Networked Wearable Devices, Machine Learning-based Real-Time Data Sensing and Processing, and Internet of Medical Things in COVID-19 Diagnosis, Prognosis, and Treatment

Abstract

Telehealth can be used to decrease healthcare worker exposure and personal protective equipment donning, doffing, and conservation, while caring for COVID-19 patients and providing virtual urgent care screenings. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), interconnected and heterogeneous networks in patient diagnosis, monitoring, and treatment (section 4), monitoring systems and wearable sensors integrated in Internet of Medical Things and smart healthcare (section 5), networked wearable devices, machine learning algorithms, and Internet of Medical Things (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). 4.Interconnected and Heterogeneous Networks in Patient Diagnosis, Monitoring, and Treatment Smart healthcare leverages Internet of Medical Things, wireless communication technologies, medical sensors, wearable devices, and machine learning algorithms (Calvillo-Arbizu et al., 2021;Chang et al., 2022;Muhammad et al., 2021) to inspect patient data. Telehealth can be used to decrease healthcare worker exposure and personal protective equipment donning, doffing, and conservation, while caring for COVID-19 patients and providing virtual urgent care screenings. Internet of Medical Things articulates appropriate and inexpensive manners for healthcare delivery by integrating remote access in patient physiological data collection while harnessing machine learning techniques in diagnosis assistance.