Real-time spectral analysis of HRV signals: an interactive and user-friendly PC system

Area of Science:

• Biomedical Engineering
• Physiology
• Signal Processing

Background:

• Heart rate variability (HRV) analysis is crucial for assessing autonomic nervous system function.
• Accurate spectral analysis of HRV signals requires robust and real-time computational methods.
• Existing systems may lack user-friendliness or computational efficiency for non-specialists.

Purpose of the Study:

• To develop and present a real-time system for spectral analysis of heart rate variability (HRV) signals.
• To enhance user-friendliness for non-specialized personnel through a Windows-like operating environment.
• To ensure robust spectral estimation via an advanced hybrid computational method.

Main Methods:

• A PC-based system integrated with a low-cost data acquisition board.
• Real-time spectral analysis utilizing a hybrid method combining Fast Fourier Transform (FFT) and autoregressive (AR) modeling.
• Continuous stationarity checking of the HRV signal sequence.
• Real-time computation and display of FFT for each data block.

Main Results:

• The developed system provides a user-friendly interface for real-time HRV spectral analysis.
• The hybrid FFT-AR method ensures robust Power Spectral Density (PSD) estimation.
• Continuous stationarity checks enhance the reliability of spectral analysis.
• Interactive AR model order selection is facilitated by real-time FFT display.

Conclusions:

• The presented system offers a robust, user-friendly, and efficient solution for real-time HRV spectral analysis.
• The hybrid spectral estimation algorithm provides reliable results, suitable for both specialists and non-specialists.
• The system facilitates interactive analysis and model selection, improving the accuracy of HRV assessment.