Design of Smart Wristbands for the control of the elderly using artificial intelligence

Abstract

This thesis provides a comprehensive analysis of recent health monitoring systems based on artiĄcal intelligence, with a focus on the study of the electrocardiogram (ECG), blood oxygen saturation (SpO2), heart rate (HR), integrated vital signs, and human fall detection. In order to improve patient safety and enhancing healthcare outcomes, the research investigates the integration of these critical parameters into a cohesive system. This thesis further delves into ECG analysis, HR analysis, SpO2 analysis, and combined vital signs assessment. In addition to vital signs analysis, the thesis addresses the critical need for human fall detection mechanisms and present a comprehensive approach to health monitoring, leveraging the power of combined vital signs analysis and human fall detection to enhance patient safety and improve clinical outcomes. The Ąndings of this thesis contributes to the advancement of healthcare technologies by showcasing the effectiveness of integrated health monitoring systems in early detection, prevention, and management of medical conditions, thereby enhancing patient care and well-being.