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A Novel Wavelet Transform-Homogeneity Model for Sudden Cardiac Death Prediction Using ECG Signals

  • Image & Signal Processing
  • Published:
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Abstract

Sudden cardiac death (SCD) is one of the main causes of death among people. A new methodology is presented for predicting the SCD based on ECG signals employing the wavelet packet transform (WPT), a signal processing technique, homogeneity index (HI), a nonlinear measurement for time series signals, and the Enhanced Probabilistic Neural Network classification algorithm. The effectiveness and usefulness of the proposed method is evaluated using a database of measured ECG data acquired from 20 SCD and 18 normal patients. The proposed methodology presents the following significant advantages: (1) compared with previous works, the proposed methodology achieves a higher accuracy using a single nonlinear feature, HI, thus requiring low computational resource for predicting an SCD onset in real-time, unlike other methodologies proposed in the literature where a large number of nonlinear features are used to predict an SCD event; (2) it is capable of predicting the risk of developing an SCD event up to 20 min prior to the onset with a high accuracy of 95.8%, superseding the prior 12 min prediction time reported recently, and (3) it uses the ECG signal directly without the need for transforming the signal to a heart rate variability signal, thus saving time in the processing.

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Authors and Affiliations

  1. Faculty of Engineering, Departments Biomedical and Electromechanical, ENAP-RG, Autonomous University of Queretaro (UAQ), Campus San Juan del Río, Río Moctezuma 249, Col. San Cayetano, C. P, 76807, San Juan del Río, Qro., Mexico

    Juan P. Amezquita-Sanchez, Martin Valtierra-Rodriguez & Carlos A. Perez-Ramirez

  2. Departments Biomedical Informatics, Neuroscience, and Neurology, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH, 43210, USA

    Hojjat Adeli

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  1. Juan P. Amezquita-Sanchez
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This work was partially found by the Programa para el Desarrollo Profesional Docente, para el Tipo Superior (PRODEP), México, with number UAQ-PTC-335. Authors declare that they have no conflict of interest. Authors did not collect data from humans or animals. Data used in this research are from publicly-available sources.

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Amezquita-Sanchez, J.P., Valtierra-Rodriguez, M., Adeli, H. et al. A Novel Wavelet Transform-Homogeneity Model for Sudden Cardiac Death Prediction Using ECG Signals. J Med Syst 42, 176 (2018). https://doi.org/10.1007/s10916-018-1031-5

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