Major cardiac organisations recommend U wave abnormalities should be reported during ECG interpretation. However, U waves cannot be measured in patients with atrial fibrillation (AF) due to the obscuring fibrillatory wave. The aim was to validate a U wave measurement algorithm for AF patients. Multi-beat averaging was applied to ECGs of 25 patients during paroxysms of AF and the presence of U waves compared to those from the same patients during sinus rhythm (SR). In a further database of 10 long-term AF recordings, the number of beats for effective U wave extraction by the algorithm was calculated. U waves were revealed in all AF recordings and there was no significant difference between the presence of U waves in AF and SR (p = 0.88). U wave amplitude was significantly increased in AF (mean (s.d.) amplitude 55 (39) AF vs 37 (28) μV SR, p = 0.005). The presence of U waves could easily be discerned when as few as 10 beats were used in the algorithm. The study demonstrates the validity of the algorithm to reveal U waves in AF recordings. The algorithm offers the potential to detect U wave abnormalities in patients with AF.

The reporting of U wave abnormalities is clinically important, but the measurement of this small electrocardiographic (ECG) feature is extremely difficult, especially in challenging recording conditions, such as stress exercise, due to contaminating noise. Furthermore, it is widely stated that ECG U waves are rarely observable at heart rates greater than 90 bpm. The aims of the study were (i) to assess the ability of multi-beat averaging to reveal the presence of U waves in ECGs contaminated by noise following exercise and (ii) to quantify the effect of exercise on U wave amplitude. The multi-beat averaging algorithm was applied to recover U waves in 20 healthy subjects in pre- and post-exercise recordings. Average beats were generated from 30 beat epochs. The prevalence of U waves and their amplitudes were measured in pre- and post-exercise recordings and changes in amplitude due to exercise were quantified. U waves were present in all subjects in pre-exercise recordings. Following exercise, U waves could not be seen in standard ECG but were observable in all 20 subjects by multi-beat averaging and despite significantly increased mean (±SD) heart rate (63 ± 8 bpm vs. 100 ± 9 bpm, p < 0.0001). Furthermore, U waves were observable in all subjects with heart rates greater than 90 bpm. U waves significantly increased in amplitude following exercise (38 ± 15 μV vs. 80 ± 48 μV, p = 0.0005). Multi-beat averaging is effective at recovering U waves contaminated by noise due to exercise. U waves were measurable in all subjects, dispelling the myth that U waves are rarely seen at elevated heart rates. U waves exhibit increased amplitudes at elevated heart rates following exercise.

Atrial fibrillation (AF) is characterised by rapid beat interval changes. The aim of the study was to investigate the effect of such changes on ECG ventricular repolarisation characteristics. In 10 AF recordings beat averaging of lead V4 was used to generate averaged T waves where the preceding beat interval