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Complexity analysis of 24 hours heart rate variability time series
M Ferrario1, M G Signorini, S Cerutti
1Dipartimento di Bioingegneria, Politecnico di Milano, Italy.
Summary
This study uses Lempel-Ziv (LZ) complexity to analyze heart rate variability (HRV) time series. The LZ measure effectively distinguishes between healthy individuals and those with cardiovascular disease, offering potential diagnostic insights.
Area of Science:
- Cardiology
- Biomedical Engineering
- Data Science
Background:
- Heart rate variability (HRV) analysis is crucial for assessing cardiovascular health.
- Complexity measures offer novel insights into physiological time series.
- Lempel-Ziv (LZ) complexity quantifies pattern recurrence in time series data.
Purpose of the Study:
- To evaluate the utility of Lempel-Ziv (LZ) complexity for analyzing heart rate variability (HRV) time series.
- To differentiate complexity patterns between healthy subjects and patients with cardiovascular diseases.
- To explore the sensitivity of LZ complexity to different coding methods in HRV analysis.
Main Methods:
- Computation of Lempel-Ziv (LZ) complexity on 24-hour HRV time series.
- Application of binary and ternary coding schemes for LZ analysis.
- Comparison of LZ complexity measures between healthy controls and cardiovascular disease patient groups.
- Validation using simulated time series signals.
Main Results:
- The Lempel-Ziv (LZ) complexity measure effectively differentiates between healthy individuals and patients with cardiovascular diseases.
- Binary coding of HRV time series with LZ complexity is sensitive to underlying dynamical systems.
- Ternary coding highlights the presence of stationary states (repeated RR intervals).
- LZ complexity analysis shows reliable discrimination between the healthy and disease groups.
Conclusions:
- Lempel-Ziv (LZ) complexity provides a robust method for quantifying HRV time series complexity.
- The LZ measure demonstrates significant potential for distinguishing cardiovascular health status.
- Further research into LZ complexity and its correlation with sudden death risk may yield new diagnostic tools.
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