在精神障礙就業輔導體系中,精神障礙者無法在戶外單獨行動,常常需要別人的幫助,但是因為就業輔導員人力缺乏,無法同一時間照料所有身心障礙者。而精神障礙者常會因為情緒問題在上班途中離開,造成就輔員的困擾,就輔員往往要花費更多的時間在找尋身心障礙者,造成人力資源的耗損。為了解決精神障礙就業輔導體系勞力密集的問題,本篇論文提出以輔具科技來幫助就輔員與身心障礙者的家人,結合手持裝置及全球定位系統,建立即時偵測走失系統。在系統中,我們將所有的移動軌跡做預處理,由原本的位置點變為一連串相連的矩形(稱為BOX),然後將學員的即時軌跡當作輸入,與事先蒐集的常模路徑做比對,而比對的值是根據軌跡的BOX重疊面積的權重而來。最後,透過就業輔導員的篩選,總共找尋六位精神障礙或與認知障礙相關的學員,將系統應用於實際的實驗。
Because individuals with mental impairments are frequently dependent on others for support across environments, strategies and skills must be introduced that directly lead to access of those supports. To relieve their job coaches from labor-intensive aids with traveling to work, a PDA is carried by the individual who has cognitive impairments. The PDA enables individuals to respond to unexpected situations such as being lost by effectively using the handheld device to alert themselves or call for assistance in the support system. In this paper, we build a real-time deviation detection system and conduct field experiments in community-based settings for individuals with cognitive impairments. We study real-time anomaly detection in a context that considers user trajectories as input and tries to identify anomaly for users following normal routes such as taking public transportation from the workplace to home or vice versa. Trajectories are modeled as a discrete-time series of axis-parallel constraints (“boxes”) in the 2D space. The incremental comparison between the current movement pattern and the norms which are previously constructed user transportation routines can be calculated according to the weight of overlapping area. Finally, the proposed system was implemented and evaluated with six individuals with cognitive impairments.