Alignment of R-R interval signals using the circadian heart rate rhythm

Area of Science:

• Cardiology
• Biomedical Engineering
• Chronobiology

Background:

• R-R interval signals are commonly aligned using recording start times.
• This traditional method may be inaccurate due to variations in individual circadian rhythms.
• Accurate alignment is crucial for analyzing heart rate (HR) variability patterns.

Purpose of the Study:

• To propose novel algorithms for aligning R-R interval signals based on circadian HR rhythm.
• To demonstrate the limitations of horological time as an alignment criterion.
• To identify and classify distinct patterns within the circadian HR rhythm.

Main Methods:

• Developed two new alignment algorithms: Puzzle Piece Alignment (PPA) and Event Based Alignment (EBA).
• Converted R-R interval data into time windows to compute mean HR per window.
• Algorithms search for matching circadian patterns to align signals, considering HR variability.

Main Results:

• Both PPA and EBA successfully aligned R-R interval signals according to HR circadian rhythmicity.
• Experimental validation using Physionet Data Bank signals confirmed algorithm efficacy.
• Findings revealed multiple distinct patterns within the circadian HR rhythm.

Conclusions:

• Horological time is an inadequate criterion for aligning R-R interval signals.
• The proposed PPA and EBA algorithms offer a more accurate alignment method by incorporating circadian HR patterns.
• Automatic classification of signals based on identified circadian HR rhythm patterns is suggested.