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Mutual information-based approach to the analysis of dynamic electrocardiograms
Mingjing Yang1, Hui Zhang, Huiru Zheng
1College of Physics and Information Engineering, Fuzhou University, Fuzhou, China.
Summary
This study introduces an information theory approach to analyze dynamic electrocardiograms (ECG). Mutual information analysis of R-R intervals reveals distinct patterns, aiding in the classification of heart movement and cardiovascular diseases.
Area of Science:
- Cardiology
- Biomedical Engineering
- Information Theory
Background:
- Dynamic electrocardiograms (ECG) are crucial for understanding heart function and detecting cardiovascular diseases.
- Previous research utilized chaos and fractal theories to analyze nonlinear information in ECG signals.
Purpose of the Study:
- To propose an information theory approach for analyzing dynamic ECG data.
- To investigate patterns in R-R intervals over different times of day and subject groups.
Main Methods:
- Calculation and analysis of mutual information from R-R intervals.
- Utilized data from four subject groups recorded at different times.
Main Results:
- Heart movement exhibits characteristics similar to chaotic movement.
- Mutual information of R-R intervals shows distinct patterns across different times of day and subject groups.
Conclusions:
- The proposed information theory approach is a valuable tool for dynamic ECG analysis.
- This method can support the classification of heart movement and the diagnosis of cardiovascular diseases.
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Introduction
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Definition
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Parts of an ECG
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