Utilizing Ultra Wideband Technology for Health Monitoring through Lens of Machine Learning

Ultra-wideband (UWB) technology is considered as a promising technique towards different applications of clinical infrastructure, delivers noteworthy features such as fine localization accuracy, very high data rates and low energy consumption. The paper systematically reviews the use of UWB technology in clinical environments: in healthcare monitoring, medical imaging, indoor positioning and wireless communication. Based on a set of high-quality data from UCI Machine Learning Repository, this paper gives empirical results involving the performance and capability of UWB-based systems in bettering healthcare outcomes. They additionally detail response and potential barriers, including integration challenges and regulatory constraints, as well as assets like the symbiosis of UWB technology to trigger future developments in patient care and healthcare disbursal. In addition, the authors combined feature selection and random forest model to obtain an accuracy of 91.8%.