研究生: |
張斯閔 Chang, Ssu-Min |
---|---|
論文名稱: |
利用晃動程度判斷騎乘技術 Determining riding technique by using swaying |
指導教授: |
相子元
Shiang, Tzyy-Yuang |
學位類別: |
碩士 Master |
系所名稱: |
運動競技學系 Department of Athletic Performance |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 中文 |
論文頁數: | 57 |
中文關鍵詞: | 自行車 、晃動 、胎壓 、慣性感測器 、踩踏頻率 |
英文關鍵詞: | Bicycle, swaying, tire pressure, IMU, cadence |
DOI URL: | http://doi.org/10.6345/NTNU202001446 |
論文種類: | 學術論文 |
相關次數: | 點閱:140 下載:20 |
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前言:驅動自行車的方式是透過雙腳交替踩踏,力量藉由傳動系統經過輪組傳至地面,由於踩踏循環是雙腳交替進行,因此也會對人車系統造成左右方向的晃動;騎乘時的晃動增加會提高輪組的滾動阻力,且騎乘者必須消耗更多能量以維持平衡。已有研究證實菁英自行車選手騎乘時晃動程度較低,但是否能夠利用晃動程度判斷騎乘技術尚未出現完整的討論。目的:本研究希望釐清是否能夠利用騎乘時的晃動程度判斷騎乘技術。方法:招募14位受試者,其中包含6位選手與8位非選手;實驗共有兩種騎乘環境,分別為室內開放式滾筒訓練台與室外柏油路面進行四種不同踩踏頻率(70、80、90、100 rpm)的騎乘;利用慣性感測器與胎壓感測器收取騎乘過程中角速度、加速度與胎壓變化訊號,利用紅外線攝影機訊號收取室內騎乘時的左右偏移;並分別計算出不同晃動指標。以獨立樣本T檢定比較選手與非選手間室內紅外線攝影機反光點晃動程度的差異;以二因子混合設計變異數分析比較選手與非選手、室內與室外陀螺儀、加速規以及胎壓變化的差異。結果:紅外線攝影機方面,只有在最低踏頻(70 rpm)選手與非選手達顯著差異;陀螺儀X軸在四種踏頻下皆出現交互作用,在室內騎乘非選手晃動程度顯著高於選手,室外方面兩者並無顯著差異;胎壓變化方面,四種踏頻皆無交互作用,但選手與非選手間達顯著差異,非選手顯著高於選手,室內與室外也達顯著差異,室外顯著高於室內。結論:在判斷晃動程度上,陀螺儀與胎壓變化是一項可以參考的指標,同時本研究也發現,其餘參數與陀螺儀也有相同的趨勢,因此在實際應用上,利用多項參數以獲得更加精確的晃動程度指標,是未來可以深入探討的方向。
Bike riding are through bilateral pedaling movement and transfer the pedaling power to the ground through transmission system and wheel. The bike-and-rider system sways right and left due to the bilateral pedaling movement of both legs. The sway increased the rolling resistance between the wheel and ground, therefore rider required more energy to maintain riding balance. Previous studies have shown that elite cyclists have lower swaying during bike riding. However, using swaying to determine the riding technique has not been complete investigated. Object: The aim of this study was to clarify whether the sway during riding can be used to judge riding technology. Methods: Fourteen participants were recruited, including 6 athletes and 8 non-athletes. There were two riding environments in the experiment: indoor roller training and outdoor asphalt road. The IMU sensor and tire pressure sensor were used to collect the angular velocity, acceleration and tire pressure during the riding with four different cadences (70, 80, 90, 100 rpm). The infrared camera signal was used to detect bike medial-lateral sway during indoor riding. Sway index was calculated by the variation of IMU signal and tire pressure as well as the infrared camera. Independent sample T-test was used to analyze the difference between the infrared camera sway index of athletes and non-athletes. For IMU and tire pressure sway index, two-way ANOVA was used to analyze the difference between athletes and non-athletes as well as indoor and outdoor riding. Results: For infrared camera sway index, there was significant difference between athletes and non-athletes at 70 rpm cadence. There was significant interaction between riding level and environment for X axis gyroscope at all cadences. The sway index of non-athlete is significantly higher than the athlete for indoor riding, while there was no significant difference for outdoor riding. There was no significant interaction between riding level and environment for tire pressure at all cadences. The sway index of non-athlete is significantly higher than the athlete, and the sway index of outdoor riding is significantly higher than the indoor riding. Conclusion: Both gyroscope and tire pressure are suitable approach to determine the riding sway. This study found out that other parameters such as acceleration also show similar trend as the gyroscope and tire pressure. Therefore, obtaining more accurate sway index by using multiple parameters in practical applications should be thoroughly investigated in the future.
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