Comparison of three T-wave delineation algorithms based on wavelet filterbank, correlation and PCA

There is a large interest in analysing the QT-interval, as a prolonged QT-interval can cause the development of ventricular tachyarrhythmias such as Torsade de Pointes. One major part of QT-analysis is T-end detection. Three automatic T-end delineation methods based on wavelet filterbanks (WAM), correlation (CORM) and Principal Component Analysis PCA (PCAM) have been developed and applied to Physionet QT database. All algorithms tested on Physionet QT database showed good results, while PCAM produced better results than WAM and CORM achieved best results. Standard deviation in sampling points (f
_s
=250Hz) have been 33.3 (WAM), 8.0 (PTDM) and 7.8 (CORM). It could be shown that WAM is prone to interference while CORM is the most stable method even under bad conditions. Furthermore it was possible to detect significant QT-prolongation caused by Moxifloxacin in Thorough QT Study # 2 using CORM. QT-prolongation is significantly correlated to blood plasma concentration of Moxifloxacin.