Predictive Modeling For Real-Time Personalized Health Monitoring in Muscular Dystrophy Management
It addresses the need for continuous, remote monitoring in muscular dystrophy care, but is incremental as it applies existing IoT technology to this specific domain.
This paper tackles the problem of real-time health monitoring for muscular dystrophy patients by proposing an Internet of Things-based system to provide actionable data, aiming to enhance treatment strategies and improve patient management.
Muscular Dystrophy is a group of genetic disorders that progressively affect the strength and functioning of muscles, thereby affecting millions of people worldwide. The lifetime nature of MD requires continuous follow-up care due to its progressive nature. This conceptual paper proposes an Internet of Things-based system to support the management of MD through remote, multi-dimensional monitoring of patients in order to provide real-time health status updates. Traditional methods have failed to give actionable data in real time, hence denying healthcare providers the opportunity to make evidence-based decisions. Technology-driven approaches are urgently needed to provide deep insights into disease progression and patient health. It aims to enhance treatment strategies, enabling patients to better manage their condition and giving healthcare professionals more confidence in their management decisions.