前言：無氧閾值速度 (velocity at anaerobic threshold, VAT) 對長跑運動而言是一項重要的
參數，它與耐力型競賽表現有著高度相關。然而，少有研究以生物力學的角度，針對跑
者達到無氧閾值時的動作機轉進行探討。目的:探討生物力學參數隨速度的變化轉折點
與無氧閾值速度的關聯。方法：招募 15 名男性業餘跑者，進行跑步機速度漸增測試，
並以氣體分析儀量測受試者的無氧閾值速度。同時在跑者身體四個位置(雙腿脛骨、薦椎
以及胸椎)配戴慣性感測器，分別量測軀幹旋轉角速度、質心垂直加速度、騰空時間、觸
地時間、步頻以及脛骨加速度峰值等運動學參數。透過 D-max 數學模型計算各項參數隨
速度變化下的轉折點，進而得到該運動學參數的轉折點速度(Velocity at Biomechanical
Deflection Point, VDBP)。接著以皮爾森積差相關觀察各 VDBP 與 VAT)的相關性，最後以逐
步迴歸分析法得出迴歸方程式以估計無氧閾值速度。結果：除質心垂直加速度峰值轉折
點速度之外，其餘參數皆與 VAT呈中度相關(r = .54~.66)，而逐步迴歸分析所得出的推估
方程式為: VAT = -11.282+0.75*軀幹旋轉旋轉角速度峰值轉折點速度+1.113*脛骨加速度
峰值轉折點速度 (R2 = 0.67, r = .85, bias ±1.95 SD = ±2.22 km/hr，結論:跑者的 VBDP 可反
映 VAT 的優劣，且透過多項參數進行逐步迴歸分析，對比於單一 VBDP ,能更好地解釋與
推估 VAT，提升未來應用於提升跑者表現的可能性。

Background: Velocity at anaerobic threshold VAT is an important parameter for long-distance
running, which is highly correlated with endurance competition performance. However, few
studies have explored the running mechanism of runners when they reach the anaerobic
threshold from the perspective of biomechanics. Purpose: To explore the relationship
between biomechanical deflection point and anaerobic threshold velocity. Method: Fifteen
male amateur runners were recruited to perform an incremental speed test. VAT were measured
by gas analysis system. 4 Inertial Measurement Units IMUs were placed on the runner's
body(both shank、sacrum and thoracic spine), in order to measure Angular Velocity of Thorax
Rotation AVTR, Trunk Vertical Acceleration TVA, Flight Time FT, Contact Time CT, Cadance
CAD, and Peak Tibial Acceleration PTA respectively. DMAX method were used to calculate the
velocity at biomechanical deflection point VDBP. The correlation between VAT and VBDP were
analysed through Pearson correlation coefficient(r). Stepwise regression analysis was used to
build the regression equation in order to predict VAT. Result: Except for VACOM- VBDP , all other
VBDP were moderately correlated with VAT (r = .55~.66), and the estimation equation obtained
by stepwise regression analysis was: VAT=-11.282+0.75*VAVTR-DP + 1.113*VPTA-DP , correlation:
r=.85, error: ±2.22km/hr. Conclusion: VBDP can reflect VAT, and through the stepwise
regression analysis, it could more accurately estimate VAT compare to a single VBDP, which also
iii
enhance future possibility of application, in order to improve the performence of distance
runners .

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