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A new algorithm for estimating the ν-index using sinusoidal basis functions.

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    A new algorithm improves the estimation of spatial heterogeneity of ventricular repolarization (SHVR) using the ν-index from surface ECGs. This method enhances accuracy by incorporating higher-order terms and reducing computational complexity.

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    Area of Science:

    • Cardiovascular Electrophysiology
    • Biomedical Signal Processing

    Background:

    • Spatial heterogeneity of ventricular repolarization (SHVR) is a crucial metric for assessing cardiac electrical activity.
    • The ν-index, derived from surface ECG, offers a non-invasive method to quantify SHVR.
    • Previous methods for ν-index estimation faced limitations in accuracy and computational efficiency.

    Purpose of the Study:

    • To introduce a novel algorithm for more accurate estimation of the ν-index.
    • To enhance the assessment of SHVR from surface electrocardiograms (ECGs).
    • To overcome limitations of previous estimation techniques, including noise sensitivity and computational demands.

    Main Methods:

    • Development of a new analytical model for the derivative of transmembrane potentials during repolarization using trigonometric functions.
    • Implementation of an iterative linear matrix factorization method for estimating lead factors and the ν-index.
    • Simulation of synthetic SHVR using the ECGSIM model, generating 240 8-lead ECG recordings.

    Main Results:

    • The new algorithm allows for the inclusion of higher-order terms, improving ν-index estimation accuracy.
    • The method eliminates the need for nonlinear iterative optimization required by prior techniques.
    • Improved accuracy was observed with an increased number of lead factors (RMSE decreased from 0.295±0.037 to 0.280±0.038).

    Conclusions:

    • The proposed algorithm provides a more accurate and computationally efficient method for estimating the ν-index.
    • This advancement facilitates better non-invasive assessment of spatial heterogeneity of ventricular repolarization.
    • The findings support the utility of incorporating higher-order lead factors for enhanced SHVR analysis.