# Web Applications for Teaching the Respiratory System: Content Validation
## 4 Discussion
### Anatomy and Physiology Module
#### 4.1.1 Statistical Analysis
To achieve flow, there must be a pressure difference between two points to overcome the frictional forces. Although the lung tissue's elastic properties and the rib cage's structures offer some degree of resistance, approximately 90% of the total resistance of the respiratory system is constituted by that exerted by the airways [36]. The elastic properties and their associated impedance do not represent a parameter that directly affects the airflow through the system. Tests A, B, and C in Figure 5(III) show that the model considers the losses caused by the impedance associated with the elastic and inertial load. However, according to the magnitude of the slopes of each trend (approximately zero in all cases), it is found that the changes in flow are minor as compliance increases, but greater as resistance becomes higher, which is theoretically consistent. The slope of the experimental data reflects the insignificant changes that the airflow undergoes as compliance increases, since in normal conditions, respiratory muscles easily overcome elastic resistance [29]. This airflow behavior is proved by statistically significant differences between experimental data and Tests A, B, and C.  
Individual Analysis  
The results obtained for \(\dot{V}\) and VTmax show a good level of prediction due to the similarity between medians and the non-existence of statistically significant differences between the experimental and predicted values, as shown in Figure 6. However, the equations involved in the model do not consider that the respiratory cycle can be altered by reflexes that arise in the lungs, airways, and the cardiovascular system as a result of respiratory control exerted by the nervous system [37]. This reflex mechanism against variations in mechanical parameters, the error related to the experimental data due to electromyography techniques and obstructive maneuvers for signal acquisition, and the respiratory mechanics' data variability reported in [20] all justify the errors presented in Table 4.  
In the VTmax case (see Figure 6(I)), the predicted values do not exceed the normal inspiratory capacity, which is reported around 2500 mL [1], demonstrating that the application is compatible at a physiological level. Moreover, there are no over-peaks when physiologically consistent R, C, Pmusc, and RR values are entered. Studies by [PERSON] et al. [38,39] suggest no direct relationship between respiratory rate and volume since ventilatory control respondsunder different stimuli in each case. Hence, the error is independent, as is presented in the first row of Table 4 after changes in the RR. On the other hand, the amplitude of the predicted flow presents more significant variability with tendencies to high flows than the information collected in the DB (see Figure 6(II)), as result of the increase in RR, as evidenced in Table 4. The way RR is interpreted in mathematical models defines breathing dynamics and brings critical information for breathing characterization, so the parameter must be effectively evaluated [25]. In healthy subjects, when there is a difference from the normal breathing pattern, neuronal activity is modified, and appropriate changes in ventilation occur [40] because respiratory muscles allow them under normal conditions. When an obstructive disease occurs, such as asthma, subjects respond by increasing the RR by constantly maintaining minute ventilation--and, therefore, flow (in fluid dynamics, flow is defined as the mathematical derivative of volume over time [41], to which both ventilatory parameters are related)--to maintain ventilatory demand [42]. Therefore, using a database of healthy men is a limitation for this validation. Expanding the database with obstructive subjects will show more details and allow us to support the model validation. However, when there is no significant increase in RR by the healthy subjects analyzed, the pair of experimental predicted values does not present a high error range because the closed-loop control does not intervene in the ventilatory variables.