老人居家照護是近來愈趨重視的議題，過去ㄧ直以來主要著重在老人生理狀態的偵測及相關居家醫療儀器的研究，但除了生理上訊號所顯現的不適之外，尚有其它的問題困擾著老人的生活。對於在老人身上所產生的許多不適，最直接的就是反映在老人的情緒上，若是能針對老人目前所處的環境狀態分析出造成老人情緒狀態轉變的因素，將有助於提升老人的生活品質。本研究所採用的替換調適模式之案例式推理，有別於一般案例式推理的應用，一般案例式推理需要對於應用領域的知識有相當了解才能達到有效地案例調適，因此在發展案例式推理的應用時，需要經過相當長的資訊收集，而替換調適模式運用一些已經存在的案例，從中萃取出案例間的關聯性，並藉由案例的不斷累積來自動化的調適案例庫中的知識，因此將使得推理的結果更符合老人過去的生活習性，因此能針對老人的情緒狀態找出形成的因素，而找出改變情緒的形成因素之後，將有機會的進一步解決老人目前所遭遇的生活難題，最終本研究期望能藉此達成提升老人生活品質的目的。

e-Care for aging has become an increasingly important research topic in recent years. Most research focus on the detection of Physiological state or the study of the e-Care medical devices. Nevertheless, there are still other problems tormenting an aging’s life besides physiological discomfort detected from physiological signals. For instance, it is often the case that the discomfort comes from the aging's atypical mood status. In other words, causes behind the change of the aging’s mood status would help improve the quality of the aging’s life. Accordingly, this paper presents a substitution-based case adaptation CBR to analyze the causes of effecting the change of the aging’s mood status. Substitution-based case adaptation CBR differs from general CBR in lean adaptation knowledge required. Most existing CBR systems rely on an enormous amount of built-in adaptation knowledge in the form of adaptation rules (that require a deep analysis of the domain). Substitution-based case adaptation can make use of a limited number of cases to extract the relations between the cases and reach automatic adaptation. With the accumulation of cases in the case library, the result of inference fit in line with the habit of the aging’s life would be improved based on this automatic adaptation. The contribution of our method aims at reaching the e-Care goal of improving the aging’s life quality from the mental perspective.

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