Data Analysis and Modeling of Body Sensor Network in Healthcare Application

Abstract

Data are now processed relatively in an efficient manner due to the development of machine learning techniques. Such strategies for knowledge extraction are frequently employed in a variety of contexts, including business, social media, voting, wagering, forecasting, and more. Healthcare in Body Sensor Network is one of these key fields where modelling and data analysis are extensively used. The data that is captured and processed in this network is used to track a person's everyday activities, check that the data is accurate, determine when a medical emergency is required, and more. There are sufficient studies based on such analysis; some offered their own methodology while others employed pre-defined techniques such as Machine Learning, Neural Networks, Deep Learning, and more. In order to analysis the sensor data, various methodologies that have been stated in some selected research articles are compared in this document. Both the analysis methods and the study's findings are very diverse and have many unique characteristics. The comparison study provides a comprehensible demonstration of these methods and features.