**3.2. Influence of the burst and silence in treatment of EMG signal (Second Study)**

Computational Intelligence in Electromyography Analysis – 106 A Perspective on Current Applications and Future Challenges

**Figure 8.** Electrode position used; SENIAM recommendations [12].

MA, USA).

exhaustion.

and 110% of MWL.

The relation of rejection common mode was >95dB and the limits of entrance of established signal in ± 5 mV. The reference electrode was positioned in the right elbow (lateral epicondyle). To capture and process the signal was used the software AcqKnowledge 3.8.1™ (BIOPAC Systems®, USA) and the software MatLab 7.0 (Mathworks®, South Natick,

The EMG signal was treated to obtain the RMS (root mean square) values in time windows with five seconds in the first minute of the test in different intensities. The first twenty seconds of each signal were discarded with the intention to avoid possible inertial influences. After that, it was used proceedings recommended to exclude artifacts and noises from EMG signal, divided in conditions: raw (R), Filtration (F), Filtration + smoothing (FS), filtration + smoothing + rectification (FSR). The filtration was done using a pass-band digital filter Butterworth with frequencies of 20 and 500 Hz. The smoothing process was done through a mobile mean with three points. The process of rectification was done considering all signals, without discards of negative part. The table 1 present the mean values of the load used in the constant load test in 80, 100 and 110% of MWL and the respective times to

Condition **Load (W) Time (s) CLT80%** 212.6 ± 23.5a 1070.0 ± 250.5a **CLT100%** 268.5 ± 33.6b 282.3 ± 75.5b **CLT110%** 301.5 ± 31.7c 110.3 ± 22.3c

**Table 1.** Loads and times to exhaustion (mean and standard deviation) on constant load tests in 80, 100

Note: different letters show significant differences between loads and times to exhaustion, (*P*<0.05).

To test the possibility of bursts get in the way of an EMG signal and change the final outcome, we used a similar method, assessing 27 healthy students (14 men, age = 28,2 ± 2,7 years and 13 women, age = 23,2 ± 2,7 years). The test proposed was the Wingate supramaximal test (WST) used with a purpose to reach a higher intensity in exercise matched with a short duration. The index of performance was defined in a software (WINGATE TEST®, CEFISE, BRASIL) to determine the power by each second during the test, beyond the relative peak power (RPP) (W.kg-1), relative mean power (RMP) (W.kg-1), fatigue index (FI) (%) and the peak power instant (PPI). The figure 9 represents the second study protocol.

**Figure 9.** Illustrative representation of second study protocol, involving burst analyze.

The protocol consisted of 4 minutes warm-up in a mechanic cycle ergometer to lower limbs (MONARK 324E, SWEDEN) with 50 W load, with a pedal cadence in 70 rpm and the beginning of each minute the subjects realized a sprint during 6 seconds. After warm-up, the subjects rest for two minutes and they began the test, with a 0,075 kg.kg-1 load until finish the test in 30 seconds. The same muscles were analyzed with the same EMG protocol and the same equipment's and procedures in the previous study. However, for this study in addition to the RMS also analyzed spectral parameters. To spectral analyses or frequency domain, was obtained the parameters from median frequency (MF), variance and slope, those values were determined using Wavelet Daubechies db4 (DWT) [6,8]. Was considered the analyses of EMG signal in the contraction phase (bursts) and during all signal (bursts + silence).


The table 2 present a descriptive analyze referent of subject performance.

Note: relative peak power (RPP), relative mean power (RMP), and fatigue index (FI).

**Table 2.** Mean values ± standard deviation of subject performance.
