研究生: |
周黎恩 Chou, Li-En |
---|---|
論文名稱: |
透過單一肌電慣性感測儀器參數預測長跑運動生理指標 Prediction of Long-Distance Running Physiological Indicators Through a Single Electromyography Inertial Sensing Device Parameter |
指導教授: |
相子元
Shiang, Tzyy-Yuang 王鶴森 Wang, Ho-Seng |
口試委員: |
相子元
Shiang, Tzyy-Yuang 陳家祥 Chen, Chia-Hsiang 王鶴森 Wang, Ho-Seng |
口試日期: | 2024/05/20 |
學位類別: |
碩士 Master |
系所名稱: |
體育與運動科學系 Department of Physical Education and Sport Sciences |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 54 |
中文關鍵詞: | 穿戴式裝置 、表面肌電圖 、慣性感測器 |
英文關鍵詞: | Wearable Devices, Surface Electromyography, Inertial Measurement Unit |
研究方法: | 實驗設計法 |
DOI URL: | http://doi.org/10.6345/NTNU202401207 |
論文種類: | 學術論文 |
相關次數: | 點閱:79 下載:9 |
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過去判斷適合跑步速度的方法多以生理學參數為標準,然而這種方式時常受到環境限制,若能使用較簡便且能實地取得數據的檢測方法,則可以幫助更多運動人口得到更加豐富的資訊。目的:透過穿戴式裝置測得生物力學參數加速度、角速度和表面肌電與生理學參數氣體交換量進行比較,進而得出隨速度變化下的閾值速度。方法:實驗招募12名男性業餘跑者,於室內跑步機連續漸增負荷測驗,測驗時以攜帶式氣體分析監測儀收集分析生理訊號,以及整合式肌電慣性感測檢測儀紀錄肌肉電位和加速規的訊號,計算出生物力學指標,並比較生理學和生物力學參數閾值。結果:各項生物力學參數皆與VO2/kg呈現顯著相關,其中最大肌肉中位頻率、觸地時間、騰空時間以及著地指數與生理指標呈負相關,相關係數落在 (r = -0.819 至 -0.391) 之間,剩餘生物力學參數與生理指標呈正相關相關係數落在 (r = 0.376 ~ 0.915)。生物力學閾值速度與VT1速度皆無顯著相關,肌電閾值速度與VT2速度皆呈中度顯著相關 (r = 0.735 ~ 0.741),而運動學則是步頻、騰空時間以及著地指數閾值速度與VT2速度達顯著相關,係數落在中度相關 (r = 0.583~ 0.689),且與VT2 相關的生物力學閾值速度皆未與VT2速度達顯著差異。結論: 本次實驗的結果發現生物力學閾值可用於代替昂貴繁雜的生理檢測,提供更豐富細節的資訊給跑者與教練進行訓練的監控以及安排。
Traditional methods for determining appropriate running speeds have often relied on physiological parameters. The use of simpler testing methods could provide more information. The advancements in wearable devices enable us to perform tests in a simpler and less intrusive manner. Objective: We aimed to compare biomechanical parameters obtained from wearable devices with physiological parameters, to derive threshold under varying velocity. Methods: Twelve male amateur runners participated in incremental tests on a treadmill indoors. while signals from integrated EMG and IMU sensors were recorded to compute biomechanical indices. These indices were then compared with physiological parameters to determine biomechanical thresholds velocity. Results: All biomechanical parameters were significantly correlated with VO2/kg. MPF, Contact Time, Flight Time, and Duty Factor showed a negative correlation, with correlation coefficients ranging from moderate (r = -0.819 to -0.391). The remaining biomechanical parameters had correlation coefficients ranging from (r = 0.376 to 0.915). There was no significant correlation between biomechanical thresholds velocity and VT1 velocity. However, EMG thresholds velocity were significantly correlated with VT2 velocity, with coefficients falling in the moderate range (r = 0.735 to 0.741). The thresholds velocity for kinematic factors such as Cadence, Flight Time, and Duty Factor, were significantly correlated with VT2 velocity, with coefficients also in the moderate range (r = 0.583 to 0.689). No significant differences were found among biomechanical thresholds correlated with VT2. Conclusion: The results of this experiment suggest that biomechanical thresholds can serve as substitutes for complex physiological testing. They can also offer more detailed information for monitoring and arranging training for runners.
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