- Feb 23, 2022
- Posted by: admin
- Category: Abstract of 5th-icmets
Proceedings of The 5th International Conference on Modern Research in Engineering, Technology and Science
Mobile Applications and Cloud Computing Applied on a Solution to Optimize the Auscultation Process
Paulo Estevão de Oliveira Ferreira, Daniel Alberto Santos Divino, Gabriella Braga Garcia Santos, Gustavo Ferreira Lins do Rego Santos, Lais Pimenta Lopes, Renato Alcântara Bento Raphael, Ricardo Barbosa Soares, Suellem Andrade Dutra, Wilgner Ricardo Rail Silva, Vladimir Alexei Rodrigues Rocha, Gustavo Alves Fernandes, Luiz Melk de Carvalho, Bráulio Roberto Gomes Marinho Couto, Diva de Souza e Silva Rodrigues, Flávio Henrique Batista de Souza
Auscultation measurement is one of the primary processes of medical education. Despite its extreme importance, the number of patients who are delegated to students for their care depends on the frequency of patients at the clinic where they perform their practices, which may be sufficient or not (in the pandemic period of COVID-19, the Brazilian hospitals had a high demand for professionals in the medical field, emptying school clinics). In addition, it is relevant for the teachers to compare the auscultation diagnosis that their students made with the signal that was actually collected in the process. This work proposes a method that aims to assist the teaching of cardiac auscultation techniques in medical courses, as well as to generate a structure that can share the measurements, in addition to recording them via Cloud Computing for further evaluation by the teacher. To achieve this goal, this project aims on developing two applications: a web and a mobile application. The mobile application is responsible to capture the sounds generated during the auscultation process using a hardware adapted on a stethoscope and a microphone. The audios collected are saved in the cloud using the Cloud Firestore platform and can be accessed through both web and mobile platforms. The framework also enables the implementation of a data analysis tool for medical teaching strategies.
keywords: Cardiac Auscultation; Mobile Application; Cloud Computing; Medical Education; Data Analytics.