Computer-based analysis of heart rate variability signal for detection of sleep disordered breathing in children

Abstract

A computer-based analysis system was developed to display and analyze heart rate variability (HRV). ECG, oxygen saturation and respiratory signals (airflow, abdominal and thoracic movements), were used as raw data. The heart rate variability signal was derived from ECG by applying a Hilbert transform-based algorithm for reliable QRS complex detection. Following the guidelines suggested by the Task Force of the European Society of Cardiology and the North American Society for Pacing and Electrophysiology, appropriate time -domain and frequency-domain methods were used for HRV signal analysis. Autoregressive modeling of the HRV power spectrum was achieved by implementing the Burg algorithm. Three main spectral features were clearly distinguished in the heart rate variability signal spectrum from polysomnographic recordings of different sleep stages and were correlated with respiratory parameters. The integrated graphical user interface was developed using LabView and the signal processing algorithms were implemented using Matlab application programs. In this paper we present an overview of the system and analyze pilot data for two children undergoing nocturnal polysomnography. The pilot data demonstrated that the HRV analysis system may potentially distinguish between periods of normal and sleep disordered breathing (SDB) in children.

Detrended Fluctuation Analysis: A Suitable Long-term Measure of HRV Signals in Children with Sleep Disordered Breathing

“…The study protocols are as described previously in reference [3]. The ECG signals were sampled at 500Hz and digitized with a resolution of 16 bits/sample.…”

“…An Enhanced Hilbert Transform algorithm was used to accurately detect the QRS complex of ECG signals [3]. We validated the DFA results by using known Approximate Entropy (ApEn) derived from our data set.…”

“…However, the substantial cost, long waiting lists and inconvenience of prolonged overnight sleep recordings frequently preclude using this test for routine evaluation. Different measures of the HRV signal characteristics may be useful non-invasive indicators of altered autonomic control associated with sleep disordered breathing and may therefore improve the accuracy and ease of detecting SDB in adults and children [3].…”

Accurate derivation of heart rate variability signal for detection of sleep disordered breathing in children

“…The study protocols are described previously [3] and the ECG signals were sampled at 500Hz and digitized with 16 bits/sample.…”

“…The substantial cost and inconvenience of prolonged overnight sleep recordings in adults and children frequently preclude routine evaluation. The detection and clinical diagnosis of milder cases of SDB in children is further hampered by a number of other factors [3]. Different measures of the HRV signal characteristics may be useful non-invasive indicators of altered autonomic control associated with sleep disordered breathing and may therefore improve the accuracy and ease of detecting SDB in adults and in children [3].…”