While progresses have been made in medications to treat Multiple sclerosis (MS), there are difficulties in assessing the
multifaceted evolution of the disease. Sensitive, reliable capture of disability is critical for developing early stage trials aimed at stopping neuronal loss and progressive disease.
With the mass production of connected sensors, there is an opportunity to transform the traditional neurological exam with
biosensors already in use outside the realm of health applications. We herein propose to validate a wearable electromyography device (MYO) for detection of upper and lower limb dysfunction in MS patients. We will refine signal processing algorithms to create reliable outcomes using this device in MS patients. We hypothesize that this digital technology may be introduced in the standard neurological exam technique in a non-disruptive non-invasive manner and more accurately detect both physicianreported and patient-reported disability. This bi-lateral project is an ideal demonstrator for multi-centric digital data acquisition that is critical to secure funding for future research.