增進並維持工作能力對於身心障礙者就業是非常重要的一環，而認知障礙者的就業率又是所有身心障礙者中最低的，相對的對於就業輔導的需求即是最高，因此本研究為幫助認知障礙者提昇職業工作能力，設計了一套智慧型的工作提醒系統，幫助認知障礙者減輕因認知缺損而工作成效不章的影響。現行工作提醒的方式大多以紙本為主，無法克服當工作場域進行轉換後，認知障礙者必須將新場域和新工作內容重新連結的記憶負擔，與如何針對個人化的工作內容設計提醒此兩項重要課題。智慧型認知障礙者工作提醒系統結合數位個人助理與藍牙定位，為認知障礙者建置具有情境感知能力之輔助科技；認知障礙者可以透過輔具的聲音、影像、圖片、文字等多種模式來加強工作上的產能，彌補因認知障礙造成的記憶力、組織、自我管理上的缺損。為驗證系統成效，亦對智慧型認知障礙者工作提醒系統進行多方面測試實驗與修正，結果發現到如果工作提醒輔具具有情境感知的能力，將能夠賦予使用者直覺化的即時、即地提醒與更佳的使用成效。

A challenge to individuals with cognitive impairments in workplaces is how to remain engaged, recall task routines, and transition autonomously across tasks in a way relying on limited cognitive capacity. A novel task prompting system is presented with an aim to increase workplace and life independence for people with traumatic brain injury, cerebral
palsy, intellectual disability, schizophrenia, and Down syndromes. This paper describes an approach to providing distributed cognition support of work engagement for persons with cognitive disabilities. The unique strength of the system is the ability to provide unique-to
the-user prompts that are triggered by context. As this population is very sensitive to issues of abstraction (e.g. icons) and presents the designer with the need to tailor prompts to a ‘universe-of-one’ the use of picture or verbal cues specific to each user and context is implemented. The key to the approach is to spread the context awareness across the system, with the context being flagged by beacon sources and the appropriate response being evoked by displaying the appropriate task prompting cues indexed by the intersection of specific end-user and context ID embedded in the beacons. By separating the context trigger from the pictorial or verbal response, responses can be updated independently of the rest of the installed system, and a single beacon source can trigger multiple responses in the PDA depending on the end-user and their specific tasks. A prototype is built and tested in field experiments involving eight individuals with cognitive impairments. The experimental results show the task load of the human-device interface is low or very low and the capabilities of helping with task engagement are high and reliable.