Virtual Care Technologies, Wearable Health Monitoring Sensors, and Internet of Medical Things-based Smart Disease Surveillance Systems in the Diagnosis and Treatment of COVID-19 Patients
Virtual Care Technologies, Wearable Health Monitoring Sensors, and Internet of Medical Things-based Smart Disease Surveillance Systems in the Diagnosis and Treatment of COVID-19 Patients

Summary/Abstract: The aim of this paper is to synthesize and analyze existing evidence on virtual care technologies, wearable health monitoring sensors, and Internet of Medical Things-based smart disease surveillance systems in the diagnosis and treatment of COVID-19 patients. Using and replicating data from Deloitte, Ericsson ConsumerLab, GlobalWebIndex, McKinsey, PwC, Sony, and Sykes, we performed analyses and made estimates regarding artificial intelligence-based diagnostic algorithms in Internet of Things-supported healthcare delivery. Artificial intelligence-enabled wearable medical devices, virtualized care systems, and wireless biomedical sensing devices are pivotal in COVID-19 screening, testing, and treatment. Digital epidemiological surveillance in monitoring, detection, and prevention of COVID-19 is optimized by use of medical artificial intelligence, clinical and diagnostic decision support systems, machine learning-based real-time data sensing and processing, and smart healthcare devices and applications. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

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