eHealth4MS: Problem detection from wearable activity trackers to support the care of multiple sclerosis

Abstract

This paper presents eHealth4MS, an assistive technology system based on wearable trackers to support the care of Multiple Sclerosis (MS). Initially, the system integrates a tracker and a smartphone to collect and unanimously store movement, sleep and heart rate (HR) data in an ontology-based knowledge base. Then, ontology patterns are used to provide an initial approach to detect problems and symptoms of interest, such as lack of movement, stress or pain, insomnia, excessive sleep, lack of sleep and restlessness. Finally, the system visualizes data trends and detected problems in dashboards and apps. This will allow patients to self-manage and for clinicians to drive effective and timely interventions and to monitor progress in future trials to evaluate the system’s accuracy and effectiveness.