Abstract Dicrotic notch detection in aortic pressure waveforms enables a reference in time, marking the transition from systole to diastole. Identification of the notch is useful in applications studying events specific to systole or diastole, for example, models that estimate cardiac function, and systolic time intervals such as left ventricular ejection time. The purpose of this study was to test a new dicrotic notch detection algorithm, against an existing end systole estimation method. The new algorithm utilises a shear transform, which is adaptive based on the shape of the aortic pressure waveform. To assess the accuracy of the two algorithms, 80 beats aortic pressure waveforms were used from four porcine pigs. The pigs were subjected to hemodynamic modification in order to test the algorithms on different waveforms shapes. The dicrotic notches were first found by eye in the 80 beats waveforms, and systolic time, from the start of the beat to the dicrotic notch, was the metric used to compare the accuracy of dicrotic notch locations. The new algorithm identifies features of the dicrotic notch when it is present and estimates the location when it is less clear, better than the existing method of end systole estimation. This result was evident in the mean difference between measured and estimated systolic times of 0.5ms vs 11.6ms, for the new algorithm and existing respectively. The new method also showed significantly less variation in its estimate than the existing method, across all pigs’ hemodynamic states.