner, comprises a magnetomechanical coupling layer formed from a silicone rubber matrix embedded with micromagnets and a conductive gold coil patterned onto a thin thermoplastic elastomer layer. This design allows the conversion of eye movements into high-fidelity electrical signals. The sensor exhibits a Young’s modulus of 200 kPa, a stretchability of up to 530% and a pressure sensitivity of 0.2 µA kPa−1. Its thin membrane structure adheres conformally to human upper eyelid tissue and maintains intimate contact during diverse eye movements. When combined with a one-dimensional convolutional neural network and data-processing techniques, the sensor can recognize subtle eye movements and categorize fatigue levels with an accuracy of 96.4% based on six eye-blink parameters.

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Fig. 1: On-eyelid soft magnetoelastic sensor-based wearable fatigue measurement system.
Fig. 2: Mechanical and electrical characterization of on-eyelid magnetoelastic sensors.
Fig. 3: Perception capability of the on-eyelid magnetoelastic sensor.
Fig. 4: Wearable on-eyelid magnetoelastic sensor for quantitative fatigue assessment.

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Data availability

Source data are available via figshare at https://doi.org/10.6084/m9.figshare.25272598.v2 (ref. 47). Other data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

No custom code or mathematical algorithm that was central to the conclusions was used in this study.

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Acknowledgements

J.C. acknowledges the Vernroy Makoto Watanabe Excellence in Research Award at the UCLA Samueli School of Engineering, the Office of Naval Research Young Investigator Award (Award ID N00014-24-1-2065), a National Institutes of Health grant (Award ID R01 CA287326), a National Science Foundation grant (Award No. 2425858), an American Heart Association Innovative Project Award (Award ID 23IPA1054908), an American Heart Association Transformational Project Award (Award ID 23TPA1141360), the American Heart Association’s Second Century Early Faculty Independence Award (Award ID 23SCEFIA1157587) and the NIH National Center for Advancing Translational Science UCLA CTSI (Grant No. KL2TR001882).

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Author notes

  1. These authors contributed equally: Jing Xu, Chrystal Duan.

Authors and Affiliations

  1. Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA

    Jing Xu, Chrystal Duan, Xiao Wan, Ziyuan Che, Xun Zhao, Yihao Zhou, Yang Song, Junyi Yin, Trinny Tat, Song Li & Jun Chen

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Contributions

J.C. conceived the idea and supervised the whole project. J.X. and C.D. designed the experiment and fabricated the device. X.W. and Z.C. assisted in the testing the performance of the device. J.X., C.D. and T.T. wrote the paper. X.Z., Y.Z. and J.Y. assisted in designing the figures. S.L. and Y.S. provided support on the cell viability assay. All authors have read the paper, agree with its contents and approved submission.

Corresponding author

Correspondence to Jun Chen.

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Competing interests

J.C. and J.X. have filed a patent from the University of California, Los Angeles. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Electronics thanks Guosong Hong, Shiyuan Wei and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–43, Notes 1–5 and Tables 1–5.

Reporting Summary

Supplementary Video 1

Actual appearance of the 3UM on-eyelid sensor.

Supplementary Video 2

3UM on-eyelid sensor for fatigue detection and management.

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Xu, J., Duan, C., Wan, X. et al. A soft magnetoelastic sensor to decode levels of fatigue. Nat Electron 8, 709–720 (2025). https://doi.org/10.1038/s41928-025-01418-x

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