Accurate end systole detection in dicrotic notch-less arterial pressure waveforms

Area of Science:

• Cardiovascular Physiology
• Biomedical Engineering
• Signal Processing

Background:

• Accurate end systole identification is vital for cardiac function and systolic time interval analysis.
• Dicrotic notches in proximal arterial waveforms mark end systole, but are absent in common distal measurements.
• Existing methods struggle with end systole detection in distal, dicrotic notch-less arterial pressure waveforms.

Purpose of the Study:

• To develop and validate a novel algorithm for end systole detection in dicrotic notch-less arterial pressure waveforms.
• To compare the accuracy of the new algorithm against an existing method for estimating systolic duration.
• To establish a robust validation method for end systole detection in distal pressure signals.

Main Methods:

• A new end systole detection algorithm utilizing a beta distribution probability density function as an adaptive weighting function was developed.
• The algorithm's accuracy was assessed on dicrotic notch-less distal pressure waveforms from ten pigs under varied hemodynamic states.
• A validation method was created using simultaneously measured aortic pressure, projected via pulse transit time (PTT) to distal signals.

Main Results:

• The new algorithm demonstrated superior accuracy in estimating systolic duration compared to the existing method.
• Mean difference ± limits of agreement for systolic duration estimation were [Formula: see text] for the new algorithm versus [Formula: see text] for the existing algorithm.
• The validation method provided a reliable comparison point for algorithm performance in the absence of dicrotic notches.

Conclusions:

• The developed algorithm offers a significant improvement for end systole detection in distal arterial pressure waveforms.
• This advancement is critical for accurate cardiac function and systolic time interval assessment in clinical settings.
• The novel validation approach using PTT-projected aortic pressure enhances the reliability of evaluating end systole detection algorithms.