現代人因工作繁忙常常忽略定時運動的重要，在運動時常有人因動作的不正確，除了達不到運動的效果外，還容易受傷。為了改善這些狀況，如果有一個教練能跟在身旁，隨時給予即時、正確的指導，便可達到運動訓練的效果。現今運動訓練常利用各式各樣的方法，而本研究中採用無標記式的動作擷取設備並進行人體運動分析，於是如何讓使用者自主地進行運動訓練，了解在動作訓練過程中觀看、學習與模仿教練示範標準動作等課題便顯得十分重要。大部份前人的訓練系統著重在比較單一姿勢與預先定義好的姿勢類別是否一致，然而一段連續動作中往往包含了許多不同的姿勢，而單一姿勢無法代表整段動作；為了解決這個問題，我們的系統建議將動作訓練所組成連續的姿勢與預先定義好的動作序列進行整體的比對，先於序列中尋找兩個動作子序列的起始點與終止點，再將兩個動作子序列利用動態時軸扭曲 (dynamic time warping) 演算法比對相似度。以實際應用而言，本系統提供了教練錄製、學員訓練和學習歷程等子系統；在教練錄製方面，教練可針對學員的學習狀況錄製訓練動作；在學員訓練方面，系統會分析學員的動作是否與教練相符；最後，在學習歷程方面，可讓學員與教練檢視與評估過去訓練的狀況。

The modern people often ignore the importance of establishing an exercise routine. With possibly incorrect actions during exercise, not only the fitness goal is not reached, but also people may be injured. In view of this, an accompanying trainer who provides real-time and appropriate guidance is necessary. On the other hand, there are already various approaches in place that support sport training. In this work, we utilize a markerless device for motion capture and then conduct subsequent human motion analysis. Note that several previous studies focus on the comparison of a single posture to evaluate the correctness of a trainee’s movements. However, a workout program is usually a motion sequence containing different postures. A single posture is not enough to be representative. We thus propose to utilize both the LCS (longest common subsequences) and the DTW (dynamic time warping) algorithms for matching whole sequences. A prototype system is also implemented, in which a user can imitate the postures as demonstrated by the trainer. Specifically, our prototype system provides functionalities of trainer recording, student training, and history reviewing. Consequently, a trainer can record different exercises for specific users whereas a trainee can perform workouts and review his or her own exercise histories.

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