Spectral and Bispectral Analysis of Awake Breathing Sounds for Obstructive Sleep Apnea Diagnosis
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Date
2013-04-03
Authors
Karimi, Davood
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Abstract
The goal of this study was to investigate the potential of breathing sounds recorded during wakefulness for Obstructive Sleep Apnea (OSA) screening and severity estimation. Breathing sounds were recorded from 189 subjects in supine and sitting postures during nose and mouth breathing. Features were extracted from power spectrum and bispectrum of the signals. Data from 70 subjects were used for training. Validation accuracy, specificity, and sensitivity for non-OSA and OSA groups were 78%, 77%, and 82%, respectively. Screening based on six OSA risk factors was less accurate. Parallel classification by both breathing sound features and risk factors had high sensitivity (94%). OSA severity estimation, by classifying subjects into three classes of OSA severity, achieved a maximum validation accuracy of 71%. The results demonstrate the potential of breathing sounds for OSA screening. The proposed method can lead to significant improvements in efficient use of resources such as sleep laboratories.
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Keywords
bispectrum, spectrum, OSA, biomedical