# Analysis of Surface EMG Parameters in the Overhead Deep Squat Performance
## 2 Materials and Methods
### Investigated Parameters Description  
#### 2.2.1 Maximum Voluntary Contraction  
Maximum voluntary contraction (MVC) was determined for each muscle under consideration using sEMG signals recorded during deep squat. Then, MVC values were normalized to obtain the %MVC parameters. The MVC normalization process divided MVC by the maximum voluntary isometric contraction. To determine MVC, an extra normalization sEMG signal was recorded for each considered muscle and subject involved in the experiment, before the deep squat performance. The participants were asked to generate a maximum voluntary isometric contraction for about 5 s, and this activity was repeated two times. The main advantage of MVC normalization, pointed out in the literature [7], is the fact that such normalization rescales the sEMG data and expresses them as a percentage of a reference value unique and standardized for all participants in the study. Such approaches eliminate any varying influence of local signal recording conditions, allowing a direct quantitative comparison of sEMG findings between subjects. In line with [7], \"Group statistics and normative data can be developed and statistically, be verified.\" Determining the value of muscle excitation (ME) and MVC requires processing the sEMG signals, which involves removing artifacts by appropriate signal filtering and smoothing, for example, using a method based on the root mean square (RMS) calculation. Details regarding sEMG signal processing and determination of ME, MVC, and %MVC values are widely presented in the literature [5; 23; 24; 25; 26]. In this work, to determine muscle excitation and maximum voluntary contraction, we used the method we proposed and described in the previous papers [27; 28]. This method consists of the following main stages: filtering the raw sEMG signal, removing the impulse interference, calculating the envelope of sEMG, and the MVC determining process. The sEMG processing pipeline is shown in Figure 4. In the next two paragraphs, we present some details of our method. \begin{table}
\begin{tabular}{c l c c} \hline
**Criteria** & **Description** & **Answer** & **Score** \\ \hline Q1 & Upper torso is parallel with the tibia or towards vertical & Yes/No & 1/0 \\ Q2 & The femur is below the horizontal & Yes/No & 1/0 \\ Q3 & The knees are aligned over the feet & Yes/No & 1/0 \\ Q4 & The dowel is aligned over the feet & Yes/No & 1/0 \\ Q5 & The arms are an extension of the torso & Yes/No & 1/0 \\ Q6 & The heels are in contact with the ground & Yes/No & 1/0 \\ Q7 & Correctly performed squat with the base under the heels & Yes/No & 1/0 \\ Q8 & Occurrence of pain & Yes/No & 0/1 \\ Q9 & Limited mobility of the shoulder girdle and thoracic spine & Yes/No & 0/1 \\ Q10 & Impaired functioning of the muscles performing the abduction & & \\  & movement in the hip joint, especially the middle gluteal muscles & Yes/No & 0/1 \\ Q11 & Increased tension, lack of flexibility of the adductor muscles & Yes/No & 0/1 \\ Q12 & Limitation of ankle joint mobility in dorsal flexion & Yes/No & 0/1 \\ Q13 & Disturbance of transfer of the center of gravity & & \\  & in favor of one of the sides & Yes/No & 0/1 \\ \hline \end{tabular}
\end{table} 
Table 1: Description of the scoring criteria used for the overhead deep squat, a component of the Functional Movement Screen (FMS). Surface EMG Filtering and Enveloping  
The sEMG signal was filtered by two digital finite impulse response filters (FIR): the band stop 852-order filter to attenuate the main interference (50 Hz) and the bandpass filter from 10 to 250 Hz (cascaded connection of 266-order high-pass and 5-order low-pass filters with 60 dB attenuation). The frequency characteristics of the used filters are shown in Figure 5.  
The impulse interference was removed by the moving average [29; 30] hole filter (MAHF) [27]. MAHF calculates a 7-bin histogram in a moving window (1) of 80 ms length (\(M\)\(W\)L) containing the absolute value of sEMG samples.