標題: 利用Kinect 分析步態型態與疾病的相關性Analysis of the Correlation between Disease and Gait using Kinect 作者: 王蕙菱Wang, Huei-Ling荊宇泰Ching, Yu-Tai資訊科學與工程研究所 關鍵字: 疾病;步態;腦中風;運動學參數;左右對稱;Disease;Gait;CVA;Kinematic parameters;Symmetry 公開日期: 2015 摘要: 一般要分析步態，需要多台攝影機重不同角度去做拍攝。架設環境複雜以及貼反光球可能因為肢體動作所以造成遮蔽的情況。本論文是利用Kinect不必貼光球即可以擷取骨架資訊以及不需要多重角度去拍攝的特性，去分析正常人步態與病人步態的左右側肢的差別。 實驗分為兩部分，坐下站起以及朝 Kinect 方向正常走路。利用Kinect 擷取身上20個關節點座標，計算其角度、速度、…等運動學參數以及步伐差、…等。繪出曲線以和時間的關係去做左右側肢的比較。正常步態受測者為學生平均年齡28.2±6.2，共4名男性，1名女性。病人為台大醫院新竹分院腦中風病患，平均年齡61.88±13.12，共6名男性，2名女性。正常受測者數據曲線一致性很高。而病人的曲線會有一側較為平滑不規則。Usually ,to analyze the gait we need to use multiple camera to take photograph from different position. May happened with the complexity of setting up the environment or the action may cover the reflective balls. In this study we use Kinect to solve the upper problem, and to analyze the difference between the left and right limbs of normal gait and gait with disease. Experiments have two part. Sit , stand and walk .Use Kinect to capture the 20 major joint coordinate points of human body. Calculate the kinematic parameters like angle , velocity, etc., and step length, etc. Also, draw the cure with the time to compare the left and right limbs difference. The average age of subjects with Normal gait are 28.2±6.2,with total 4 male and 1female, and all are students. The average age of patients are 61.88±13.12, with 6 male and 2 female, and all are CVA patients form NTUH Hsin-Chu Branch. The curve of normal gait are high consistency. But the patients have one side limbs with abnormal curve. URI: http://140.113.39.130/cdrfb3/record/nctu/#GT070256029http://hdl.handle.net/11536/126981 Appears in Collections: Thesis