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http://dx.doi.org/10.9718/JBER.2019.40.4.132

Development of Auto-titrating Algorithm for Auto-titrating Positive Airway Pressure  

Park, Jong-Uk (Department of Biomedical Engineering, Yonsei University)
Urtnasan, Erdenebayar (Department of Biomedical Engineering, Yonsei University)
Kim, Yoon-Ji (Department of Biomedical Engineering, Yonsei University)
Lee, Kyoung-Joung (Department of Biomedical Engineering, Yonsei University)
Lee, Sang-hag (R&D department, MEKICS)
Publication Information
Journal of Biomedical Engineering Research / v.40, no.4, 2019 , pp. 132-136 More about this Journal
Abstract
This study proposes an auto-titrating algorithm for auto-titrating positive airway pressure (APAP). The process of the proposed algorithm is as follows. First, sleep apnea-hypopnea and snoring events were detected using nasal pressure. Second, APAP base pressure and SDB events were used for automatic titration of optimal pressure. And, auto-titrating algorithm is built into M3 (MEK-ICS CO. Ltd., Republic of Korea) for evaluation. The detection results of SDB showed mean sensitivity (Sen.) and positive predictive value (PPV.) of 85.7% and 87.8%, respectively. The mean pressure and apnea-hypopnea index (AHI) of auto-titrating algorithm showed $13.0{\pm}5.2cmH_2O$ and $3.0{\pm}2.4$ events/h, respectively. And, paired t-test was conducted to verify whether the performance of our algorithm has no significant difference with AutoSet S9 (p>0.05). These results represent better or comparable outcomes compared to those of previous APAP devices.
Keywords
Auto-titrating; Auto-titrating positive airway pressure (APAP); Sleep-disordered breathing; Sleep apnea-hypopnea; Snoring;
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