摘要
臺灣邁入高齡化社會之際，高齡者健康照護日益受到重視。為節省醫療成本、有效率地及早發覺疾病，遠距居家健康監測與照護服務逐漸在世界各地推展。藉由日常居家長期、持續性的健康監測，可紀錄無法在短時間內察覺的疾病與生理機能退化徵兆。在遠距居家健康監測與照護服務中，營運機構儲存、分析以及監控照護對象之生理訊號資料。若每筆資料均需透過醫護人員逐一審視、判斷，營運機構人力成本將居高不下，且人為審視判斷易因疏忽而有遺漏或判斷錯誤等狀況發生。因此本研究建置以「生理訊號關鍵指標」與「健康照護演算法」為主體之專家系統，協助「遠距居家健康監測與照護服務」營運機構進行異常判讀。異常發生時，專家系統將會主動警示，醫護人員進而迅速與照護對象進行聯繫與處理，以期及時掌握異常情形。本研究可節省營運機構運作人力、減少人為判斷所導致之疏忽、遺漏或誤判等情形，加速異常情形判讀，以掌握時效，並能累積醫護人員之專業知識，使專家系統與演算法日益完整。
並列摘要
Taiwan is changing into an aged society. The issue of elder health care is more and more important. In order to save the medical cost and find diseases efficiently, the home telehealth monitoring and health care is spread in the world. By the long-term and continuously health monitoring, diseases and degeneration signs can be recorded. In the service of home telehealth, the operator was store, analyze and monitor vital sign data from care targets. If health care workers need to view and check each record, the human cost will be huge. Human is always making some mistakes when viewing and checking vital sign data. This research is focuses on building an expert system based on critical values and algorithms of vital sign to help the operator find the abnormal status. If the abnormal status occurs, the expert system will alert health care workers actively, and they can call target and do some further dealings. The research purpose is expected to reduce the human cost of operator, human mistakes, and accelerate the checking of abnormal status. The expert system can accumulate the domain knowledge of doctors and health care workers; let the expert system and algorithms are more and more completed.
參考文獻
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