Cross-database evaluation of a multilead heartbeat classifier.

In this paper, we studied the improvement in heartbeat classification achieved by including information from multilead ECG recordings in a previously developed and validated classification model. This model includes features from the RR interval series and morphology descriptors for each lead calculated from the wavelet transform. The experiments were carried out in the INCART database, available in Physionet, and the generalization was corroborated in private and public databases.

Investigation of parameters highlighting drug induced small changes of the T-wave's morphology for drug safety studies.

In guideline E14, the American Food and Drug Administration (FDA) requests for clinical studies to investigate the prolongation of the heart rate corrected QT-interval (QTc) of the ECG. As drug induced QT-prolongation can be caused by changes in the repolarisation of the ventricles, it is so far a thorough ECG biomarker of risk for ventricular tachyarrhythmias and Torsade de Pointes (TdP). Ventricular repolarisation changes not only change QT but also influence the morphology of the T-wave.

Predicting the QRS complex and detecting small changes using principal component analysis.

In this paper, a new method for QRS complex analysis and estimation based on principal component analysis (PCA) and polynomial fitting techniques is presented. Multi-channel ECG signals were recorded and QRS complexes were obtained from every channel and aligned perfectly in matrices. For every channel, the covariance matrix was calculated from the QRS complex data matrix of many heartbeats.