Copyright ©ERS Journals Ltd 2007 Automatic detection of sleep-disordered breathing from a single-channel airflow record1 Dept of Pulmonology, Fukuoka National Hospital, Fukuoka, and 2 Dept of Public Health Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Japan. CORRESPONDENCE: H. Nakano, Dept of Pulmonology, Fukuoka National Hospital, 4-39-1 Yakatabaru, Minami-ku, Fukuoka, 811-1394, Japan. Fax: 81 929669444. E-mail: nakano_h{at}palette.plala.or.jp Keywords: Power spectral analysis, screening, signal processing, sleep apnoea
Received: July 11, 2006
Single-channel airflow monitors developed for screening of sleep-disordered breathing (SDB) have conflicting results for accuracy. It was hypothesised that the analytical algorithm is crucial for the performance and the present authors tried to develop a novel computer algorithm.
A total of 399 polysomnography (PSG) records were employed, including a thermal sensor signal. The first 100 records were used in the development of the algorithm and the remainder for validation. In addition, 119 PSG records, including a thermocouple signal and a nasal pressure signal, were used for the validation. The algorithm was designed to obtain a time series (flow-power) using power spectral analysis, which expresses fluctuation in the airflow signal amplitude. From the time series the algorithm detects transient falls of the flow-power and calculates flow-respiratory disturbance index (RDI), defined as the number of falls per hour.
In the validation group, the areas under receiver operating characteristic curves for diagnosis of SDB (apnoea/hypopnoea index
The present results suggest that a single-channel airflow monitor can be used to detect sleep-disordered breathing automatically if the analytic algorithm is optimised.
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