Generalized Multiscale Entropy Analysis: Application to Quantifying the Complex Volatility of Human Heartbeat Time...

Area of Science:

• Physiology
• Complexity Science
• Biomedical Engineering

Background:

• Multiscale entropy (MSE) analysis is a standard method for quantifying time series complexity.
• Traditional MSE uses the first moment (mean) for coarse-graining, limiting its scope.

Purpose of the Study:

• To introduce and validate a generalized MSE analysis using higher moments, specifically the second moment (variance).
• To apply this novel MSE variance method to analyze heartbeat time series complexity.

Main Methods:

• Generalized multiscale entropy (MSE) analysis using the second moment (variance) to quantify signal volatility dynamics across multiple time scales.
• Application of MSE variance to analyze heartbeat time series from healthy young subjects.

Main Results:

• The dynamics of heartbeat time series volatility exhibit high complexity in healthy young individuals.
• Multiscale complexity of volatility, similar to that of mean heart rate, decreases with aging and pathology.
• Observed 'bursty' dynamics may indicate intermittency in physiological energy and information flows.

Conclusions:

• Generalized MSE (using variance) provides a novel approach to quantify the complex dynamics of signal volatility.
• This method reveals significant changes in heartbeat volatility complexity with aging and disease.
• The approach holds potential for analyzing diverse physiological and non-physiological time series.