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Computerized system for assessing heart rate variability
A Frigy1, A Incze, E Brânzaniuc
1Third Medical Clinic, University of Medicine and Pharmacy 1, Târgu-Mureş, Romania.
Summary
Heart rate variability (HRV) analysis offers a noninvasive method to assess autonomic nervous system activity. A new computerized system analyzes short-term HRV and ventricular rates, demonstrating effectiveness in various cardiac conditions.
Area of Science:
- Cardiology
- Biomedical Engineering
- Physiology
Background:
- Heart rate variability (HRV) analysis is a key noninvasive technique for evaluating autonomic nervous system (ANS) function.
- Developed over the past decade, HRV analysis provides insights into cardiac autonomic regulation.
- Understanding HRV is crucial for diagnosing and managing various cardiovascular conditions.
Purpose of the Study:
- To review the theoretical, methodological, and clinical aspects of heart rate variability (HRV) analysis.
- To present a novel computerized rhythm-analyzer system for HRV and ventricular rate analysis.
- To demonstrate the system's performance in diverse cardiac rhythms, including atrial fibrillation.
Main Methods:
- Review of principal theoretical, methodological, and clinical aspects of HRV analysis.
- Description of a newly developed computerized rhythm-analyzer system.
- Short-term (≤20 minutes) time-domain HRV analysis and statistical analysis of ventricular rate.
- Utilized RR histograms, delta RR histograms, and RR scattergrams for performance evaluation.
Main Results:
- The developed system performs short-term time-domain HRV analysis and statistical ventricular rate analysis.
- The system is effective for analyzing rhythms, particularly in cases of atrial fibrillation.
- Performance was demonstrated using ECG recordings from a healthy subject, a heart failure patient, and an atrial fibrillation patient.
Conclusions:
- The presented computerized system offers a robust tool for HRV and ventricular rate analysis.
- The system's capabilities are validated through graphical and statistical analysis of diverse ECG recordings.
- This technology has significant potential for clinical application in cardiology, especially for patients with arrhythmias like atrial fibrillation.