量化全身性運動協調之工具－主成份分析

The Method for Quantifying Whole Body Movement coordination-principal Component Analysis

10.6222/pej.3804.200512.0904

陳秀惠(Hsiu-Hui Chen)

動力系統 ； 運動學習 ； 多肢段協調 ； 主成份分析 ； dynamical system ； motor learning ； multiple segments coordination ； principal component analysis

體育學報

38卷4期（2005 / 12 / 01）

39 - 52

繁體中文

目的：主要目的在檢驗以主成份分析法來簡化全身性運動協調的眾多維度資料之可行性，另一個研究重點是探討分析結果所反映出的肢段協調情形。方法：收集受試對象學習踩板車技能時全身15個肢段的三維座標資料進行分析。結果：主成份分析使得原本45維的變項簡化成三至五個，第一和第二主成份所代表的變異量由學習初期的58.30和21.27變為77.95和9.1。此外，成份分數呈現了主要的動作型態，而成份係數則進一步的描述肢段間的協調情形。結論：主成份分析法對於複雜肢段協調過程的量化來說，是一個可行的分析方式。

Purpose: The purposes of this study were to testify the validity of using principal component analysis (PCA) for decreasing high-dimensional data sets of whole body movement and to investigate the coordination of multiple segments described by the PCA. Methods: 3 dimension coordinates of 15 segments over whole body during learning the pedalo task were collected for analyzing. Results: The results showed that the 45 dimensions were decreased to less than 5 components. The percentage of variance accounted changed from 58.30 to 77.95 for first component and changed from 21.27 to 9.1 for second component. In addition, the factor scores projected the real movement patterns and the coefficients of factors revealed the coordination of segments. Conclusion: PCA was verified as an effective method to quantify the coordination of complex movement.

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