Introduction: The purpose of the study was to evaluate the effects of maxillomandibular advancement (MMA) surgery with counterclockwise rotation on soft tissue oral and nasal structures. Materials and Methods: This retrospective study included 34 subjects diagnosed with OSA who underwent MMA at the Stanford Sleep Clinic. Initial (T1) and Final (T2) CBCTs were evaluated and compared for 10 hard tissue and 15 soft tissue measurements. Additionally, the external nasal valve surface area was measured and compared between the two time points. A 3D superimposition was performed and used to evaluate the relative hard and soft tissue movements. Results: There was a linear correlation in the advancement of the maxilla to the sagittal movement of the upper lip of 75%, while the mandibular soft tissue moved 91-93% of the mandibular sagittal position. The interalar width and mouth width increased significantly following surgery while the lower vermillion border length decreased significantly. There was a clinically significant increase in the average surface area of the external nasal valve by 28%. No correlations were found between maxillary impaction and soft tissue oral or nasal measurements. Conclusion: MMA with CCW results in significant changes to the soft tissue nose and oral region. Soft tissue planning must be considered to maintain desirable esthetics following surgery.

Abstract Sleep Apnea (SA) is a common disorder that affects approximately 2% of middle-aged women and 4% of middle-aged men. It is characterized by repetitive cessation of breathing during sleep. SA has significant health and social consequences such as daytime sleepiness, impaired quality of life, and in the worst case, myocardial infarction and sudden cardiac death. It has been estimated that approximately 80% of individuals with moderate to severe SA syndrome have not been diagnosed. The lack of patient sleep histories has caused low identification of SA and referral rates, especially in primary care facilities. Moreover, due to the inadequate prevalence of overnight polysomnography (PSG) as a standard clinical test of SA, patients suspected of having this sleep disorder have to wait several months for diagnosis and treatment. The costly and time-consuming nature of PSG and the lack of sleep clinics have created a demand for suitable home-based health monitoring devices. Over the years, several devices have been developed to monitor sleep unobtrusively, while an individual is lying in bed. However, most of these devices would either disrupt the sleep of the patient or be disrupted by the patient during routine bed sheet changes. Pressure measurement using a Pressure Sensitive Mat (PSM) enables a non-contact approach for monitoring patient vital signs such as respiration rate. The PSM has the potential to replace obtrusive breathing sensors in the sleep lab and to be used as a pre-screening tool for patients suspected of having sleep apnea. This thesis proposes multiple algorithms applicable to PSM in order to assess sleep quality. First, fusion techniques are proposed to extract a breathing signal from PSM. Second, a wide range of machine learning approaches including a simple threshold-based algorithm, a linear support vector machine (SVM) and two deep learning methods (i.e., a temporal convolutional network (TCN) and a bidirectional long short-term memory (BiLSTM) network) are compared to find a good- iii performing method for automatically detecting central sleep apnea (CSA) events from PSM signals. The results show that the accuracy of the model with the best performance is 95.1% and it is achieved by the BiLSTM network. Finally, by applying SVM, personalized systems are optimized to investigate long-term sleep pattern changes such as central apnea index (CAI), bed occupancy (BO), day-clock, and night-clock from previously recorded data.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18450号 / 医博第3905号 / 新制||医||1004(附属図書館) / 31328 / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊達 洋至, 教授 稲垣 暢也, 教授 森田 智視 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第19367号 / 医博第4044号 / 新制||医||1011(附属図書館) / 32381 / 新制||医||1011 / 京都大学大学院医学研究科医学専攻 / (主査)教授 中山 健夫, 教授 佐藤 俊哉, 教授 横出 正之 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第19400号 / 医博第4051号 / 新制||医||1012(附属図書館) / 32425 / 京都大学大学院医学研究科医学専攻 / (主査)教授 横出 正之, 教授 福原 俊一, 教授 山下 潤 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第19603号 / 医博第4110号 / 新制||医||1014(附属図書館) / 32639 / 京都大学大学院医学研究科医学専攻 / (主査)教授 中山 健夫, 教授 富樫 かおり, 教授 松田 秀一 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20261号 / 医博第4220号 / 新制||医||1020(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 福田 和彦, 教授 木村 剛, 教授 大森 孝一 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20987号 / 医博第4333号 / 新制||医||1027(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊達 洋至, 教授 長船 健二, 教授 一山 智 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

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