Abstract An ECG-derived respiration (EDR) algorithm based on signal reconstruction and filtering is presented and applied to derive the respiratory signals from single-lead ECG. The ECG features, R-peak amplitude, S-peak amplitude, and R-peak position are used to reconstruct the signal by cubic spline interpolation. The EDR signal is obtained by applying a Kaiser filter to the reconstructed signal at last. The method is evaluated on data from the MIT-BIH polysomnographic database and validated against a “gold-standard” respiratory obtained from simultaneously recorded respiration data. Correlation coefficient (C) and magnitude-squared coherence coefficient (MSC) are used to assess the performance of the methods. The statistical difference is significant among the method presented in this study and the EDR methods based on wavelet and empirical mode decomposition (EMD), proving that the algorithm introduced in this article outperforms the others in the extraction of respiratory signals from single-lead ECGs.


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    Title :

    An ECG-Derived Respiration Method Based on Signal Reconstruction of R, S Amplitudes and Filtering


    Contributors:
    Gao, Yue (author) / Yan, Hong (author) / Xu, Zhi (author) / Zhang, Lin (author) / Xiao, Meng (author)


    Publication date :

    2017-08-22


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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