Analysis of the High-Frequency Content in Human QRS Complexes by the Continuous Wavelet Transform: An Automatized Analysis for the Prediction of Sudden Cardiac Death

Fragmentation and delayed potentials in the QRS signal of patients have been postulated as risk markers for Sudden Cardiac Death (SCD). The analysis of the high-frequency spectral content may be useful for quantification. Forty-two consecutive patients with prior history of SCD or malignant arrhythm...

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Published inSensors (Basel, Switzerland) Vol. 18; no. 2; p. 560
Main Authors García Iglesias, Daniel, Roqueñi Gutiérrez, Nieves, De Cos, Francisco Javier, Calvo, David
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 12.02.2018
MDPI
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Summary:Fragmentation and delayed potentials in the QRS signal of patients have been postulated as risk markers for Sudden Cardiac Death (SCD). The analysis of the high-frequency spectral content may be useful for quantification. Forty-two consecutive patients with prior history of SCD or malignant arrhythmias (patients) where compared with 120 healthy individuals (controls). The QRS complexes were extracted with a modified Pan-Tompkins algorithm and processed with the Continuous Wavelet Transform to analyze the high-frequency content (85-130 Hz). Overall, the power of the high-frequency content was higher in patients compared with controls (170.9 vs. 47.3 10³nV²Hz ; = 0.007), with a prolonged time to reach the maximal power (68.9 vs. 64.8 ms; = 0.002). An analysis of the signal intensity (instantaneous average of cumulative power), revealed a distinct function between patients and controls. The total intensity was higher in patients compared with controls (137.1 vs. 39 10³nV²Hz s ; = 0.001) and the time to reach the maximal intensity was also prolonged (88.7 vs. 82.1 ms; < 0.001). The high-frequency content of the QRS complexes was distinct between patients at risk of SCD and healthy controls. The wavelet transform is an efficient tool for spectral analysis of the QRS complexes that may contribute to stratification of risk.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s18020560