本研究開發之太極八法自動化評量系統，經過中國醫藥大學修習中醫養生學之學 員 112 名測試，與 1 名太極拳專家評斷後，利用 ROC 曲線進行分析，計算出各動作之 最佳分數切點，以及其 AUC 值、敏感度、特異度與正確率，以此分數做為區分學員各 太極動作屬於待加強或及格兩種分類，大致上都有很好的表現，能判定出各動作之好 壞。
但仍有部分側面與背面動作之 AUC 值、敏感度、特異度與正確率有偏低的狀況，
由於在這些動作時 Kinect 感應器無法準確捕捉肢體重疊時之人體骨架關節資料，因此 未來將與專家討論在這些動作時之分析重點，該著重於哪些部位的評分，使系統在評 量這些動作時能更加精確，也預計在側面架設另一之 Kinect 感應器，由正面的 Kinect 感應器與側面的 Kinect 感應器同時拍攝，能更加全面的抓取各動作之人體關節角度資 料，避免肢體重疊導致評判錯誤的情況發生。而在切點分數方面大部分都在 80 分以 上，顯示系統評量方面較專家更為嚴格，後續也將與專家討論，如何調整切點分數偏 高之動作方面的配分比例與解決方法，讓專家與系統的分數更為一至，也使太極八法 自動化評量系統更加精確與完善。
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