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. 2004 Oct;9(4):316-22.
doi: 10.1111/j.1542-474X.2004.94566.x.

Wavelet-based analysis of heart-rate-dependent ECG features

Martin K Stiles  1 , David Clifton, Neil R Grubb, James N Watson, Paul S Addison
Affiliations

Wavelet-based analysis of heart-rate-dependent ECG features

Martin K Stiles et al. Ann Noninvasive Electrocardiol. 2004 Oct.

Abstract

Background: Wavelet-based methods of analyzing ECG signals have been used to identify specific features in cardiac arrhythmias. Since some of these features are rate dependent, it is a requirement that they are examined across a range of physiological heart rates. The wavelet transform is a signal analysis tool that can elucidate spectral and temporal information simultaneously from complex signals, including the ECG. The aim of this study was to identify the local frequency characteristics of the ECG using a real-time wavelet scalogram and to study the rate dependence of these features.

Methods: We examined the spectral temporal behavior of the local characteristics of the electrocardiogram (ECG) of 10 patients, in whom precise control of heart rate was achieved using right atrial pacing. Temporary reprogramming was used to adjust the paced atrial rate to predetermined values so that a rate-controlled rhythm was produced that closely resembled sinus rhythm.

Results: Rate-dependent features are seen on time-frequency scalograms. As the rate increases, the temporal spacing of features decrease and the frequency bands shift upward on the plot. Two patients with abnormal atrioventricular conduction demonstrate features of Wenckebach conduction and fusion.

Conclusions: Characterization of the rate-dependent features of the ECG in a paced atrial rhythm by wavelet transform techniques has revealed some additional information not readily seen on single lead ECG analysis. This model provides a surrogate for changes that might be expected during rate changes in physiological sinus rhythm. It is envisaged that this method will offer advantages in detecting features of clinical significance that may not be readily seen by existing methods.

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Figures

Figure 1
Figure 1
Entire recording of pacing maneuvers.
Figure 2
Figure 2
Close‐up of a rate transition point.
Figure 3
Figure 3
Onset of V pacing. The ridge of the wavelet band associated with the beat frequency is shown as dashed line in the plot. The ridge increases in frequency from fb= 2 Hz to fm= 2.6 Hz over the fusion region between the two arrows. This band reverts to the prefusion intrinsic conduction frequency when conduction is no longer competing.
Figure 4
Figure 4
Wenckebach phenomenon.
See this image and copyright information in PMC

References

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