Development of graphical user interface for heart rate variability analysis of sleep-disordered breathing
Abstract
We present a graphical user interface software environment that enables sleep specialists to analyze, quantify and display time-domain, frequency-domain, and nonlinear dynamics measures of heart rate variability (HRV) signal. A user-friendly graphical user interface (GUI) and appropriate signal processing algorithms were developed and implemented in MATLAB 6.0, following the guidelines of the Task Force of the European Society of Cardiology and the North American Society for Pacing and Electrophysiology. This GUI provides the capacity to import or read sleep data (ECG, EEG, blood pressure, respiratory, oxygen saturation, etc.) under user control and displays them individually or collectively in a graphical window for visual comparison. It facilitates the user to analyze 2 min length of data at a time to carry out the analysis. Raw ECG data is preprocessed for reliable QRS detection and the HRV signal is derived, which is then displayed along with respiration signal in the analysis window. After this step time-domain, frequency domain, and nonlinear dynamics analyses of the HRV signal are performed to extract sensitive measures used in detecting and diagnosing sleep disordered breathing. The system was developed and validated using data from the MIT-BIH Polysomnographic Database and ECG-Apnea Database. After confirmation and reliability testing, this software tool was used to analyze sleep data for classification of normal and abnormal children suffering from sleep disordered breathing (SDB). Data from normal and children diagnosed with SDB showed that the system could potentially distinguish between normal children and children suffering from sleep disordered breathing.
Subject Area
Computer science|Surgery|Biomedical research
Recommended Citation
Magdum, Vaishali Chandrakant, "Development of graphical user interface for heart rate variability analysis of sleep-disordered breathing" (2004). ETD Collection for University of Texas, El Paso. AAIEP10578.
https://scholarworks.utep.edu/dissertations/AAIEP10578