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震動訓練對股四頭肌最大肌力預測之影響

The Effects of Vibration Training on One-Repetition Maximum Quadriceps Strength Prediction

摘要


目的:本研究目的探討震動訓練對於最大肌力之立即性效益。方法:以30名大學男性為研究參與者,利用股四頭伸腿機(PL-2000, Paramount, USA)量測股四頭肌的最大肌力(1 repetition maximum, 1RM)。以80%1RM測量反覆次數(repetitions to fatigue, RTF)來估算出1RM。間隔48小時後,以震動訓練介入熱身活動中再RTF測量。最後將所得RTF帶入預估公式中,計算1RM預估值。統計分析以級內相關考驗信賴度,並以相依樣本單因子變異數分析考驗震動訓練前、後預估值與實際量測1RM之差異性。結果:研究結果顯示,受試者重複1RM之ICC值達0.998。震動訓練前之預估值與實際1RM間達顯著的差異,而震動訓練後則無。結論:透過本研究結果可知,於熱身階段中介入以震動訓練,能夠有效的提升RTF次數,進一步能夠提高預估公式的準確性。

關鍵字

熱身 預估公式 準確性

並列摘要


Purpose: The purpose of this study was to investigate the immediate effects of vibration training on one-repetition maximum quadriceps strength prediction. Methods: Thirty college male volunteers were recruited in this study. The subjects were required to perform the actual one-repetition maximum (actual-1RM) quadriceps strength by using leg extension machine (PL-2000, Paramount, USA). Forty-eight hour later, the 80% 1RM used to perform repetitions to fatigue (RTF) as pre-test. And then, the subjects applied vibration training during warm up and implemented 80% 1RM RTF as post-test after 48 hours. The results of pre-test and post-test were respectively applied into the predicting formulas to find out the predict-1RM. Data reliability was measured using the intra-class correlation coefficient (ICC). A repeated measures analysis of variance (ANOVA) was used to determine the difference among pre-test, post-test and actual-1RM performances. Results: The results showed that the reliability tests for 1RM variables produced highly intra-class correlation coefficients of 0.998. The predict-1RMs of pre-test were significantly smaller than the actual-1RMs and predict-1RMs of post-test and there were not significant difference between the actual-1RMs and predict-1RMs of post-test. Conclusions: The results of this study demonstrated that the RTF could be ameliorated by using vibration training during warm up, and which also improve the accuracy of prediction equations.

並列關鍵字

Warm up Prediction Equations Accuracy

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