Heart Rate Fragmentation: A Symbolic Dynamical Approach

Area of Science:

• Cardiology
• Physiology
• Data Science

Background:

• Introduced heart rate fragmentation (HRF) as a dynamical marker of anomalous heart rate variability.
• HRF may indicate breakdown of neuroautonomic control of the sino-atrial node, potentially confounding traditional heart rate variability analysis.
• Previous work established HRF and metrics for its quantification.

Purpose of the Study:

• Develop a symbolic dynamical approach to quantify HRF.
• Assess age-related changes in dynamical patterns of HRF in healthy individuals and coronary artery disease (CAD) patients.
• Compare HRF patterns between healthy subjects and CAD patients.

Main Methods:

• Employed a symbolic dynamical method using a ternary map of NN interval time series.
• Analyzed the frequency of symbolic sequences (words) with specific features.
• Utilized annotated Holter ECG data from healthy subjects and CAD patients (THEW database).

Main Results:

• Older individuals exhibited significantly higher HRF than younger individuals.
• Healthy aging associated with increased "soft" inflection points (acceleration/deceleration to zero acceleration transitions).
• CAD patients showed increased "hard" inflection points (acceleration/deceleration reversals) and higher overall fragmentation compared to healthy subjects.

Conclusions:

• The symbolic dynamical method effectively quantifies HRF.
• Both CAD and older age are independently associated with increased HRF.
• HRF in healthy aging differs phenotypically from HRF in CAD.