## 3 Experimental Scenario  
We followed a similar experimental methodology to [6], but we extended the sample to a group of 37 people distributed between 13 women and 24 men, aged from 20 to 50 years. This large population sample presents different physical characteristics associated with gender and age. Thus, from the onset of puberty to menopause, women maintain a greater body fat mass percentage than men, despite smaller energy intake per kg lean mass [15], and evidence indicates that estrogens contribute to the gender differences in fat mass and the gestational changes in body composition [16]. Moreover, we should not forget that with age, body fat increases and fat-free mass decreases because of the loss of skeletal muscle; hence, the mean body fat of a 20-year-old man weighing 80 kg is 15% compared to 29% in a 75-year-old man of the same weight [17].  
For every person, we took anthropometric measurements and body composition values. These parameters, shown in Figure 1, were selected because they are directly related to the locations of the nodes and the links of interest. The measurements of body composition were acquired using the Tanita tetrapolar foot-to-foot bioelectrical impedance analyzer, Model BC-601 [18]. These body composition parameters include: fat mass, muscle mass, bone mass, body mass index, total body water and the levels of body fat percentage and muscle mass of each segment (right/left arm and right/left leg). Body composition and anthropometric parameters allow one to describe the human sample accurately and their expected impact on the radio transmission.  
In our experiments, we use the sensor nodes, Shimmer [19]. The Shimmer node is equipped with an ultra-low-power 16-bit microcontroller (TI MSP430), 10 KB of RAM and 48 KB of Flash. This platform includes an IEEE 802.15.4-compliant CC2420 transceiver, which has a sensitivity threshold of \(-94\) dBm and eight programmable power transmission levels from 0 dBm to \(-25\) dBm with a current consumption of 17.4 mA to 8.5 mA, respectively [20]. FreeRTOS has been ported as the real-time operating system in this platform.  
The nodes were placed on the subjects' bodies, describing a star topology, with the coordinator placed at the waist (just over the navel) and the node sensors at the right arm (Link L1) and at the right knee (Link L2), as shown in Figure 1. We took measurements of RSSI and the packet error rate (PER); these measurements were gathered for every subject, and these were repeated at every transmission power level available in the radio. All of the results were taken in controlled indoor conditions, under the ground level, to minimize the effect of electromagnetic interference (EMI) (WiFi, 3G, solar radiation, _etc_).  
We planned two experimental scenarios to investigate the temporal variations in the quality of two different links in stationary positions:  
* Scenario 1: the subject sat in a chair and performed five movements of the arms (Link 1): (1) hands on thighs, denoted as L1/P1; (2) arms crossed, L1/P2; (3) arms extended forward, L1/P3; (4) arms extended up, L1/P4; and (5) arms extended to both sides, L1/P5.
* Scenario 2: the subject sat in a chair and performed four movements of the legs (Link 2): (1) leg at a 90 degree angle with the body, L2/P1; (2) right leg crossed over the left knee, L2/P2; (3) left leg crossed over right knee, L2/P3; and (4) leg extended forward, L2/P4.  
As a result, the largest and most complete database (to the author's knowledge) of human channel characterization is built after this experimental work. The univariate analysis of the data has been used in the first descriptive stage of research to know in depth the nature and the meaning, separately, for each one of the variables. Subsequently the study was continued by doing a bivariate analysis to understand how two or more variables relate. Finally, a multivariate analysis was used for explaining the relationships between the variables and RSSI as the link quality metric.