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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/82128


    Title: 運用於睡眠安全監控與睡眠品質優化之人工智慧整合系統( I );Artificial Intelligent Integration System Applied on Sleeping Safety Monitoring and Quality Optimization( I )
    Authors: 陳健章;周百謙
    Contributors: 國立中央大學生醫科學與工程學系
    Keywords: 睡眠;睡眠監測;銀髮族;嬰幼兒;呼吸中止;呼吸衰竭指數;阻塞性飽和指數;寢具;感測器;人工智慧;溫度辨識;姿態辨識;聲紋辨識;機械視覺;Sleep;Sleep Monitoring;Senior Citizen;Infants;Apnea;Respiratory Desaturation Index;Obstruction Desaturation Index;Bedding;Sensors;Artificial Intelligence;Temperature Identification;Gesture Recognition;Voiceprint Recognition;Mechanical Vision
    Date: 2020-01-13
    Issue Date: 2020-01-13 14:16:46 (UTC+8)
    Publisher: 科技部
    Abstract: 睡眠為現代人最重要的恢復時刻,然而諸多文明困擾亦造成整體睡眠效率與品質下降。為緩解睡眠不佳造成之風險,銀髮族及長照族群、嬰幼兒、呼吸中止症候群,以及醫療照護高風險者等族群,都應該透過相關睡眠生理訊號與物理訊號監控達成睡眠品質優化。遂本計畫提出以非侵入型或非接觸型之睡眠生理與物理多重訊號監測以及相關之品質優化方法。採取以生理與物理訊號輔以人工智慧方法調節睡眠環境之干擾因子,紓解相關夜間呼吸中止問題,以期改善使用者睡眠品質。有鑑於睡眠是種與外界環境有高度連動性的動態性變化,本計畫規劃使用人工智慧方法即時整合睡眠安全監控裝置,除可協助找出現場環境影響睡眠效率的因素,更進一步分析相關個體表現型、動態化分析並介入整合相關微環境調控,優化睡眠相關設定與微環境以期有效改善睡眠品質與效率。因此可提供最佳的睡眠策略以提高使用者的睡眠舒適性,從而改善其睡眠品質與睡眠效率達到增加使用者之使用意願。本計畫產品的進階功能,可使用於老年人、亞健康族群、年幼使用者,以及醫療院所夜間高風險照護等族群,預期如以此人工智慧系統針對部分特殊族群以及醫院醫療高風險族群持續監控,將可減少專業人力需求,並建立預警系統,同時提升照護安全與照護水準。簡言之,本計畫之重要性在於能透過人工智慧感測融合技術之發展,結合睡眠姿態辨識、鼾聲聲紋分析、室內微環境偵測調控系統、氧氣飽和度偵測與溫度分析系統,抑或擴增偵測選項,以尋找潛在的睡眠問題並輔助優化調整相關睡眠環境之配置。同時偵測高風險族群之臨床使用變化,在人力節省前提下,有效達成居家安全及醫療安全的雙重目的。本計畫合作廠商為歐得葆家具有限公司,是獲得經濟部工業局輔導的第一家綠色家具公司且擁有全台灣最大的家具工廠。歐得葆公司具有寢具以及相關睡眠輔助之產品設計、研發以及製造之能力。因此在實務應用上,得以實現雲端評估服務以及各項寢具加值服務,進而提供寢具使用前後之效益檢測分析,提供個使用者客觀的評估報告;而本研發團隊則能受惠於感測功能的精進與更貼近使用者經驗的最佳化設計。亦能針對睡眠障礙患者所開發之系統即時監測分析,能利於與醫療院所之睡眠分析實驗室整合,開發出睡眠機制與檢測之高性能監測環境。在協作廠商相互配合之下,能更有效地將實驗室技術帶入業界的場景當中,並能以貼近使用者端的思考模式改善感測器佈局以及使用方式。 ;The proposal suggests a methodology to construct an artificial intelligence integration system for sleep safety monitoring and sleep quality optimization. By extracting data features from physical sensors, the employed method can be used for monitoring the real-time posture changes from seniors, infants, and people who are suffering sleep apnea. The data extracted from thermal sensors will be used for real-time face temperature detection and face tracking. The data will be further combined with the analog signals extracted from ultrasonic sensors for posture recognition. Frequent change of postures will trigger a sensor hub to subsequently switch on a dehumidifier, an air conditioner, or an air purifier based on the physical parameters collected and the posture patterns interpreted. Therefore, the proposed method is suitable for optimizing the sleep environment and monitoring the posture change of seniors and infants for the purpose of sleeping safety. For people affected by sleep apnea, the proposed method can also monitor and record the changes of face temperature and posture during sleep. The voiceprints of snoring will be also recorded simultaneously and the corresponding analog signals will be used to analyze the snoring patterns during sleep. In a nutshell, the proposal suggests an artificial intelligent sensing fusion technology by combining sleep posture recognition, snoring voice analysis, indoor micro-environment detection and control system, oxygen saturation detection, and temperature analysis system for the purpose of detecting potential sleep problems and optimizing the configuration of the relevant sleep environment. Under the premise of manpower saving, the proposal can effectively achieve sleep safety both in the home and the medical settings. The project partner, Oderbau Furniture Co., Ltd., is the first green furniture company with the largest factory in Taiwan. Oderbau is one of the best manufactures of bedding supplies with its own product design and R&D team. Therefore, Oderbau is a perfect partner to realize the inevitable cloud evaluation services and various bedding value-added services. They can use the system to generate objective evaluation reports for their users and marketing supports. The R&D team can also be benefited from the improved sensing capabilities to refine the future design that is closer to the user experience by the feedback of Oderbau company. The system can be used for real-time monitoring of patients with sleep disorders. It can also be integrated with the sleep analysis laboratories of medical institutions to develop a high-performance monitoring environment for sleep mechanism and detection. By collaborating with Oderbau, the technologies developed in the laboratory can be brought into the business setting more efficiently, and the sensor layout and usage can be improved by introducing the perspectives of users.
    Relation: 財團法人國家實驗研究院科技政策研究與資訊中心
    Appears in Collections:[生醫科學與工程學系] 研究計畫

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