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Simulation and experimental studies of the factors influencing the frequency spectrum of cardiac extracellular
D Joly1, P Savard, F A Roberge
1Research Center, Sacré-Coeur Hospital, Institut de génie biomédical, Université de Montréal, Quebec, Canada.
Insights
Spectral analysis of electrocardiographic signals can reveal cardiac disease features. Simulation and experimental data show that factors like ischemia and infarction decrease signal bandwidth, indicating reduced high-frequency content.
Area of Science:
- Cardiovascular Physiology
- Computational Biology
- Signal Processing
Background:
- Spectral analysis of electrocardiographic (ECG) signals is explored for detecting cardiac diseases.
- Existing research lacks a strong theoretical foundation for ECG spectral analysis in disease detection.
Purpose of the Study:
- To investigate the theoretical basis of spectral analysis for ECG signals.
- To simulate and analyze electrograms from cardiac tissue to understand signal characteristics.
Main Methods:
- Utilized a bidomain volume conductor model of cardiac tissue.
- Employed Fourier analysis on simulated and experimentally recorded electrograms.
- Recorded electrograms from an isolated canine right atrial preparation.
Main Results:
- Normal electrogram bandwidth in crista terminalis was 840±200 Hz (longitudinal) and 660±370 Hz (transverse).
- Premature stimulation increased signal bandwidth and propagation velocity with coupling interval.
- Vmax was identified as the primary determinant of high-frequency signal content.
- Signal bandwidth decreased significantly beyond 1-5 mm from the source, leveling at 50-120 Hz.
- Myocardial infarction, characterized by fragmented activity and reduced propagation velocity, led to decreased ECG bandwidth.
Conclusions:
- Simulation and experimental data support the link between ECG signal bandwidth and cardiac tissue properties.
- Decreased propagation velocity, action potential upstroke, and fragmentation associated with ischemia/infarction reduce ECG bandwidth.
- Spectral analysis holds potential for non-invasively assessing cardiac health and disease states.
Abstract:
Spectral analysis of electrocardiographic signals has been proposed as a tool to detect features reflecting cardiac diseases, such as ventricular hypertrophy, myocardial infarction, and a predisposition to sustained ventricular tachycardia. The lack of a theoretical basis to address this question prompted the authors to undertake a simulation study using a bidomain volume conductor model of a strip of cardiac tissue, combined with Fourier analysis, and electrograms recorded from an isolated right atrial canine preparation. In the crista terminalis, the bandwidth of the normal electrogram was 840 +/- 200 Hz (mean +/- SD) during longitudinal propagation and 660 +/- 370 Hz during transverse propagation. During premature stimulation, signal bandwidth and propagation velocity increase with the coupling interval. In the model, a linear combination of Vmax and propagation velocity values allows simulation of the various features of premature excitation. Vmax is the major determinant of the high-frequency content of the signal. An important decrease in the high-frequency content of electrograms occurs when the recording electrode is moved away from the preparation or the simulation model; at distances larger than 1-5 mm, the bandwidth levels off to a value of 50-120 Hz. Partial blockade of axial current flow in the direction of propagation due to microscopic discontinuities and variable activation delays at these discontinuities may be the cause of fragmented activity in necrotic myocardium, which is associated with a reduced bandwidth. Thus, short- and long-term effects of ischemia followed by infarction, such as decreased propagation velocity, decreased action potential upstroke, and fragmentation, tend to decrease the electrocardiographic bandwidth.