## 5 Results and Discussion
### Statistical Analysis  
The statistical analysis of the results was performed using Statistica 13. The distribution of variables in the individual groups was verified with the Shapiro-Wilk W test and graphically assessed. The unpaired t-test and, in justified cases, its non-parametric counterpart, the Mann-Whitney U test, was used to compare the results (AUC) of two groups, i.e., those obtained from complete data and after applying the transmission control algorithm. Although the measurement cycle consisted of a series of gestures repeated three times, they were not treated as dependent samples. The aim was not to check the repeatability of the gestures performed, but to verify the impact of the applied transmission control algorithm on the shape of the obtained measurement signals. For this reason, each repetition of a specific gesture was treated as independent. Each group (individually for each of the six gestures) was verified with the two-sided Grubbs test for outliers. However, none of the values indicated by the test was removed, as the deviation in the values did not result from a measurement error, but from a specific arrangement of sensors on the hand when performing a specific gesture. For example, in the case of gesture 2 and sensor 15 or 16, the changes in values in some components may be much smaller than in the case of other sensors, due to the arrangement of these sensors. The calculated AUC value  
Figure 13: The first measurement series, consisting of six gestures (1–6) separated by the control gesture C, recorded from the sensor No. 8: (**a**) change in the values of individual components obtained from the accelerometer, (**b**) change in the values of individual components obtained from the gyroscope.  
may deviate from the other values, but should not be treated as a measurement error and removed from the data series.  
Table 6 shows the probabilities obtained for the comparison of the AUCs calculated from the signals obtained from the complete data and after applying the data transmission control algorithm. In each of the analysed cases (for each of the six gestures performed), the differences in the AUC turned out to be statistically insignificant (\(p>0.05\)).  
Tables 7 and 8 present descriptive statistics (mean, standard deviation, minimum value, maximum value, median, p\({}_{25}\)--lower quartile, p\({}_{75}\)--upper quartile, p\({}_{75}\)--p\({}_{25}\)--interquartile range) obtained from the percentage differences between the AUCs calculated from the complete data and after applying the data transmission control algorithm.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Gesture**} & \multicolumn{6}{c}{**\(p\)**} \\ \cline{2-9}  & \multicolumn{3}{c}{**Accelerometer**} & \multicolumn{3}{c}{**Gyroscope**} \\ \cline{2-9}  & **ax** & **ay** & **az** & **oux** & **avy** & **avy** & **uz** \\ \hline
1 & 0.9962 & 0.8980 & 0.9737 & 0.9620 & 0.9679 & 0.9737 \\
2  
The maximum difference between the AUCs for the accelerometer data was obtained for gesture 3 (Figure 12c) and was about 5-7%, but it was the only case in the entire series of data, none of which exceeded 4.7%. In the case of the gyroscope, also for gesture 3, in one case (only for the z component) the difference in the AUCs exceeded 5%. The mean difference in the AUCs from the entire measurement cycle, both for the data obtained from the accelerometer and the gyroscope, was about 1%. Due to the separation of individual components and the imperfect reproducibility of gestures in the next three series of repetitions, the data are varied, therefore the standard deviations (std) are comparable to the calculated mean values.