Artificial intelligence and WeArables for the undeRstanding and Evaluation of Multiple Sclerosis

Objective

The immune system protects the human body against disease and infection, but when it malfunctions, it can lead to autoimmune diseases like multiple sclerosis (MS). MS is a chronic inflammatory condition affecting the Central Nervous System, characterized by the demyelination of nerve fibers. It is currently one of the leading causes of non-traumatic disability worldwide, affecting 2.8 million of individuals. Most MS cases begin with relapsing-remitting episodes, marked by acute events, known as relapses, that occur frequently and present with severe sensorimotor symptoms. Early detection and prevention of relapses are crucial, as these events cause cumulative neurological damage that drives disease progression and leads to irreversible functional disability. A deeper understanding of MS relapses is vital for enabling effective, targeted care and improved disease management outcomes. Standard prognostic tools, like clinical scales, present weak predictive power, and more advanced solutions are still immature, lacking robust validation and interpretability. The AWARE-MS (Artificial intelligence and WeArables for the undeRstanding and Evaluation of Multiple Sclerosis) project aims at establishing a proactive approach to MS by modelling the evolution of MS to uncover the mechanisms underlying relapse onset and severity and ultimately address the early detection of exacerbations. The proposed framework integrates continuous multimodal data collected on MS patients via wearable devices with interpretable physics-informed machine learning (PIML) models. The project will leverage the biomedical expertise of Spaulding Rehabilitation Hospital (US) and the bioengineering and data science expertise of Scuola Superiore Sant’Anna (IT). AWARE-MS has the ambition of enhancing the awareness of MS processes to further impact treatment and decision strategies in the long-term, thus, improving patients’ quality of life and reducing the global healthcare burden associated with MS.