Patient Health Monitoring Using IoT Information Technology

Abstract

The paper examines the features of IoT devices that collect real-time medical parameters from patients and their integration with machine learning methods to improve data quality. The article describes common approaches to correcting these artifacts to ensure the accuracy and reliability of medical diagnostic systems. The authors also focus on the practical application of filters and machine learning methods to optimize signal processing, which enables high-precision patient monitoring in real-time. Key technical and methodological challenges associated with integrating IoT into medical systems are highlighted, and solutions are proposed to improve monitoring efficiency and accuracy.