Automatic detection of the electrocardiogram T-wave end

Various methods for automatic electrocardiogram T-wave detection and Q-T in terval assessment have been developed. Most of them use threshold level cro ssing. Comparisons with observer detection were performed due to the lack o f objective measurement methods. This study followed the same approach. Obs erver assessments were performed on 43 various T-wave shapes recorded: (il with 100 mm s(-1) equivalent paper speed and 0.6 mV cm(-1) sensitivity; and (ii) with 160 mm s(-1) paper speed and vertical scaling ranging from 0.07 to 0.02 mV cm(-1) depending on the T-wave amplitude. An automatic detection algorithm was developed by adequate selection of the T-end search interval , improved T-wave peak detection and computation of the angle between two 1 0 ms long adjacent segments along the search interval. The algorithm avoids the use of baseline crossing and direct signal differentiation. It perform s well in cases of biphasic and/or complex T-wave shapes. Mean differences with respect to observer data are 13.5 ms for the higher gain/speed records and 14.7 ms for the lower gain/speed records. The algorithm was tested wit h 254 various T-wave shapes. Comparisons with two other algorithms are pres ented. The lack of a 'gold standard' for the Tend detection, especially if small waves occur around if, impeded adequate interobserver assessment and evaluation of automatic methods, it is speculated that a simultaneous prese ntation of normal and high-gain records might turn more attention to this p roblem. Automatic detection methods are in fact faced with 'high-gain' data , as high-resolution analogue-to-digital conversion is already widely used.