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. MPSs were found to be significantly related to relative OSA indices. Mouth puffing signals were noted and categorized into four types of MPSs by our algorithms. An MPD was able to detect the signals of mouth puffing. Patients were found to mouth puff when they sleep with their mouths taped. Bland–Altman plot, correlations, independent sample t-test, and ANOVA were analyzed by SPSS 24.0. The video recording was used to validate the program. 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). Ten patients were recruited and had polysomnography. MethodsĪ 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. 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.
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