## 2 Methods
### Results  
Descriptive demographic data are shown in Table 1. Studied variables were non-parametrically distributed. The analysis of intra-session reliability values for the initial session are shown in Table 2. The average walking point value was 3.933 \(\pm\) 1.371 with a mean ICC of 0.885 (0.82-0.925) and a SEM value of 0.465. The highest ICC value was obtained for the step width variable (mean ICC of 0.908 (0.872-0.936) and a SEM of 0.196) and the lowest ICC value was obtained for walking point gap (mean ICC of 0.758 (0.670-0.829) and a SEM of 0.091). For all the studied variables, the ICC achieved strong values (i.e., almost perfect). Table 2 shows the VN for all the variables.  
\begin{table}
\begin{tabular}{c c} \hline \hline  & _Total (n = 87)_ & _CI_ \\  & _Mean SD (95\% CI)_ & \\ \hline _Age (Years)_ & 27.5 \(\pm\) 1.79 (27.1–27.9) & \\ _Weight (Kg)_ & 64.9 \(\pm\) 9.9 (62.8–66.9) & \\ _Height (cm)_ & 168.5 \(\pm\) 5.2 (167.4–169.6) & 95\% \\ _BMI_ & 22.7 \(\pm\) 2.66 (22.2–23.3) & \\ _Foot Size (UE Size)_ & 39.8 \(\pm\) 2.29 (39.4–40.3) & \\ \hline \hline \end{tabular} Abbreviations: BMI: body mass index; CI: confidence interval; SD: standard deviation.  
\end{table}
Table 1: Descriptive demographic values for total sample.  
The analysis of the intra-session reliability values for the second trial is shown in Table 3. The mean walking point value was \(4.075\pm 1.201\) with a mean ICC of 0.861 (0.803-0.904) and a SEM value of 0.448. The highest ICC value was again obtained for step width (mean ICC of 0.903 (0.868-0.932) with a SEM of 0.170) and the lowest ICC value was for walking point gap (mean ICC of 0.668 (0.547-0.765) and a SEM of 0.118). For all the studied variables, the ICC achieved strong values (i.e., almost perfect). The VN for the walking points, walking point gap, step width, and walking base variables are shown in Table 3.  
The analysis of the inter-session reliability data is presented in Table 4. The highest ICC value was obtained for  
clinical activities (such as clinical treatment or orthopedic devices, e.g., insoles) and their modifications along the treatment intervention.  
In our research, all the subjects were barefoot. Shoes could modify the studied variables due to different characteristics, such as drop or shore value.  
A key goal in this observational study was to obtain a baseline for the four studied variables in order to detect different data caused by pathologies. The developed trials for the participants in this research did not cause fatigue. On the other hand, a greater number of measurements may achieve higher reliability values.  
We checked an uninjured population in order to achieve the reliability for the four variables of walking point, walking point gap, step width, and walking base, which are deeply related to the gait measurement variables analyzed by the OptoGait system.  
The SEM values for all four datasets in this trial were very low, suggesting that these data are strong enough to use in the clinical assessment of changes before and after interventions like physical therapy, orthotics devices, or therapeutic exercise interventions. In addition, the OptoGait device seems useful for measuring differences between different participant groups. SEM is defined as a quantitative measurement of the errors that could happen when a participant repeats certain tests; in our trial, the obtained intra-session SEM values were very low, showing a strong absolute reliability.  
Our results are close to those reported by previous studies [1; 2; 3; 9; 14]. The obtained data may help future clinicians to achieve adequate clinical assessments regarding gait and posture modifications that are due to factors beyond the errors associated with the normal variability of measurements between trials.