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Characterisation of Physiological Tremor using Multivariate Empirical Mode Decomposition and Hilbert Transform.

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    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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    Summary

    Fatigue-induced physiological tremor (FIPT) is characterized using multivariate empirical mode decomposition (MEMD) and Hilbert spectral analysis. An Energy Ratio (ER) effectively indicates increasing fatigue during micromanipulation tasks.

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    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Human Factors Engineering

    Background:

    • Fatigue-induced physiological tremor (FIPT) negatively impacts precision tasks like micromanipulation.
    • Traditional methods (sEMG, MMG with Fourier transforms) assume signal linearity and stationarity, limiting their analysis of tremor.
    • Developing robust methods to characterize FIPT is crucial for improving performance in high-precision activities.

    Purpose of the Study:

    • To characterize fatigue-induced physiological tremor (FIPT) using advanced signal processing techniques.
    • To introduce a novel indicator, Energy Ratio (ER), for quantifying FIPT.
    • To assess the efficacy of MEMD and Hilbert spectral analysis for tremor characterization.

    Main Methods:

    • Utilized multivariate empirical mode decomposition (MEMD) to extract relevant frequency bands from physiological tremor signals.
    • Applied Hilbert spectral analysis to estimate signal energy within the extracted bands.
    • Proposed and calculated the Energy Ratio (ER) as a parameter to quantify FIPT.

    Main Results:

    • The Energy Ratio (ER) demonstrated a significant increasing trend with task epoch, indicating rising fatigue levels.
    • Linear regression showed high correlation coefficients (R²≈0.7 for sEMG, R²≈0.9 for accelerometer data) for ER predicting fatigue.
    • MEMD and Hilbert spectral analysis proved effective for analyzing non-linear, non-stationary tremor signals.

    Conclusions:

    • The proposed Energy Ratio (ER) is an effective and versatile indicator for quantifying fatigue-induced physiological tremor.
    • This characterization method can be integrated into control strategies to mitigate tremor effects in prolonged micromanipulation, such as surgery.
    • The findings support the use of MEMD and Hilbert spectral analysis for analyzing physiological tremor and have implications for surgical training and performance enhancement.