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Abstract
Around the world, more than 20 million patients rely on mechanical ventilators annually; however, not enough individuals understand how to operate ventilators, posing a risk to the health of many. Moreover, it is increasingly difficult to determine optimal mechanical ventilator settings in a timely fashion, especially in low-resource countries and critical care areas. Respire is a mobile application that bridges this gap in a twofold manner: it is designed to assist healthcare workers around the world navigate and use mechanical ventilators effectively as well as educate the general public about mechanical ventilation. Respire offers a user-friendly yet educational interface that quickly generates the most optimal ventilator settings based on the patient’s age, gender, weight, and health history. With limited information provided, Respire provides an individualized-patient model for optimal mechanical ventilation settings, including values generated for Positive End-Expiratory Pressure (PEEP), Respiratory Rate (RR), Tidal Volume (TV), and Trigger Sensitivity (TS). Developed entirely from scratch, this application was built in Android Studio IDE utilizing the programming language Java, and the graphical user interface as well as design components were created using XML and CSS. The desired outcomes of this program are to serve as an educational platform and a tool to supplement patient care related to medical respiration.
Publication Date
2023
Subject Major(s)
Bioinformatics
Keywords
mechanical ventilation, mobile, application, educational, patient, technology, model, education
Disciplines
Bioinformatics | Biomedical Informatics | Health Information Technology | Medical Education
Current Academic Year
Freshman
Faculty Advisor/Mentor
Dr. LaMont Cannon, Ph.D
Rights
© The Author(s)
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Health Information Technology Commons, Medical Education Commons