Abstract
(Alimadadi et al., 2020) In clinical settings, Internet of Medical Things optimizes patient-centric undertakings with remote patient monitoring, and, in clinical trials, accurately tracks vital signs, blood-sugar levels, and weight trends. (Usak et al., 2020) Internet of Things-assisted cloud-based health monitoring systems deploy heterogeneous physiological and environmental signals to supply contextual data through artificial intelligence-based diagnostic algorithms. Methodology and Empirical Analysis Building our argument by drawing on data collected from Accenture, AIR, Amwell, Ericsson ConsumerLab, Ginger, Kyruus, PwC, and Syneos Health, we performed analyses and made estimates regarding how connected wearable biomedical devices can assist in configuring precise diagnoses. Study Design, Survey Methods, and Materials The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States.
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