Assessing multiscale complexity of short heart rate variability series through a model-based linear approach

Area of Science:

• Physiology
• Biomedical Engineering
• Complexity Science

Background:

• Analyzing short time series of heart period (HP) variability is crucial for understanding cardiac autonomic control.
• Traditional methods like multiscale entropy (MSE) have limitations in discerning complexity changes in short HP series.
• Existing techniques struggle to associate cardiac complexity with underlying physiological mechanisms across different time scales.

Purpose of the Study:

• To introduce and validate a novel multiscale complexity (MSC) method for analyzing short time series, specifically HP variability.
• To assess the contribution of low frequency (LF) and high frequency (HF) bands to cardiac regulation complexity.
• To compare the efficacy of MSC against traditional MSE in distinguishing experimental conditions affecting cardiac rhythm.

Main Methods:

• Developed the MSC method based on autoregressive model coefficients and pole positions in the complex plane within assigned frequency bands.
• Applied MSC to short HP variability series from subjects undergoing graded head-up tilt and paced breathing protocols.
• Compared MSC results with multiscale entropy (MSE) to evaluate performance on short time series analysis.

Main Results:

• MSC demonstrated a reduction in HP variability complexity during head-up tilt, linked to LF band regularization possibly via sympathetic control.
• MSC revealed a decrement in HP variability complexity during slow breathing, attributed to regularization in both LF and HF bands.
• MSE failed to differentiate experimental conditions at time scales greater than 1, highlighting MSC's superior sensitivity for short series.

Conclusions:

• The proposed MSC method provides a more insightful analysis of cardiac control complexity from short time series compared to MSE.
• MSC effectively associates changes in cardiac complexity with specific physiological mechanisms modulating heart rhythm, including autonomic and respiratory influences.
• MSC's ability to analyze complexity across different frequency bands offers a deeper understanding of physiological regulatory processes.