Multiple sclerosis (MS) is a auto-immune disease that is mostly characterized by acute clinical relapses and/or focal inflammation in the central nervous system (CNS) followed by recovery. Yet, a significant part of the patients also experience a progressive decline in function. This progressive phase usually has an insidious onset causing a delay for diagnosis and adjusted therapies. There are plenty of clinical assessments available to measure walking speed, cognition, sleep,.... . But these assessments are merely a snapshot of the patient 's symptoms. By monitoring these parameters at home, real life data can be provided to capture subclinical signs of progression. The goal of this study is to detect a digital biomarker for progressive MS at an earlier stage next to validating wearables by comparing them to golden standard measurements such a polysomnography or gait analysis in a specialized lab.