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  • 學位論文

穿戴裝置在運動期間的即時肌肉疲勞監測

A Wearable Device for Monitoring Muscle Fatigue in Real Time during Exercise

指導教授 : 劉省宏
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摘要


近年來隨著可穿戴裝置的普及化,該設備已廣泛應用於醫療保健領域或監測運動過程中的身體狀況,如運動帶和智慧錶帶。開發可穿戴設備必須克服三個問題。第一個問題是功率消耗,第二個問題是微控制器的數位信號處理時間,第三個問題是靜態隨機存取記憶體空間分配。在這項研究中,目標是開發一種肌電圖裝置,可以在任何的肌肉上佩戴,以便在運動時可以即時檢測肌肉狀況。肌電圖的中位數頻率可以代表肌肉疲勞狀況,為了對肌電圖信號進行去噪,在微控器上使用經驗模態分解方法,並設計了一個三電極電路來測量肌電圖。有20名參與者騎多功能滑步機兩次。我們比較了由微控制器即時計算的肌電圖信號的中值頻率值與離線的個人電腦計算的中值頻率值。第一次和第二次的整體平均均方根誤差分別為2.86±0.84Hz和2.56±0.47Hz。因此本研究中所設計的肌電圖裝置可用於即時監測運動時肌肉狀況。

並列摘要


In recent years, with the popularization of wearable devices, the device has been widely used in the field of health care or for monitoring the physical condition during exercise, like as the sport band and watch. There are three issues that must be overcome when developing wearable devices. First problem is the power consumption, the second problem is the time of digital signal processing, and the third problem is the static random access memory (SRAM) space allocation on the microcontroller unit (MCU). In this study, the goal is to develop an electromyography (EMG) patch which could be worn on any used muscle to detect its condition in real time when exercising. The median frequency of EMG signal has been used to assess the muscle fatigue condition. In order to alleviate the artifact noise in the EMG signal, the empirical mode decomposition (EMD) method was used on the MCU system. A three electrodes circuit was designed to measure the EMG. There were 20 participators to ride the multifunctional elliptical training machine twice. We compared the median frequency values of EMG signal calculated by the MCU in the real time and by the personal computer in the off line. The averaged root mean square differences were 2.86±0.84 Hz and 2.56±0.47 Hz for the first and second times, respectively. Therefore, the EMG patch designed in this study may be applied to monitor the muscle fatigue condition when exercising.

參考文獻


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