Classification of sleep disordered breathing in the evaluation of acoustic sound in correlation with the ECG signal

Current trends in patient care emphasize the overall quality of life as a goal for treatment outcome, therefore various ways of continuous patient monitoring have become increasingly popular in healthcare. Since an average human spends one third of his life asleep, it is apparent that the quality of sleep has an important impact on the overall life quality. The aim of the study was to investigate the predictive capability of a dual-modality analysis scheme for the detection of sleep disordered breathing, specifically for automatic detection of sleep disorders such as snoring, wheezing or sleep apnea in the evaluation of acoustic sound in correlation with the electrocardiography (ECG) signal during sleep.