## 2 Materials and Methods
### Evaluation of Muscle Force  
We evaluated muscle force using the BioFET equipment dynamometer (MusTec Muscle Dynamic Technology b.v., Louis Christijnstraat 1, 1325 PC Almere, The Netherlands--Figure 1). The BioFET MusTec HD is a handheld dynamometer for evaluating muscle force [29]. It offers a powerful software package that automatically collects data. This wireless electronic device is extremely handy, ergonomic, and lightweight (250 g), provides accurate records (<1% from registered values), and displays the average and maximum force and time (in seconds). Forces can be displayed in pounds (lbs), kilos (kg), and newtons (N) in increments of 0.1 units of measurement. Its dimensions are 10 \(\times\) 7.5 \(\times\) 4.5 cm (Figure 1), and it can automatically upload measurement data onto a computer via Bluetooth and USB. We measured the muscle force for flexors and knee extensors and tested the muscle in a supine position for knee extensors and a prone position for knee flexors (see Figures 2 and 3). For the muscle group we made three measurements for both knees. The placement of the BioFET is made on the 1/3 distal side of the calf (Figures 2 and 3). We recorded maximal muscle force, medium maximal muscle force, and duration of maintained muscle force. Statistical analysis was made using the Microsoft Excel, XLSTAT software package [30]. The statistical analysis included descriptive analysis and a Jarque-Bera test (_JB test_), which gives us information about the normal distribution of parameters. A _Student's t-test_ was applied to reveal any differences between parameter values: maximal muscle force; medium maximal muscle force; duration of maintaining the maximal force for both sides, right and left, but also agonist and antagonist muscles. The test indicates whether there is a significant difference. We applied the _Student's t-test_ for equal means. For evaluation of the level of correlations between muscle parameters using BioFET and level of sleep quality and sleepiness (based on SQS and CASQ scores), we used Pearson correlation. To take into account the interactions between 2 variables of sleep and 12 variables of muscles groups, we used MANOVA statistical analysis. This analysis is available in XL STAT software [30]. For comparing the means for each variable, we used the Wilks lambda tests (1932), which is the one of the most important tests, available also in XL STAT software [30]. Figure 1: BioFET equipment. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c c c} \hline \hline Subject code & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 & 13 & 14 & 15 & 16 & 17 & 18 \\ \hline CASQ Score & 28 & 33 & 28 & 34 & 37 & 30 & 34 & 34 & 30 & 29 & 40 & 36 & 26 & 39 & 34 & 37 & 27 & 32 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Values (extreme, mean, and standard deviation) for CASQ score. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Variables** & **Min.** & **Max.** & **Mean** & **Standard Deviation** \\ \hline Scale SQS & 20 & 51 & 34.06 & 8.31 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Values (extreme, mean, and standard deviation) for SQS. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Score SQS** & **Number of Answers** & **Number of Answers (\%)** \\ \hline
20-30 & 5 & 27.78 \\
31-35 & 6 & 33.33 \\
36-40 & 4 & 4 & 22.22 \\
40-45 & 1 & 5.56 \\ \textgreater{}45 & 2 & 11.11 \\ Total & 18 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Percentile repartition according to score intervals—SQS. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Score SQS** & **Number of Answers** & **Number of Answers (\%)** \\ \hline
20-30 & 5 & 27.78 \\
31-35 & 6 & 33.33 \\
36-40 & 4 & 4 & 22.22 \\
40-45 & 1 & 5.56 \\ \textgreater{}45 & 2 & 11.11 \\ Total & 18 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Percentile repartition according to score intervals—SQS.