Morphologically constrained signal subspace characterization of electrograms during ventricular fibrillation. (September 2017)

• Record Type: Journal Article
• Authors: Balasundaram, Krishnanand; Masse, Stephane; Farid, Talha; Nair, Krishnakumar; Asta, John; Cusimano, Robert J.; Vigmond, Edward; Nanthakumar, Kumaraswamy; Umapathy, Karthikeyan
• Is Part Of: Biomedical signal processing and control. Volume 38(2017)
• Page Start: 379
• Page End: 387
• Publication Date: 2017-09
• Subjects: Ventricular fibrillation -- Adaptive signal decomposition -- Matching Pursuits -- Criterion function -- Rotor; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.06.002
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: Automate extraction of electrogram signal morphologies in the vicinityof rotors. Matching Pursuits (MP) signal decomposition using a modified criterion function. Segregation of electrogram signal structures to determine vicinity to a rotor. Proposed MP based method achieved a sensitivity of 84.62% and specificity of 70.77%. Abstract: Ventricular fibrillation (VF) is a lethal cardiac arrhythmia traditionally believed to be chaotic in nature. However, recent research studies have shown that certain events of interest during VF may exhibit local (or regional) organization. These time-varying and spatially migrating organized activities manifest themselves into different signal morphologies within electrograms acquired during VF. Performing targeted (or constrained) signal decomposition of electrograms to extract such signal morphologies associated with events of clinical interest will be of significant value. We present one such targeted adaptive signal decomposition of intra-cardiac electrograms during VF, to automatically extract morphologies previously observed in relation to the vicinity of rotor phenomenon (i.e. an event of interest during VF). Using a Gabor dictionary and Matching Pursuits (MP), the proposed method successfully performed targeted signal decomposition in highlighting signal structures that could be used to determine the ventricular electrogram's vicinity to a rotor in the epicardium. A comparative analysis using the MP with a proposed choice function ( P < 0.001) against the standard choice function ( P < 0.5688) performed better in segregating the electrogram data (130 electrograms from 7 isolated human hearts) based on the signal structures.