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Statistical signal characterization for congestive heart failure patient's classification.
Bader Al Ghunaimi1, Abdulnasir Hossen, Mohammed O Hassan
1Electrical and Computer Engineering Department, College of Engineering, Sultan Qaboos University, Oman.
Summary
This study introduces a novel time-domain analysis of heart rate variability (HRV) using Statistical Signal Characterization (SSC) for Congestive Heart Failure (CHF) screening. The method accurately identifies patients with CHF using R-R interval data.
Area of Science:
- Cardiology
- Biomedical Engineering
- Signal Processing
Background:
- Congestive Heart Failure (CHF) poses a significant health burden.
- Early detection of CHF is crucial for effective management and improved patient outcomes.
- Traditional heart rate variability (HRV) analysis methods may not capture all relevant physiological changes.
Purpose of the Study:
- To investigate a novel time-domain analysis technique for R-R interval (RRI) data.
- To assess the efficacy of this technique in screening patients for Congestive Heart Failure (CHF).
- To develop a robust method for early CHF detection using signal characterization.
Main Methods:
- Utilized Hilbert transformation to generate an analytical signal from RRI data.
- Applied Statistical Signal Characterization (SSC) to derive four key parameters: amplitude mean, period mean, amplitude deviation, and period deviation.
- Analyzed these parameters over sliding segments (300, 32, and 16 samples) of instantaneous amplitudes and frequencies.
- Employed Receiver Operating Characteristic (ROC) curves to determine optimal threshold values for CHF identification.
Main Results:
- The new technique demonstrated high classification accuracy on both trial and test datasets.
- Achieved correct classification rates of 31/33 for trial data and 65/70 for test data.
- The SSC parameters derived from RRI data proved effective in distinguishing CHF patients from normal subjects.
Conclusions:
- The proposed time-domain analysis technique based on SSC of the analytical RRI signal is a promising tool for CHF screening.
- This method offers a potentially accurate and efficient approach for early detection of Congestive Heart Failure.
- Further validation on larger and diverse datasets is warranted to confirm its clinical utility.