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The Effects of 40 Hz Low-Pass Filtering on the Magnitude of the Spatial Ventricular Gradient

  • The magnitude of the spatial ventricular gradient (MSVG) is an attractive parameter in electrocardiogram (ECG)monitoring applications. The MSVG is most commonlyobtained from150 Hz low-pass filtered resting ECGs. However, monitoring applications typically utilize 40 Hz low-pass filtered ECG data. The extend to which the value of the MSVG is affected by the utilization of 40 Hz low-pass monitoring ECG filters over the commonly used 150 Hz low-pass resting ECG filters has not previously been reported. The aim of this research was to quantify the differences between MSVG values computed using 40 Hz low-pass filtered ECG data (MSVG40) and 150 Hz low-pass filtered ECG data (MSVG150). The differences between the MSVG40 and the MSVG150 were quantified as systematic error (mean difference) and random error (span of Bland-Altman 95% limits of agreement) using a study population of 726 subjects. The systematic error was found to be 0.013 mV ms [95% confidence interval: 0.008 mV ms to 0.018 mV ms]. The random error was quantified as 0.282The magnitude of the spatial ventricular gradient (MSVG) is an attractive parameter in electrocardiogram (ECG)monitoring applications. The MSVG is most commonlyobtained from150 Hz low-pass filtered resting ECGs. However, monitoring applications typically utilize 40 Hz low-pass filtered ECG data. The extend to which the value of the MSVG is affected by the utilization of 40 Hz low-pass monitoring ECG filters over the commonly used 150 Hz low-pass resting ECG filters has not previously been reported. The aim of this research was to quantify the differences between MSVG values computed using 40 Hz low-pass filtered ECG data (MSVG40) and 150 Hz low-pass filtered ECG data (MSVG150). The differences between the MSVG40 and the MSVG150 were quantified as systematic error (mean difference) and random error (span of Bland-Altman 95% limits of agreement) using a study population of 726 subjects. The systematic error was found to be 0.013 mV ms [95% confidence interval: 0.008 mV ms to 0.018 mV ms]. The random error was quantified as 0.282 mV ms [95% confidence interval: 0.266 mV ms to 0.298 mV ms]. Our findings suggest that it is possible to record accurate MSVG values using 40 Hz low-pass filtered ECG data.show moreshow less

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Metadaten
Author:Daniel GüldenringORCiD, Dewar D. FinlayORCiD, Alan KennedyORCiD, Raymond R. BondORCiD, Michael R. Jennings, James D. McLaughlinORCiD
DOI:https://doi.org/10.23919/CinC49843.2019.9005814
Identifier:9781728159423 OPAC HS OPAC extern
Identifier:2325-887X OPAC HS OPAC extern
Parent Title (English):Computers in Cardiology (CinC)
Publisher:IEEE
Place of publication:Piscataway
Editor:Christine Pickett
Document Type:conference proceeding (article)
Conference:2019 Computing in Cardiology (CinC), 8 - 11 Sept. 2019, Singapore
Language:English
Date of Publication (online):2019/09/10
Year of first Publication:2019
Volume:45
Number of pages:4 Seiten
Institutes:Fakultät Elektrotechnik
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften
Publication Lists:Güldenring, Daniel
Publication reviewed:begutachtet
Release Date:2021/02/16
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