ArticleJournal of medical systems2016
New Rule-Based Algorithm for Real-Time Detecting Sleep Apnea and Hypopnea Events Using a Nasal Pressure Signal.
Article in Journal of medical systems, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- An LSTM Network for Apnea and Hypopnea Episodes Detection in Respiratory Signals.Sensors (Basel, Switzerland) · 2021Article
- Cascading detection model for prediction of apnea-hypopnea events based on nasal flow and arterial blood oxygen saturation.Sleep & breathing = Schlaf & Atmung · 2020Article
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Authors and funding
4 authors.
Funding
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Abstract
We developed a rule-based algorithm for automatic real-time detection of sleep apnea and hypopnea events using a nasal pressure signal. Our basic premise was that the performance of our new algorithm using the nasal pressure signal would be comparable to that using other sensors as well as manual annotation labeled by a technician on polysomnography study. We investigated fifty patients with sleep apnea-hypopnea syndrome (age: 56.8 ± 10.5 years, apnea-hypopnea index (AHI): 36.2 ± 18.1/h) during full night PSG recordings at the sleep center. The algorithm was comprised of pre-processing with a median filter, amplitude computation and apnea-hypopnea detection parts. We evaluated the performance of the algorithm a confusion matric for each event and statistical analyses for AHI. Our evaluation achieved a good performance, with a sensitivity of 86.4 %, and a positive predictive value of 84.5 % for detection of apnea and hypopnea regardless of AHI severity. Our results indicated a high correlation with the manually labeled apnea-hypopnea events during PSG, with a correlation coefficient of r = 0.94 (p < 0.0001) and a mean difference of -2.9 ± 11.6 per hour. The proposed new algorithm could provide significant clinical and computational insights to design a PSG analysis system and a continuous positive airway pressure (CPAP) device for screening sleep quality related in patients with sleep apnea-hypopnea syndrome.
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