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Related Experiment Video

Updated: Jun 13, 2026

Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
06:00

Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test

Published on: July 27, 2015

Multi-Day Muscle Fatigue Estimation During Dynamic Exercise Using sEMG E-Tattoo and BH-IEEMD Processing.

Heeyong Huh, Xiangxing Yang, Samuel Bello

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |June 11, 2026
    PubMed
    Summary
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    A new e-tattoo sensor and signal processing method improve muscle fatigue assessment during exercise. This technology offers stable, long-term monitoring for rehabilitation and wearable devices.

    Area of Science:

    • Biomedical Engineering
    • Wearable Technology
    • Signal Processing

    Background:

    • Dynamic surface electromyography (sEMG) for muscle fatigue assessment faces challenges like sensor instability and motion artifacts.
    • Existing methods struggle with signal nonstationarity during dynamic activities, limiting reliability.

    Purpose of the Study:

    • To develop a robust framework for reliable multi-day muscle fatigue monitoring using a novel approach.
    • To integrate a skin-conformal e-tattoo sensor with an advanced signal processing pipeline to overcome current limitations.

    Main Methods:

    • Developed a noninvasive, skin-conformal e-tattoo sensor for continuous sEMG acquisition over five days.
    • Implemented a bandpass-Hampel-iterative ensemble empirical mode decomposition (BH-IEEMD) pipeline to suppress noise and artifacts.

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    Published on: July 22, 2022

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    Last Updated: Jun 13, 2026

    Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
    06:00

    Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test

    Published on: July 27, 2015

    Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment
    10:03

    Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment

    Published on: July 22, 2022

  • Benchmarked e-tattoo performance against conventional gel electrodes during dynamic exercises with 20 participants.

    • Main Results:

    • The e-tattoo demonstrated stable contact impedance and comparable noise floor to gel electrodes, with superior signal-to-noise and signal-to-motion ratios.
    • BH-IEEMD effectively reduced motion artifacts and improved signal stationarity, leading to tighter feature distributions and better fatigue classification.
    • Leave-one-subject-out validation showed robust, model-agnostic performance, with the best model achieving R² = 0.70 and best-subject performance reaching R² = 0.93.

    Conclusions:

    • The combination of skin-conformable e-tattoo sensing and artifact-aware BH-IEEMD processing provides a reliable method for long-term muscle fatigue monitoring.
    • This framework enables practical applications in rehabilitation, fitness training, and control of wearable exoskeletons.