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- Title
A Novel Wavelet Transform-Homogeneity Model for Sudden Cardiac Death Prediction Using ECG Signals.
- Authors
Amezquita-Sanchez, Juan P.; Valtierra-Rodriguez, Martin; Adeli, Hojjat; Perez-Ramirez, Carlos A.
- 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.
- Subjects
MASSACHUSETTS; CARDIAC arrest; ALGORITHMS; ECHOCARDIOGRAPHY; ARTIFICIAL neural networks; SIGNAL processing; DIAGNOSIS
- Publication
Journal of Medical Systems, 2018, Vol 42, Issue 10, p1
- ISSN
0148-5598
- Publication type
Article
- DOI
10.1007/s10916-018-1031-5