F. Plesinger, I. Viscor, V. Vondra, J. Halámek, Zuzana Koscova, P. Leinveber, K. Čurila, P. Jurák
{"title":"VDI Vision - Analysis of Ventricular Electrical Dyssynchrony in Real-Time","authors":"F. Plesinger, I. Viscor, V. Vondra, J. Halámek, Zuzana Koscova, P. Leinveber, K. Čurila, P. Jurák","doi":"10.23919/cinc53138.2021.9662916","DOIUrl":null,"url":null,"abstract":"Background: Ventricular electrical dyssynchrony can be examined using ultra-high-frequency (UHF-ECG) analysis. Furthermore, UHF-ECG analysis would allow direct optimization of pacing therapy. Here we introduce VDI vision (Ventricular Dyssynchrony Imaging), a desktop application for the real-time processing of UHF-ECG recordings. Method: Incoming ECG data (5kHz, 26 bits, 24 channels) are processed as follows: QRS detection, pacemaker stimuli elimination, QRS clustering, amplitude envelopes in nine frequency bands, and final combination into the Ventricular Depolarization (VD) map. The VD map is updated whenever a new QRS is detected. Results: We developed the VDI vision using the. NET platform. Until the end of March 2021, the VDI monitor was used to analyze 773 and 4,849 recordings at ICRC-FNUSA hospital (Brno, Czechia) and FNKV hospital (Prague, Czechia), respectively. The median length for ICRC-FNUSA recordings was 124 (IQR 121–139) seconds. The median length for recordings at FNKV hospital was 157 seconds (IQR 127–200). Conclusion: The VDI vision delivers information about electrical ventricular dyssynchrony in real-time. The instant analysis allows using the software during implant procedures for optimizing electrode placement and pacing. The presented real-time solution also significantly minimized measurement duration.","PeriodicalId":126746,"journal":{"name":"2021 Computing in Cardiology (CinC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Computing in Cardiology (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/cinc53138.2021.9662916","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Background: Ventricular electrical dyssynchrony can be examined using ultra-high-frequency (UHF-ECG) analysis. Furthermore, UHF-ECG analysis would allow direct optimization of pacing therapy. Here we introduce VDI vision (Ventricular Dyssynchrony Imaging), a desktop application for the real-time processing of UHF-ECG recordings. Method: Incoming ECG data (5kHz, 26 bits, 24 channels) are processed as follows: QRS detection, pacemaker stimuli elimination, QRS clustering, amplitude envelopes in nine frequency bands, and final combination into the Ventricular Depolarization (VD) map. The VD map is updated whenever a new QRS is detected. Results: We developed the VDI vision using the. NET platform. Until the end of March 2021, the VDI monitor was used to analyze 773 and 4,849 recordings at ICRC-FNUSA hospital (Brno, Czechia) and FNKV hospital (Prague, Czechia), respectively. The median length for ICRC-FNUSA recordings was 124 (IQR 121–139) seconds. The median length for recordings at FNKV hospital was 157 seconds (IQR 127–200). Conclusion: The VDI vision delivers information about electrical ventricular dyssynchrony in real-time. The instant analysis allows using the software during implant procedures for optimizing electrode placement and pacing. The presented real-time solution also significantly minimized measurement duration.