Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

© 2015 CCAL. Hypertrophic cardiomyopathy (HCM) is an inherited cardiac disease characterized by an unexplained thickening of the heart ventricles. It is the first cause of sudden cardiac death in young adults. No reliable biomarkers for risk assessment have been presented so far, but the electrocardiograms of HCM patients are often abnormal due to structural and electrical abnormalities. The goal of our study was to extract morphological QRS biomarkers in order to discriminate between HCM patients and control patients by analyzing fifty 12-lead Holter recordings (29 HCM - 21 control). Morphological features such as QRS width or slopes from the QRS complex directly and the coefficients of the first four Hermite transform basis were extracted. Classification was then performed using those features in an L1 regularized logistic regression algorithm. Classification between control and HCM patients reached 95.7% of accuracy (sensitivity of 94.96% for HCM and specificity of 96.90%) using only two main features: the percentage of negative regions of the QRS complex with respect to the isoelectric level and the 3rd coefficient of its Hermite fitting showing interesting connections to cardiac electrophysiology.

Original publication

DOI

10.1109/CIC.2015.7408573

Type

Conference paper

Publication Date

16/02/2015

Volume

42

Pages

9 - 12