在動作學習的領域中，一般需有專家在旁指導，學習者才有辦法知道自己的動作是否正確，而在電腦科技日新月異的今日，已可以透過感測器，擷取人體各肢段的資料出來分析。 本研究結合舞蹈學上的拉邦動作分析，將感測器抓取出來的數據進行分析學習者動作質地的特性，為了達到即時性分析，我們提出一個時間複雜度為O(n)的演算法，Triangle Area Smoothed (TAS) 演算法進行質地波形圖的平滑化，並藉由動作中的突然(sudden)、綿延(sustain)質地，分析學習者的動作行為模式，最後結合專家的指導術語，建立一個動作指導系統，提供學習者可以自我學習的環境。 In the motion learning domain, there is an expert to analyze the learner motion, to help learner to know whether his movement is correct or not. By the modern science and technology, we can analyze the motion of each body region by sensors. Our research is based on the Laban Movement Analysis (LMA) of dance, and we analyze the data from several different sensors. According to the data, we can examine learners’ motion characters and effort. For the real time analysis, we proposed a Triangle Area Smoothed (TAS) algorithm to smooth curve, which time complexity is O(n). We use the sudden and sustain effort to analyze learners’ motion and integrate expert’s guiding language to construct the guiding language system. In this way, we could provide an environment for learners who can learn by themselves.
