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Order Statistics Concordance Coefficient With Applications to Multichannel Biosignal Analysis.

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    We introduce the order statistics concordance coefficient (OSCOC) to measure multichannel biosignal association. OSCOC shows strong performance across various models and excels in nonlinear cases and arrhythmia analysis.

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    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Statistical Analysis

    Background:

    • Quantifying associations in multichannel biosignals is crucial for accurate analysis.
    • Existing concordance coefficients have limitations in complex signal scenarios.

    Purpose of the Study:

    • To introduce a novel concordance coefficient, the order statistics concordance coefficient (OSCOC).
    • To evaluate OSCOC's performance against established methods like APPMCC, KCC, and AKT.
    • To demonstrate OSCOC's utility in analyzing real-world multichannel cardiac signals for arrhythmia detection.

    Main Methods:

    • Developed the order statistics concordance coefficient (OSCOC).
    • Compared OSCOC with average Pearson's product moment correlation coefficient (APPMCC), Kendall's concordance coefficients (KCC), and average Kendall's tau (AKT).
    • Evaluated performance under multivariate normal, linear, and nonlinear models.
    • Applied OSCOC to multichannel cardiac signals for atrial arrhythmia analysis.

    Main Results:

    • OSCOC performs comparably to APPMCC and outperforms KCC and AKT under multivariate normal and linear models.
    • OSCOC demonstrates superior performance over KCC and AKT in nonlinear scenarios.
    • OSCOC achieved the best performance in the atrial arrhythmia analysis case study.

    Conclusions:

    • OSCOC is a robust and effective measure for quantifying associations in multichannel biosignals.
    • OSCOC offers advantages over existing methods, particularly in nonlinear conditions and complex biological signal analysis.
    • The proposed OSCOC provides a valuable tool for biomedical signal processing and diagnostics.