Quantifying the PR interval pattern during dynamic exercise and recovery

Area of Science:

• Cardiovascular Physiology
• Biomedical Signal Processing
• Medical Instrumentation

Background:

• Accurate PR interval estimation is crucial for assessing atrioventricular conduction.
• High heart rates during exercise can cause T wave overlap with P waves, distorting PR interval measurements.
• Existing methods struggle with T wave interference, limiting diagnostic accuracy.

Purpose of the Study:

• To develop and validate a novel analysis tool for precise time delay estimation in electrocardiographic (ECG) signals.
• To improve PR interval (atrioventricular conduction time) measurement accuracy, particularly during exercise and recovery.
• To mitigate the distortion caused by T wave overlap on P waves at high heart rates.

Main Methods:

• Developed a method involving T wave modeling and cancellation to isolate the P wave.
• Employed a generalized Woody method for PR interval estimation post-T wave cancellation.
• Utilized piecewise linear functions for T wave modeling, validated through statistical comparison.
• Applied the method to ECG data recorded during exercise and recovery phases.

Main Results:

• A piecewise linear T wave model significantly reduced bias in PR interval estimation.
• The novel tool achieved accurate PR interval estimation, even with T wave overlap.
• PR interval recovery slopes differed between sedentary (0.11 ms/s) and athlete men (0.28 ms/s).
• An hysteresis phenomenon was observed between PR and RR intervals during exercise and recovery.

Conclusions:

• The proposed analysis tool effectively enhances PR interval estimation in ECG signals by addressing T wave interference.
• The findings highlight the influence of training status on cardiac electrophysiological recovery.
• The identified hysteresis phenomenon offers new insights into the dynamic relationship between heart rate and conduction during exercise.