**5. Conclusions**

We concluded that, although exist many orientations and recommendations to use and apply the electromyography method, sometimes these components can be a path too complex to understand and to respect with closed eyes. In a considerable perspective of study we were able to show with a model of exercise in high intensity, which was capable to produce a lot of noises and variations on the signal, that different methods of process to achieve the muscular activity do not change the final result if used the complete signal or just the burst parts, or still using all sequence of treatment with filtration, rectification and smoothing in many combinations of analyses. Moreover, should be noted that only filtration was sufficient to improve the quality of EMG signal, making us think in keeping the use at least the filtration in electromyography analyses, still this procedure is used to at least maintain the signal inside the muscle activity range, so, it should not be took out just because no significant differences were founded, we have to consider all the process, as said before, like the devices used and the investigator experience. These outcomes show us that we have remained with a critical knowledge to many things and test the main recommendations to use some techniques. In order to make those results clearer and give us more confidence when use the treatments in EMG analyzes. Some studies creating different noises in computer should be made. This way we can be more secure about the removing of noises, securing that the absence of difference is not because a good pre-acquisition was made, securing not enough noises to be cut.

These results and conclusion takes in consideration only cyclic exercise with the intensity used in the studies. Exercises such as isometric or acyclic have different signal waves and so, could have different results to the same treatments. Also, exercises with lower load could change mainly the results in the Burst + Silence (Second Study) results, once that a task such as 10 km in low intensity, would be realized with less intense movements, creating not only different power signals but also different silence and burst time duration.

Still, a more accuracy statistic method could be used, such as The Smallest Worthwhile Change [23], capable to find minimal and almost invisible differences between different methods, that can contribute with good perspective to sports domain when obscure changes exist among several techniques to data process in EMG analysis and if we use a classical statistic we may not identify with probabilities these modulations.
