ABSTRACT
In this research work, a novel and unique way is proposed to monitor the health by means of advanced technologies that includes wireless communication and machine learning. ‘The system uses multiple-input, multiple-output technology...along with the Internet of Things architecture to continuously and remotely measure health status via a number of sensors.’ * Trained machine learning models such as ANNs, KNNs, DTs and SVMs over se nsor data can successfully predict health changes. Not only the confusion matrix provides a better visualization on where particular areas are considered more favorable, but for each possible selection of parameters and quantification indicators (based upon accuracy) it would determine which is in theory a model that performs “best”. Hence, in order to make personalized health monitoring accurate it is important that an individual component level of physiology should be understood. · Enables real-time data capture and access by the involved healthcare professionals thus improving patient-centered care. I hope that this study will help to improve the future of the healthcare system by enabling it to become more personalized and predictive, which in turn should improve patient outcomes down the road.
