隨著睡眠問題與相關疾病的盛行，對睡眠檢查的需求日益增加。然而，目前醫院睡眠中心的完整檢查量能不足，等候床位的時間過長，可能導致延誤患者診療期程，此外，專業睡眠技師的人力有限，睡眠檢查需要他們整夜監測並進行資料分析，進而完成報告讓醫師診斷並給予治療或建議。因此，本研究提出一套居家睡眠檢查的流程，作為替代方案或是快速篩檢，以緩解醫院的壓力。此檢查結合能感測腦波與眼電波的眼罩以及居家呼吸紀錄器，並提供受試者手機搭配操作，可以同步量測睡眠時的大腦活動與呼吸狀況。兩裝置量測所得的訊號已被驗證與傳統睡眠檢查具有高度一致性，並提供原始訊號以作為技師判讀的依據。眼罩使用兩條魔鬼氈綁帶固定於頭部，擁有高度舒適性，受試者在家中自行操作配戴。手機可安裝一個特別開發的應用程式，透過藍牙與眼罩的感應模組連接，將資料無線傳輸至手機內，該應用程式亦提供完整操作說明圖文，指引使用者操作。
本論文開發一套判讀與報告系統，提供一個特別設計的使用者操作介面，能同步顯示受試者配戴兩裝置量測的訊號，介面的功能符合技師判讀習慣，特別是判讀睡眠期與睡眠事件，如腦波覺醒事件、呼吸事件、血氧下降事件，呼吸事件又分為阻塞型呼吸中止、中樞型呼吸中止、混和型呼吸中止以及淺呼吸事件。資料的對齊呈現可以方便技師們在判讀時交互參照，避免任何睡眠指標被高估或低估，影響後續醫師診斷。系統功能包括調整心肺呼吸訊號的時間間距、移動標示對齊線、調整訊號倍率大小、跳轉至指定頁數等，都符合臨床判讀需求。技師完成判讀後，系統可以根據結果自動計算醫師臨床診斷所需的睡眠指標並產生圖表，將數值與圖表自動填入報告模板中另存新檔，包括受試者的個人資訊以及各式睡眠問卷的分數，節省操作步驟減輕技師的工作負擔。資料分析階段與診斷階段皆符合標準檢查的流程，讓受試者可以得到專業的醫療建議。
本研究成功招募8名受試者，並實際完成10次居家睡眠檢查流程。受試者包括一般正常人、已做過PSG檢查確認有睡眠呼吸障礙的患者，以及有潛在睡眠問題的人。技師使用我們開發的判讀與報告系統，按照AASM判讀標準對每筆資料進行判讀。報告結果顯示：兩位受試者的睡眠指標正常；一位受試者的睡眠潛伏期過長且睡眠效率較低；其他五位受試者有不同程度的睡眠呼吸障礙，分別為一位輕度、一位中度和三位重度。中重度受試者即為已做過PSG檢查確認有睡眠呼吸障礙的患者，其嚴重程度與PSG結果一致。
我們成功應用在本研究提出的睡眠檢查流程，整合多型態生理訊號同步紀錄，搭配專業睡眠技師的判讀與報告生成，證明其對於篩檢出睡眠問題的實用性以及判斷嚴重程度的有效性。

With the increasing prevalence of sleep problems and related disorders, the demand for sleep tests is rising. However, the capacity for PSG at hospital sleep centers is insufficient, leading to long waiting times, which may lead to delay in diagnosis and treatment for patients. Additionally, there is a limited number of professional sleep technicians who must monitor overnight and analyze the data to complete reports for physicians to diagnose and provide treatment or recommendations. Therefore, this study proposes a home sleep test procedure as an alternative or a quick screening method to relieve the pressure on hospitals. This procedure combines a sleep eye mask that can detect EEG and EOG signals with a home-based respiratory recorder and provides subjects with a smartphone for operation. This setup allows for the simultaneous measurement of brain activity and breathing conditions during sleep. The signals obtained from these two devices have been validated for high consistency with PSG and provide raw data that technicians can use for scoring. The sleep mask is secured to the head with two Velcro straps, offering high comfort, and subjects can operate and wear it themselves at home, avoiding the first-night effect caused by unfamiliar environments. The smartphone can be installed with a specially developed application that connects wirelessly via Bluetooth to the sleep mask's sensor module, transmitting the data to the phone. The application also provides comprehensive instructions with illustrations to guide users to operate.
This thesis developed a scoring and reporting system that provides a specially designed user interface for technicians to synchronize and display the signals measured by the two devices. The interface functions meet the usual practice of how technicians analyze the data, especially for scoring sleep stages and events such as EEG arousals, respiratory events, and oxygen desaturation events. Respiratory events are further classified into obstructive apnea, central apnea, mixed apnea, and hypopnea. The aligned data presentation allows technicians to cross-reference during scoring, avoiding overestimation or underestimation of any sleep indexes, which could affect subsequent diagnoses. The system features include adjusting the time interval of cardiopulmonary signals, moving alignment markers, adjusting signal magnitudes, and jumping to specified pages, all of which meet clinical scoring needs. After scoring, the system can automatically calculate the sleep indexes required for diagnosis, generate a graphic summary, and insert values and the graphic into the report template, including the subject's personal information and various sleep questionnaire scores, saving steps and reducing the workload of technicians. Both the data analysis and diagnostic phases adhere to PSG, enabling subjects to receive professional medical advice.
The study successfully recruited 8 subjects who completed a total of 10 home sleep tests. The subjects included normal individuals, patients previously diagnosed with sleep-disordered breathing, and those with potential sleep problems. Technicians used our developed scoring and reporting system to score each data according to the AASM scoring manual. The results showed that two subjects had normal sleep indexes; one subject had prolonged sleep latency and low sleep efficiency; and the remaining five subjects had varying degrees of sleep-disordered breathing, including one mild, one moderate, and three severe cases. The moderate and severe subjects were those previously confirmed to have sleep-disordered breathing, with severity consistent with PSG results.
We successfully applied the proposed sleep test procedure, integrating multi-type physiological signals synchronization, and combined it with the scoring of professional sleep technicians and report generation. This demonstrated its practicality in screening for sleep problems and effectiveness in determining their severity.

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