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

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.