title: Tracking repolarization dynamics in real-life data.
abstract: Ambulatory (Holter) electrocardiographic recordings provide the tools for tracking temporal instabilities of repolarization during various daily activities. However, analysis of low-amplitude repolarization changes in this setting is challenging due to the presence of multiple artifacts, variable activity levels, and other uncontrolled factors. Here we compare performance of different methods for continuous analysis of repolarization dynamics using simulated signals and real-life Holter recordings. Selection of relatively stable segments with a low baseline drift and accurate correction of baseline wander constitute the first step in repolarization analysis. We describe application of adaptive filtering, which yields more accurate results than non-adaptive techniques. Because small (microvolt-level) residual baseline drifts can be a source of error in tracking repolarization changes, stability of isoelectrical segment has to be controlled. To compare robustness of spectral and time-domain techniques for tracking temporal repolarization instabilities (T-wave alternans, TWA), we used simulated signals with changing heart rate, variable levels of TWA, noise, phase shifts, spurious artifacts, and period-four oscillations. In addition, we compared performances of the inter-beat and intra-beat averaging techniques for tracking dynamics of T-wave alternans. Using the simulated signals and real-life Holter data, we showed that analysis of information both in time and frequency domains combined with control of baseline drifts (surrogate analysis) gives a more reliable estimate of the low-amplitude repolarization dynamics than each of these techniques alone. To summarize, dynamic tracking of low-amplitude repolarization changes in ambulatory recordings is possible during most of the recording time but requires accurate control of baseline wander and stability of isoelectrical segments. Analysis of time-frequency distributions embedded in repolarization dynamics facilitates detection of abrupt and transient repolarization instabilities, including changes in the level of T-wave alternans and slower periodicities.
authors.affiliation: Cardiovascular Institute, University of Pittsburgh, Pittsburgh, PA 15213, USA. shustermanv@msx.upmc.edu
authors.forename: Vladimir
authors.initials: V
authors.lastname: Shusterman
authors.forename: Anna
authors.initials: A
authors.lastname: Goldberg
mesh_terms: D016477:Artifacts; D015716:Electrocardiography, Ambulatory / Q000379:methods* / Q000706:statistics & numerical data; D005583:Fourier Analysis; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D009200:Myocardial Contraction / Q000502:physiology; D009991:Oscillometry; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D017180:Tachycardia, Ventricular / Q000503:physiopathology; D013997:Time Factors