# Prediction of Lower Leg Swelling in Driving Posture
## 3 Result and Discussion  
### Relationship Between BI and Thigh Pressure Distribution  
Figure 6 shows the changes in the average BI of all the participants at the three tilt angles (upper, normal, and lower); BI increases with time at all tilt angles and increases as the tilt angle is increased. The participants with the smallest tilt portion had four sensor areas further from the tilt fulcrum. Therefore, in this experiment, four sensor areas were selected as the tilted portions, and the average pressure in these areas was \(P_{t}\). The relationship between \(P_{t}\) and the tilt angle is shown in Figure 7. The correlation coefficient between \(P_{t}\) and the tilt angle was 0.727, indicating a stronger correlation. Figure 8 shows a scatterplot of the relationship between \(P_{t}\) and BI after 90 min for all the participants; a weak positive correlation (\(r=0.481\)) was noted between \(P_{t}\) and BI after 90 min for all the participants. Figure 4: Placement of measurement equipment and actual image of the experiment. Figure 5: The experimental protocol. Figure 8: Relationship between BI at 90 min and \(P_{t}\) for all participants. Figure 6: BI changes over time. Figure 7: Relationship between BI and tilt angle. Dots (i)-(iv) in Figure 8 likely resulted from differences in the physiological states among the three experiments. Body impedance is influenced by factors such as the participant's physical condition, fatigue state, meals, measurement time, and posture immediately before measurement [33]. Dots (i)-(iv) were excluded because their initial impedance differed from the other two experiments, indicating insufficient control at the start of the experiment. Observation (iv) was measured during menstruation. [PERSON] et al. (1998) reported that impedance increased approximately 1 week before menstruation, peaked during menstruation, and decreased within a week [33]. Observations (v)-(vi) were derived from one participant (N13). Her data showed a higher BI at 90 min compared to other participants. Participant N13 regularly engaged in sports involving heavy loads on the lower leg. Such activity is known to increase the risk of developing medial tibial stress syndrome (MTSS). MTSS, in turn, is associated with the progression of lower leg swelling [34; 35; 36]. Therefore, it is likely that N13's higher BI was influenced by her physical condition. Accordingly, in the following discussion, observations (i)-(vi) were excluded. The correlation coefficient between BI and \(P_{t}\) at 90 min after eliminating observations (i)-(vi) was 0.525. Construction of Prediction Equations for Lower Leg Swelling Relationship Between BI and Thigh Pressure Distribution  
Previous studies have revealed the correlations of lower leg impedance with time, height, body fat percentage, and thigh pressure [15; 24]. Therefore, the BI after t min was selected as the dependent variable, while sitting time (\(t\)), pressure in the tilt portion (\(P_{t}\)), participants' height (\(h\)), and body fat percentage (\(f\)) were used as the independent variables. The results of the multiple regression analysis (forward-backward stepwise selection method) for the males, the females, and all the participants are listed in Table 2. All variables were chosen as valid variables. The adjusted \(R^{2}\) values for the prediction equations for the males, the females, and all the participants were 0.561, 0.512, and 0.551, respectively.