## 2 Materials and Methods
### Data Processing  
The kinematic from the spinal angles and the AP and ML CoP displacement and velocity were extracted from Qualisys Motion Capture Software 2021.2 from Qualisys AB\({}^{\circledR}\), Gothenburg, Sweden, and then managed and analyzed via Microsoft Excel. Before data extraction, all markers from each participant were identified, labeled, and filtered with a 4 th order Butterworth filter of 6 Hz with the smoothing tool from Qualisys software as recommended by their manual to reduce high-frequency marker noise [42; 47; 48]. Data from the angles of the head (LOM-TRG), cervical spine (TRG-C7), thoracic spine (T1-T3; T11-L1), lumbar spine (T11-L1; L4-S2), and sacral tilt (L4-S2) in the sagittal plane were extracted along with data from the position of the 3-MCF and the force plates. A 2 nd order Butterworth filter of 20 Hz using AcqKnowledge\({}^{\circledR}\) (Version 3.9.0) was applied only in the channels related to the AP and ML CoP data to reduce high-frequency noises. The FRT was divided into three phases: the reach phase, the maintenance phase, and the return phase. The onset of the reach phase (T0) was identified as the instant when the signal value from the 3-MCF position along the \(x\)-axis reached a value higher than 5% of the maximum value obtained during the task above the baseline. The end of the phase was defined as the instant of the maximum value of the 3-MCF trajectory. The maintenance phase consisted of a 5-s hold at the maximum reach position. The beginning of the return phase was defined as the instant when the signal value from the 3-MCF position along the \(x\)-axis reached a value lower than 5% of the maximum value. The end of this phase was defined as the instant when the shoulder had returned to a 90\({}^{\circ}\) flexion angle, and the trajectory had returned to its minimum value and initial position (Figure 3). The electromyographic data were analyzed using AcqKnowledge(r) (Version 3.9.0), Python (Version 3.12.4), and Microsoft Excel. The sEMG signal was submitted to a band-pass 2 nd order Butterworth digital filter of 20-450 Hz to remove electrical noise and electrode movement. If the signal exhibited cardiac activity, the digital filters applied were 50-450 Hz. Thereafter, the root mean square (RMS) was calculated with a sliding window of 100 samples [24; 44; 49]. The mean of the three maximum peaks of the voluntary isometric contraction was used as a reference to normalize the test values as described in Table 2. A five-second isometric contraction was performed for each with a one-minute rest period between each repetition [35; 50]. To automate data processing, a script was developed to apply the filtering and the RMS to all the electromyographic data. In the pilot study, the data extracted from the script were compared with the data analyzed using AcqKnowledge to verify the accuracy of the extraction process and ensure that the system functioned correctly. This comparison was conducted to confirm the consistency of the extracted data with the manual analysis performed in AcqKnowledge. For each extracted file, Visual Basic for Applications (VBA) in Microsoft Excel was used to automatically calculate various metrics related to the FRT. The means of the amplitude range for each angular segment, 3-MCF distance traveled, and the AP and ML CoP displacement were calculated with the following formula [51]:  
Amplitude range = Maximum Value - Minimum Value  
The mean velocity of the CoP in both AP and ML directions was calculated using the following formula [52]:  
\[\text{Mean CoP Velocity}\left(\text{AP or ML}\right)=\frac{1}{\text{n}-1}\sum_{i= 1}^{\text{n}-1}\frac{\left|\Delta\text{CoPi}\right|}{\Delta\text{ti}} \tag{5}\]  
This parameter was obtained by dividing the sum of the absolute variations in the CoP displacement (\(\Delta\text{CoPi}\)) at each time interval (Ati) by the total number of samples, where n  
Figure 3: Phases of the FRT are illustrated by a Qualisys plot. represents the total number of samples collected.