NurseAid Monitor: A Non-Invasive Monitor to Assess Respiratory Rate and Pattern of Bedridden Patients

Abstract: The clinical management of bedridden patients necessitates meticulous attention to their respiratory health, as their constrained mobility significantly increases the risk of respiratory complications. Considering the critical link between respiratory function and recovery outcomes, this research underscores the importance of monitoring respiratory frequency and patterns as an essential aspect of care for these individuals. Diligent observation of respiratory parameters enables healthcare providers to identify early signs of deterioration in respiratory health, allowing for timely intervention and, consequently, a reduction in the incidence of serious complications. We propose a platform based on non-invasive contactless Infrared thermography that analyzes respiratory frequency and patterns. With the help of volunteers, we conducted an experiment to collect data for statistical treatment and modeling. Our results, discussed in this work, substantiate the data collection approach and the selected methodology.

Keywords: Healthcare and Medical Devices, Internet of Things (IoT), Health Informatics, Machine Learning, Computer Vision

DOI: 10.54941/ahfe1005075

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