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  • 學位論文

以LMA為基之人體動作因子權值分析

Weight Factors in Human Movement Analysis-Based on LMA

指導教授 : 方鄒昭聰
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摘要


數位內容產業的產業規模與產值隨著時間而與日俱增,亞太地區為成長速度最快同時也是全球第三大市場。台灣的數位內容產業仍有很大的成長空間。數位內容是將各類素材經過處理後,將資料轉化成數位化格式並賦予新的應用型態;以健康和運動領域來看,透過數位化技術將資料進一步處理,可以用來研究降低人體傷害以及傷害後的復健過程。 本研究以拉邦動作分析(LMA)理論為基礎,並將研究範圍鎖定在時間分類的研究分析,將運動學參數的計算方法以單位時間(Frame)計算,目的在於透過時間的變化來觀察參數的變化,以改進過去在位移、速度、加速度、角度變化量、角速度、角加速度在計算上僅利用開始與結束進行分析而容易忽略掉動作中的細微資訊的缺點,計算後將資料展現透過統計的方法擷取動作特性參數,以RDP 平滑化演算法技術檢測多個門檻值,再利用統計分類樹的方法找出最適合的門檻值,並找到適合時間分類的動作特性參數,進行各肢段各質地的動作因子決策準則以及值域的解析,將分析結果儲存入本研究所設計的動作質地資料庫中,並提供一套框架程序,供後人可以繼續建構完整的動作質地資料庫,或運用動作質地資料庫操作出特定肢段特定質地的動作。

並列摘要


The scale and output value of digital content industries are steadily on the increase. And digital content industries still has a very big growth space in Taiwan. Digital content includes a lot of material information that will be processed into digital format and give new types of applications. By the medical service and movement domain, further process will be done by the digitizing technology the material. Afterwards, it may be used to study how to reduce the bodily harm as well as the injury recovery process. In this study, based on the LMA(Laban Movement Analysis) theory , the scope of the study focuses on time analysis of the kinematics parameters by the unit interval/unit time (frame) computation. The purpose of the analysis is to observe the changes of the parameters by time change, to improve the displacement, the velocity, the acceleration, the angular variation, the angular velocity, the angular acceleration in the computation only used in the beginning and end times. After material computation, it then penetrates the statistical methods to pick up some movement characteristic parameters. We applied RDP smoothing algorithm to detect the threshold values, used statistical classification tree method to identify the most appropriate threshold and to find the movement characteristic parameters with suitable time classification. We then carried the analytical process on the decision-making criteria and domain value of movement factors to respective body parts/efforts, and the analytical results were stored into the movement effort database, which could be used to generate the digitized movement with specific efforts on some specific body parts. We also designed a framework for future generations to build the complete movement effort database.

參考文獻


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