Aging and cardiovascular complexity: effect of the length of RR tachograms
Karthi Balasubramanian1, Nithin Nagaraj2
1Department of Electronics and Communication Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Amrita University , India.
Insights
Aging hearts show reduced physiological complexity, increasing cardiovascular disease risk. Complexity measures like Lempel-Ziv (LZ) and Effort-To-Compress (ETC) effectively analyze short heart-beat data, unlike Sample Entropy (SampEn).
Area of Science:
- Cardiology
- Biomedical Engineering
- Nonlinear Dynamics
Background:
- Aging leads to decreased heart control mechanism complexity, raising cardiovascular disease risk.
- Cardiovascular diseases are a leading global cause of mortality.
- Cardiac signals are nonstationary and nonlinear, necessitating complexity measures for analysis.
Purpose of the Study:
- To evaluate complexity measures for characterizing heart aging.
- To determine the minimum RR tachogram length for complexity analysis.
- To compare Lempel-Ziv complexity (LZ), Sample Entropy (SampEn), and Effort-To-Compress (ETC) in older and younger subjects.
Main Methods:
- Analysis of RR tachograms from healthy young and old subjects.
- Application of three complexity measures: LZ, SampEn, and ETC.
- Determination of the minimum data length required for reliable complexity assessment.
Main Results:
- All complexity measures showed significantly lower values in older subjects compared to younger ones.
- LZ and ETC required only 10 samples, while SampEn needed at least 80 samples.
- LZ and ETC demonstrated effectiveness with very short RR tachograms.
Conclusions:
- Complexity analysis effectively differentiates heart dynamics between age groups.
- LZ and ETC are suitable for analyzing cardiovascular dynamics due to their ability to use short RR tachograms.
- The choice of complexity measure impacts the required data length for heart rate variability analysis.
Abstract:
As we age, our hearts undergo changes that result in a reduction in complexity of physiological interactions between different control mechanisms. This results in a potential risk of cardiovascular diseases which are the number one cause of death globally. Since cardiac signals are nonstationary and nonlinear in nature, complexity measures are better suited to handle such data. In this study, three complexity measures are used, namely Lempel-Ziv complexity (LZ), Sample Entropy (SampEn) and Effort-To-Compress (ETC). We determined the minimum length of RR tachogram required for characterizing complexity of healthy young and healthy old hearts. All the three measures indicated significantly lower complexity values for older subjects than younger ones. However, the minimum length of heart-beat interval data needed differs for the three measures, with LZ and ETC needing as low as 10 samples, whereas SampEn requires at least 80 samples. Our study indicates that complexity measures such as LZ and ETC are good candidates for the analysis of cardiovascular dynamics since they are able to work with very short RR tachograms.
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