Development and validation of a respiratory pattern analysis system for Post-COVID-19 patients

Abstract

Introduction: Due to advancements in vaccination, the morbidity and lethality rates of Covid-19 have diminished significantly. Consequently, there has been a substantial decline in severe cases, underscoring the importance of long-term monitoring for individuals. In response to this imperative, a prototype device for evaluating the respiratory patterns of Covid-19-affected individuals has been conceptualized, necessitating specialized software for data analysis and processing. Objective: To develop a system for analyzing variables of the respiratory pattern for application in post-Covid-19 patients. Methodology: The desktop application of the device was developed using the Electron framework, incorporating the React graphical interface library and JavaScript for algorithm development to analyze respiratory flow and volume curves. HTML and CSS were employed for screen structuring and styling. The measured respiratory flow signal underwent numerical calculation techniques and algorithms for time-series analysis based on respiratory cycle intervals. Derived variables included respiratory rate, inspiratory, expiratory, and total time, inspiratory and expiratory flow and volume, minute inspiratory and expiratory volume, inspiratory capacity, and vital capacity. System validation involved comparing the flow signal acquired by the device with that of a Hans Rudolph Pneumotachograph (standard method) using Bland-Altman plots. Results: The RDA Analysis software, integrated with interfaces for patient records and flow/volume vs. time graphs, captured respiratory cycles during rest breathing and incorporated slow inspiratory and vital lung capacities. The RDA Sync software was developed as an auxiliary program, synchronizing and simultaneously analyzing multiple patient exams. Bland-Altman analysis revealed a bias of 0.48 L/min, with agreement limits of -10.7 and 11.6 L/min (p-value < 0.0001). Conclusion: The respiratory flow measured by the device exhibits high concordance with the gold standard. The developed software strengthens the device as a minimum viable product, currently employed to monitor respiratory pattern dysfunctions in post-Covid patients. This enhances the precision of the examination, providing quantitative and qualitative information for diagnostic assessment of respiratory functionality.