## 4 Discussion  
It is widely known that the use of mechanical ventilation is a treatment that causes complications when used for prolonged periods, increasing patient mortality [40]. The work of breathing (WOB) is an accepted index to know the state of the ventilatory mechanics and respiratory muscles, nevertheless, the monitoring of WOB during spontaneous ventilation is not easy to perform [10]. This pilot study seeks to estimate the WOB in both restrictive and obstructive situations, taking advantage of its relationship with the respiratory muscle activity. Indexes from respiratory muscle sEMG signals were used to classify each one of the muscular patterns (restrictive and obstructive maneuvers) and each one of the levels of WOB. Three indexes from the frequency domain, FC, RHL of the sternocleidomastoid and coherence (C) between the diaphragm and the accessory muscles discriminated the patterns between restrictive and obstructive (see Table 3). The FC and RHL of the sternocleidomastoid were higher in the restrictive pattern than in the obstructive one, which indicates that the activity of the sternocleidomastoid is located in the high frequency band, therefore, it has a high activity [17; 21]. The coherence between the diaphragm and any accessory muscles makes it possible to infer the level of engagement of the  
Figure 7: Real work of breathing (WOBr) compared with the estimated work of breathing (WOBe) in each one of the groups. The linear regression analysis is presented. involved accessory muscle, the sternocleidomastoid in the restrictive case. On the contrary, in the obstructive case, the muscle that supports the ventilatory process is the intercostal muscle, as observed in the coherence value between the diaphragm and intercostal, which is higher in this pattern than in the restrictive one. Concerning WOB classification, two of the calculated indexes presented a statistically significant contribution to discriminate the samples: the amplitude and the coherence (see Table 4). The median of the maximum amplitude of sEMG signals of the diaphragm increased with increments in work of breathing in both experiments, confirming that this is the principal muscle in the ventilation process. A differentiated pattern was found related to the accessory muscle activity, the more significant accessory muscle for the restrictive maneuver (E1) was the intercostal muscle (maximum amplitude of sEMG) and in the case of the obstructive maneuver (E2), the significant changes were due to the sternocleidomastoid muscle. For the same reason, the coherence between the diaphragm and the intercostal increased in E1 and decreased in E2. The findings show that during the ventilatory process of a subject with a restrictive pattern, the muscles with permanent activation are the diaphragm as the main muscle and the sternocleidomastoid as the accessory muscle engaged. However, as the work of breathing increases, there is also an increase in the intercostal muscle activity. Conversely, in a subject with an obstructive pattern, where the muscles are permanently activated are the diaphragm and the intercostal, but when the work of breathing increases, the muscle that showed increments was the sternocleidomastoid. To identify the muscular pattern between restrictive or obstructive, the best technique was the KNN, obtaining an accuracy of 91%. Meanwhile, to identify the level of work of breathing, LDA, SVM and KNN showed accuracies lower than 60%. Combining the properties of some of these classifiers, the accuracy reached is lower than 80%. However, the neural network was the algorithm with the greatest accuracy, achieving a mean of 89% for the all dataset (see Table 5). It should be noted that the accuracy of the classification of WOB level depends on the real WOB (WOBr), and this was calculated from values of compliance, resistance, and muscular pressure, obtained with an occlusion maneuver and optimization algorithms, thus WOBr may have an estimation error [28; 29].