*4.3. Spirometric Feedback in Ventilation Maneuvers during Cardiopulmonary Resuscitation Training*

Comparing measurements performed with the Laerdal® manikin simultaneously with the system of this study, the latter presents a superior performance when compared to the first one, besides a smaller experimental error, according to Table 6. The Laerdal® model is limited to measures below 1000 <sup>×</sup> 10−<sup>6</sup> m3, and this work is limited to measures below 1800 <sup>×</sup> 10−<sup>6</sup> m3, therefore, it caters to all devices used in rescue ventilations. Moreover, only when the Laerdal® indicates <sup>≤</sup> <sup>400</sup> <sup>×</sup> <sup>10</sup>−<sup>6</sup> m3, the values are experimentally equal, but below or above this value, there are divergences between the measurements. The Laerdal® model performs indirect measurements of air volume entering the lung based on chest position, which causes errors when the volume is far from 400 <sup>×</sup> <sup>10</sup>−<sup>6</sup> m3. On the other hand, the sensor of this work performs the direct measurement of the air volume, which is much more accurate compared to this kind of indirect measurement.

**Laerdal**® **(**×**10**−**<sup>6</sup> <sup>m</sup>3) Indicators This Work (**×**10**−**<sup>6</sup> m3)** 0 Off 196 ± 2 Orange 215 ± 2 Orange 282 ± 2 Orange 328 ± 3 Orange 373 ± 3 ≤400 ± 60 Orange 419 ± 3 >400 ± 60 Green 557 ± 4

≤600 ± 90 Green 851 ± 6 >600 ± 90 Red 1096 ± 2

Green 663 ± 5

**Table 6.** Simultaneous measurements of the Laerdal® and YF-S201 sensors.

Comparing the measurements provided by the YF-S201 sensor and the Koko spirometer (Table 5), we observed that the results are experimentally equivalent. Therefore, the YF-S201 achieves the objective of measuring air volume entering the lung of CPR dummies in respiratory maneuvers providing spirometric results. As stated before, the incorporation of sensors such as those presented in [1,2,4,19,27–41] is not feasible for this purpose due to, mainly, its high cost.

Another advantage is the simplicity with which measurements are performed, functioning as a noninvasive method that characterizes the ventilation maneuver. The fact that techniques and sensors presented in [1–24] require advanced techniques also make their application on dummies unfeasible, due to their complexity and, again, because they have a high cost. Therefore, the alternative presented in this manuscript is attractive for the proposed application because it adds spirometric feedback to ventilation practices in medical simulators using a low-cost sensor that is accord to the application requirements.

The main advantage of the prepared mechanism lies in its cost-effectiveness, the direct measurement of the air entering the lung, and the measurements of spirometric parameters during CPR training. Furthermore, we expect to generate feedback to the users, in future works, as expiration charts based on spirometric models, to bring more realism to the simulations, and innumerable debriefing possibilities.

The spirometric parameters, especially the FVC, along with the graphs generated for debriefing, will allow the student to perform an ideal ventilation maneuver during CPR because the system shows the amount of air that entered the lung and its spirometric input profile from the graphical analysis of the smoothness of the curve. For a more rigid control of the parameters, it is still possible to require time intervals considering the FEVt and to make indirect inference of the airflow using the mean FEV parameter.

### **5. Conclusions**

In this work, a sensor was adapted to measure the amount of air supplied to the lungs during ventilation in cardiopulmonary resuscitation (CPR) maneuvers. The calibration and validation of the sensor achieved results that address the CPR requirements. In addition, during the spirometric tests, the system presented the measurement results of (305 ± 22, 450 ± 23, 603 ± 24, 751 ± 26, 922 ± 27, 1021 <sup>±</sup> 30, 1182 <sup>±</sup> 33, 1326 <sup>±</sup> 36, 1476 <sup>±</sup> 37, 1618 <sup>±</sup> 45 and 1786 <sup>±</sup> 56) <sup>×</sup> 10−<sup>6</sup> m3 for reference values of (300 ± 2, 450 ± 3, 600 ± 3, 750 ± 4, 900 ± 5, 1050 ± 6, 1200 ± 6, 1350 ± 7, 1500 ± 8, 1650 ± 9 and 1800 <sup>±</sup> 9) <sup>×</sup> 10−<sup>6</sup> m3, respectively. Furthermore, we considered both the spirometry and pressure boundary conditions during the experiments using the mannequin lung, according to the results.

The performance of the proposed sensor was compared with a commercial spirometer, and the experimental results were equivalent. The profile of the curves and some measured parameters by the YF-S201 sensor and Koko spirometer are different. The YF-S201 characterizes normal breathing during ventilatory maneuvers while the Koko characterizes breathing from a person with a completely obstructed airway, partially obstructed airway or severe disease during the same maneuvers. After calibration, the YF-S201 sensor showed a minimum uncertainty of 22 <sup>×</sup> <sup>10</sup>−<sup>6</sup> m3 for volumes up to 300 <sup>×</sup> <sup>10</sup>−<sup>6</sup> m3, and a maximum uncertainty of 56 <sup>×</sup> <sup>10</sup>−<sup>6</sup> m3 for volumes greater than 1800 <sup>×</sup> <sup>10</sup>−<sup>6</sup> m3. Thus, the systematic and random errors were characterized, with a maximum error of 65 <sup>×</sup> <sup>10</sup>−<sup>6</sup> m3 or 3.6%.

The experiment confirmed that the measurements can be performed in various simulations using the dummies in conjunction with the sensor. It is a cost-effective alternative, and relatively easy to adapt to different mannequins. The results were based on spirometric models, bringing more realism to the simulations, and bringing numerous possibilities of debriefing. Thus, the sensor has great potential in various future applications.

In future work, we intend to use this sensor on mannequin babies and children. In addition, a supervisory software is being developed for training purposes, and to use in conjunction with the sensor on the manikin. It is also intended to perform the instrumentation of manikins dedicated to the teaching of pulmonary intubation maneuvers and tracheostomy, which the authors believe to be a novelty.

**Author Contributions:** Conceptualization, R.R.V.L., A.K.R.S. and C.F.L.; methodology, R.R.V.L., and A.K.R.S.; software, R.R.V.L. and A.K.R.S.; validation, R.R.V.L., A.K.R.S. and C.F.L.; formal analysis, A.K.R.S.; investigation, R.R.V.L. and A.K.R.S.; resources, R.R.V.L.; data curation, R.R.V.L.; writing—original draft preparation, R.R.V.L.; writing—review and editing, A.K.R.S. and C.F.L.; visualization, R.R.V.L.; supervision, A.K.R.S.; project administration, A.K.R.S.; funding acquisition, R.R.V.L.

**Funding:** This research received financial support from the Universidade Federal de Ouro Preto (UFOP) and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Financing Code 001.

**Acknowledgments:** The authors acknowledge the Collective Health Laboratory EMED/UFOP for lending the spirometer.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


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