## 3 Experimental Scenario
### Statistical Analysis
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Variable** & **Minimum** & **Q1** & **Q2** & **Q3** & **Maximum** & **IQR** & **Skewness** & **Kurtosis** \\ \hline Upper Arm Length (UAL) (cm) & 28 & 31 & 33 & 35 & 38 & 4 & 0.09 & 2.18 \\ Lower Arm Length (LAL) (cm) & 22 & 25 & 26 & 27 & 30 & 2 & 0.06 & 2.67 \\ Upper Leg Length (ULL) (cm) & 44 & 48 & 53 & 54 & 63 & 6 & 0.27 & 2.74 \\ Lower Leg Length (LLL) (cm) & 37 & 40.5 & 43 & 45 & 51 & 4.5 & 0.33 & 2.27 \\ Mid-upper Arm Circumference (MUAC) (cm) & 23 & 28 & 30 & 32 & 37 & 4 & 0.04 & 2.62 \\ Lower Arm Circumference (LAC) (cm) & 22 & 25 & 27 & 28 & 33 & 3 & 0.42 & 2.98 \\ Thigh Circumference (TC) (cm) & 35 & 39 & 41 & 44 & 50 & 5 & 0.25 & 2.97 \\ Muscle Mass (MM) (kg) & 34 & 44.5 & 57.2 & 61.6 & 77.8 & 17 & –0.18 & 2.10 \\ Bone Mass (BM) (kg) & 1.9 & 2.4 & 3 & 3.22 & 4 & 0.8 & –0.20 & 2.02 \\ Body Fat Mass (BFM) (\%) & 5.8 & 16.6 & 23.9 & 29.7 & 42.2 & 13 & 0.095 & 2.67 \\ Body Fat Mass of Arm (BFMA) (\%) & 5.1 & 14.9 & 20.4 & 30.2 & 45.4 & 15.3 & 0.302 & 2.33 \\ Body Fat Mass of Leg (BFML) (\%) & 6.2 & 13.4 & 19.6 & 30.6 & 45.3 & 17.1 & 0.434 & 2.12 \\ Muscle Mass of Arm (MMMA) (kg) & 1.4 & 2.1 & 3.2 & 3.7 & 4.5 & 1.6 & –0.38 & 1.89 \\ Muscle Mass of Leg (MM) (kg) & 6 & 7.6 & 10.2 & 11.1 & 13.6 & 3.5 & –0.27 & 1.97 \\ Body Mass Index (BMI) (kg/m\({}^{2}\)) & 19.7 & 22.2 & 23.8 & 28.5 & 33.1 & 6.3 & 0.514 & 2.12 \\ Total Body Water (TBW) (\%) & 43.5 & 51.7 & 55.4 & 59.5 & 67.6 & 7.7 & 0.115 & 2.59 \\ Visceral Fat Level (VFL) & 1 & 1.75 & 4 & 7 & 13 & 5.2 & 0.807 & 2.65 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Descriptive statistics of anthropometric and body composition variables. possible to identify three main datasets: with weak correlation \((0.5\geq r>0)\), with moderate correlation \((0.5>r>0.8)\) and with strong correlation \((r\geq 0.8)\). In conclusion, the following relationships are established from the standpoint of the correlation:  
* The variables, lower arm circumference (LAC) and mid-upper arm circumference (MUAC), show a strong correlation between them; we call these Group 1. * The variables, body fat mass of arm (BFMA), body fat mass (BFM) and total body water (TBW), show a strong correlation between them; we call these Group 2. * The variables, bone mass (BM), muscle mass (MM) and muscle mass of arm (MMA), show a strong correlation between them; we call these Group 3. The same statistical analysis was applied for variables related to Link 2. From the results, it is possible to identify two groups of variables strongly correlated amongst each other: Group I, which includes the muscle mass (MM), bone mass (BM) and muscle mass of leg (MML), and Group II, which includes the body fat mass of leg (BFML), body fat mass (BFM) and total body water. Finally, from the groups of correlated variables that were found, a multivariate analysis was used for explaining the relationships between these and the RSSI as the link quality metric. For this analysis, the highest correlation with the measured RSSI value was used as the selection criteria, and from these results, a set of three and five preliminary variables for each one of the link models was selected. In summary, from this complete and experimental knowledge and understanding of the behavior of the on-body channel under various scenarios, we are able to describe the effect of several parameters quantitatively on the effectivity of two different transmission power control schemes.