Multivariate classification of Brugada syndrome patients based on autonomic response to exercise testing

PloS One
Mireia CalvoAlfredo I Hernández

Abstract

Ventricular arrhythmias in Brugada syndrome (BS) typically occur at rest and especially during sleep, suggesting that changes in the autonomic modulation may play an important role in arrhythmogenesis. The autonomic response to exercise and subsequent recovery was evaluated on 105 patients diagnosed with BS (twenty-four were symptomatic), by means of a time-frequency heart rate variability (HRV) analysis, so as to propose a novel predictive model capable of distinguishing symptomatic and asymptomatic BS populations. During incremental exercise, symptomatic patients showed higher HFnu values, probably related to an increased parasympathetic modulation, with respect to asymptomatic subjects. In addition, those extracted HRV features best distinguishing between populations were selected using a two-step feature selection approach, so as to build a linear discriminant analysis (LDA) classifier. The final features subset included one third of the total amount of extracted autonomic markers, mostly acquired during incremental exercise and active recovery, thus evidencing the relevance of these test segments in BS patients classification. The derived predictive model showed an improved performance with respect to previous works in the...Continue Reading

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Citations

Dec 7, 2018·Artificial Intelligence in Medicine·Mireia CalvoAlfredo I Hernández
Oct 29, 2021·Medical & Biological Engineering & Computing·Daniel RomeroAlfredo Hernández

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Methods Mentioned

BETA
Feature extraction

Software Mentioned

Time
- Frequency
SPWVD
MatLab

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