使用無線感測技術檢測和分析意外傷害及身障大學生的腹直肌訓練成效

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Thesis > Item 987654321/102600

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Title:	使用無線感測技術檢測和分析意外傷害及身障大學生的腹直肌訓練成效
Other Titles:	Using wireless sensor technology to detect and analyze the effect of rectus abdominis muscle training on accident and disabilities college students
Authors:	蔡明蒼;Tsai, Ming-Tsang
Contributors:	淡江大學資訊工程學系碩士班陳瑞發;Chen, Jui-Fa
Keywords:	生物感測元件;腹直肌訓練;無線感測網路;資料探勘;決策樹;Biological sensor;Rectus abdominis muscle training;Wireless sensor networks;data mining;Decision tree
Date:	2014
Issue Date:	2015-05-04 09:59:47 (UTC+8)
Abstract:	透過生物感測元件在醫療領域的應用，人體動作分析與行為感知技術已成為醫療與健康照護之發展趨勢。為了提供學生良好的體育學習環境，台灣各大學對於身障生以及因意外傷害致行動不便的學生皆有加開特殊體育課程，訂定訓練計畫以提供正確有效的運動方式與內容，並檢視其訓練成效。本研究核心為一即時腹直肌訓練測量評估系統之研製，利用無線感測技術，針對腹直肌訓練器材佈建感測元件，收集學生在訓練中肌肉施力的詳細數據，透過程式開發工具做整理和分析，即時反映給同學供檢視訓練動作是否正確，而老師除了在現場指導同學動作外，亦可根據量化資料，檢測和分析學生的腹直肌訓練成效。本研究目標為:(1)運用無線感測技術，測量與收集訓練詳細數據(2)訓練數據正確性分析，即時回饋(3)結合資料探勘，進行決策樹分析。本研究的技術核心，除依據體育老師所訂定之動作標準予以系統化，使訓練狀況達到自動化監測功能外，著重在即時性測量運動狀態下的腹直肌施力狀況，評估人體的運動姿勢狀態與施力正確度，並結合資料庫以追蹤每位受訓者各階段訓練紀錄，設計出客觀的腹直肌訓練測量系統，再利用圖型的使用者介面設計，使測量系統具有能夠自我診斷功能與友善的人機介面，根據所收集到的使用者復健數據，進行資料探勘，以決策樹演算法分析影響復健成效之關鍵因子，回饋供體育老師規劃訓練課程與未來受訓者使用。 Through the application of biological sensor in the medical field, human motion analysis and behavior-aware technology has become the development trend of medical and health care. In order to provide students with a good sports learning environment for accident and disabilities college students in Taiwan universities, arranged special sport lessons, set an effective training program to provide the correct movement pattern and content, and view their training effectiveness. The core of this research is to develop a real-time rectus training evaluated system The key elements of this study are threefold: (1) Use wireless sensor technology, to measure and collect detailed training data. (2) Analyze training data, real-time feedback (3) Data mining, decision tree analysis. Focusing on the real-time measurement of the rectus abdominis training, design graphical user interface, so that training can be self- diagnostic. Based on the collected training data, use decision tree algorithm to analyze the impact the effectiveness of training key factors. Contribute to the future training.
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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