本研究主要目的在於建立一多項式迴歸模式(Polynomial regression
model),模擬人體在不同步幅與不同跑步速度下之跑步動作,並利用身體重
心垂直振幅為指標,以探討跑者之最佳步幅.研究對象為受過長期耐力跑訓
練之男選手一人,使用Peak 動作分析系統 , 蒐集其在正常步幅,加大步幅
以及縮小步幅等跑步資料,並根據其步幅以及速度兩個變數,與跑步時身體
各關節點間已經標準化之座標值,建立一組多項式迴歸函數,用來推估跑步
週期中身體各關節點座標值隨步幅以及速度改變之變化情形,並以估計標
準誤差值(Standard error of estimate )檢驗模擬座標值與實驗座標值
之精確度.為提高本研究最佳步幅之可證性,再根據先前模擬得出之最佳步
幅,讓受試者在跑步機上跑步,求出跑者之身體重心垂直振幅實驗值,再與
先前之模擬值進行估計標準誤差考驗 .本研究結果經分析與討論後,獲至
結論如下:一.身體各肢段位置與跑步步幅.跑步速度間存有漸進互動之關
係,且每種跑步速度下均有其步幅範圍之限制 .二.本模式模擬全身總肢段
在水平方向之估計標準誤差值為4.6207公分(3.4968%);垂直方向之估計標
準誤差值為 1.3698公分(1.5814%) .三.本模式推估跑步時最佳步幅垂直
方向之估計標準誤差值在1.121公分(1.157%)至2.744公分(2.838%) 之間;
最佳步幅跑步身體重心垂直振幅之模擬值與實驗值之估計標準誤差值
為0.184公分. 基於上列之結果,本研究之結論為此多項式迴歸模式確實可
適用於跑者個別化之跑步動作模擬,提供跑者對於最佳步幅之判定,有助於
跑步動作之診斷與改善.

The purpose of this study was to establish a polynomial
regression model to simulate the motion of distance running
during the controlled conditions ofspeed and stride length.
Subsequently,the simulated values of vertical oscilla-tion of
center of gravity was utilized as a criterion to estimate the
runnersoptimal stride length.One elite distance runner was
selected as the subject ofthis study. Peak motion system was the
major equipment to collect the data. Polynomial regression
technique was used for the running modeling based on
thevariables of running speed and stride length. The standard
error of estimateexamined the difference between the
experimental data and simulated data. Afterdata calculating and
data analyzing, the following results have been reached:1.There
was a close relationship among the variables of segment
position, stri-de length, and running speed, and different
running speeds existed in the diff-erent range of the stride
length. 2.The standard error of estimate of the body position
between experimental value and simulated value was 4.62 cm
(3.50%) inhorizontal direction, and was 1.37 cm (1.58%) in
vertical direction. 3.For thecondition of the optimal stride
length, the standard error of estimate betweenexperimental value
and simulated value was found from 1.12 cm (1.16%) to 2.74cm
(2.84%), and there was 0.18 cm of standard error of estimate
between experi-mental vertical oscillation and simulated
vertical oscillation. Finally, thisstudy concluded that the
polynomial regression model could be used for the distance
running simulation individually to estimate the runners optimal
stridelength. Keywords:running model,simulation,distance
running,optimal stride length
The purpose of this study was to establish a polynomial