Faculty of Medicine, and Institute of Brain Science, National Yang-Ming Chiao-Tung University, No. 155, Sec. 2, Li-Nong St., Beitou, Taipei, 11221, Taiwan.
Sleep Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Sleep Breath. 2023 Mar;27(1):153-164. doi: 10.1007/s11325-022-02588-0. Epub 2022 Mar 11.
This study aimed to design a device to monitor mouth puffing phenomena of patients with obstructive sleep apnea when mouth-taped and to employ video recording and computing algorithms to double-check and verify the efficacy of the device.
A mouth puffing detector (MPD) was developed, and a video camera was set to record the patients' mouth puffing phenomena in order to make ensure the data obtained from the device was appropriate and valid. Ten patients were recruited and had polysomnography. A program written in Python was used to investigate the efficacy of the program's algorithms and the relationship between variables in polysomnography (sleep stage, apnea-hypopnea index or AHI, oxygen-related variables) and mouth puffing signals (MPSs). The video recording was used to validate the program. Bland-Altman plot, correlations, independent sample t-test, and ANOVA were analyzed by SPSS 24.0.
Patients were found to mouth puff when they sleep with their mouths taped. An MPD was able to detect the signals of mouth puffing. Mouth puffing signals were noted and categorized into four types of MPSs by our algorithms. MPSs were found to be significantly related to relative OSA indices. When all participants' data were divided into minutes, intermittent mouth puffing (IMP) was found to be significantly different from non-mouth puffing in AHI, oxygen desaturation index (ODI), and time of oxygen saturation under 90% (T90) (AHI: 0.75 vs. 0.31; ODI: 0.75 vs. 0.30; T90: 5.52 vs. 1.25; p < 0.001). Participants with severe OSA showed a higher IMP percentage compared to participants with mild to moderate OSA and the control group (severe: 38%, mild-to-moderate: 65%, control: 95%; p < 0.001).
This study established a simple way to detect mouth puffing phenomena when patients were mouth-taped during sleep, and the signals were classified into four types of MPSs. We propose that MPSs obtained from patients wearing the MPD can be used as a complement for clinicians to evaluate OSA.
本研究旨在设计一种装置来监测口部贴扎的阻塞性睡眠呼吸暂停患者的口吹现象，并利用视频记录和计算算法来双重检查和验证该装置的效果。
开发了一种口吹检测器（MPD），并设置了摄像头来记录患者的口吹现象，以确保从装置获得的数据是适当和有效的。招募了 10 名患者进行多导睡眠图检查。使用 Python 编写的程序来研究该程序算法的有效性，以及多导睡眠图（睡眠阶段、呼吸暂停低通气指数或 AHI、与氧气相关的变量）和口吹信号（MPSs）之间的关系。视频记录用于验证程序。采用 SPSS 24.0 进行 Bland-Altman 图分析、相关性分析、独立样本 t 检验和方差分析。
研究发现，患者在口部贴扎睡眠时会出现口吹现象。MPD 能够检测到口吹信号。我们的算法将口吹信号分为四种类型的 MPSs。MPSs 与相对 OSA 指数显著相关。当将所有参与者的数据分为分钟时，发现间歇性口吹（IMP）在 AHI、氧减饱和度指数（ODI）和氧饱和度低于 90%的时间（T90）方面与非口吹显著不同（AHI：0.75 与 0.31；ODI：0.75 与 0.30；T90：5.52 与 1.25；p<0.001）。与轻度至中度 OSA 和对照组相比，重度 OSA 患者的 IMP 百分比更高（重度：38%；轻度至中度：65%；对照组：95%；p<0.001）。
本研究建立了一种简单的方法来检测睡眠时口部贴扎的患者的口吹现象，并将信号分为四种类型的 MPSs。我们提出，从佩戴 MPD 的患者获得的 MPSs 可以作为临床医生评估 OSA 的补充。
