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Objectives: Longer-term electrocardiographic effects of multiple inappropriate ICD shocks were investigated to study their hypothesized pro-arrhythmic potential.Design: Thirteen male patients with ischemic cardiomyopathy who received ≥2 inappropriate shocks within 24 h and for whom 12-lead ECGs were available both before and within 72h after the inappropriate shocks were analyzed. Exclusion criteria included continuous ventricular pacing, underlying AF, events within 6 weeks after lead implantation and concomitant acute medical problems.Results: A total of 149 inappropriate shocks (mean 11 ± 19) were received. There were no significant differences in any of the measured intervals or morphological indices, nor was there a correlation between the "before-after" differences and the number of shocks received. Non-significant changes showed Percentage of Loop Area increase and relative T-wave Residuum decrease while the opposite changes have previously been associated with arrhythmic risk.Conclusions: No potentially pro-arrhythmic electrocardiographic changes were found 19 h after multiple inappropriate shocks. [ABSTRACT FROM AUTHOR]

Cardiac arrhythmia or irregular heartbeats are an important feature to assess the risk on sudden cardiac death and other cardiac disorders. Automatic classification of irregular heartbeats is therefore an important part of ECG analysis. We propose a tensor-based method for single- and multi-channel irregular heartbeat classification. The method tensorizes the ECG data matrix by segmenting each signal beat-by-beat and then stacking the result into a third-order tensor with dimensions channel × time × heartbeat. We use the multilinear singular value decomposition to model the obtained tensor. Next, we formulate the classification task as the computation of a Kronecker Product Equation. We apply our method on the INCART dataset, illustrating promising results.

T wave alternans is defined as changes in the T wave amplitude in an ABABAB-pattern. It can be found in ECG signals of patients with heart diseases and is a possible indicator to predict the risk on sudden cardiac death. Due to its low amplitude, robust automatic T wave alternans detection is a difficult task. We present a new method to detect T wave alternans in multichannel ECG signals. The use of tensors (multidimensional matrices) permits the combination of the information present in different channels, making detection more reliable. The possibility of decomposition of incomplete tensors is exploited to deal with noisy ECG segments. Using a sliding window of 128 heartbeats, a tensor is constructed of the T waves of all channels. Canonical Polyadic Decomposition is applied to this tensor and the resulting loading vectors are examined for information about the T wave behavior in three dimensions. T wave alternans is detected using a sign change counting method that is able to extract both the T wave alternans length and magnitude. When applying this novel method to a database of patients with multiple positive T wave alternans tests using the clinically available spectral method tests, both the length and the magnitude of the detected T wave alternans is larger for these subjects than for subjects in a control group.