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EMG signal analysis based on fractal dimension for muscle activation detection under exercice protocol

机译:基于分形维数的肌电信号分析,用于运动协议下的肌肉激活检测

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摘要

The electromyography (EMG) reflects the electrical behavior generated by muscles movements. According the movement, muscles fibers are activated and the EMG signal reflects changes of different electromagnetic components of these fibers in time. In this paper, we describe the methodology applied for the detection of fiber muscle activation, which required the creation of digital data base with EMG signals acquired under an exercise routine designed by the authors based on Bosco Protocol. The EMG signals were obtained from different patient types divided in groups: endurance, high intensity and sedentary subjects. The measurements were done in quadriceps muscle (vastus lateralis) on isometric contraction maxim with time window of each signal of 5 secs and during Wingate test. The mathematical technique applied for the EMG signal analysis was implemented using algorithms based on fractal dimension calculation. The results allowed to observe the performance in events detection over EMG signal.
机译:肌电图(EMG)反映了肌肉运动产生的电行为。根据运动,肌纤维被激活,并且肌电信号及时反映这些纤维的不同电磁成分的变化。在本文中,我们描述了用于检测纤维肌肉激活的方法,该方法需要使用作者根据Bosco协议设计的锻炼程序使用EMG信号创建数字数据库。 EMG信号是从耐心,高强度和久坐的受试者等不同类别的患者中获得的。测量是在股四头肌(外侧输精管)上以等距收缩最大值进行的,每个信号的时间窗口为5秒,并在Wingate测试期间进行。使用基于分形维数计算的算法,实施了用于EMG信号分析的数学技术。结果允许观察EMG信号事件检测的性能。

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