Real-Time Visual Analytics for Remote Monitoring of Patients' Health

Abstract

The recent proliferation of advanced data collection technologies for Patient Generated Health Data (PGHD) has made remote health monitoring more accessible. However, the complex nature of the big volume of medical generated data presents a significant challenge for traditional patient monitoring approaches, impeding the effective extraction of useful information. In this context, it is imperative to develop a robust and cost-effective framework that provides the scalability and deals with the heterogeneity of PGHD in real-time. Such a system could serve as a reference and would guide future research for monitoring patient undergoing a treatment at home conditions. This study presents a real-time visual analytics framework offering insightful visual representations of the multimodal big data. The proposed system was designed following the principles of User Centered Design (UCD) to ensure that it meets the needs and expectations of medical practitioners. The usability of this framework was evaluated by its application to the visualization of kinematic data of the upper limbs' movement of patients during neuromotor rehabilitation exercises.