Remote Patient Monitoring Platform for Neurological Conditions

As the only remote patient monitoring platform designed and created by clinical physicians, our vision is to fundamentally change the way we understand and manage chronic neurologic diseases, remove biases, and find new treatments with better outcomes.  

BeCare Link provides validated, quantitative measurements of neurologic function and cognition, supplemented by AI analysis* to improve patient care. By assessing their own neurologic and cognitive function at home through the BeCare Link app, patients are empowered to monitor their clinical progress and strengthen the bonds with their physicians.

*This feature is currently only available for use in an academic/research settings, but it will be released to the public pending FDA clearance

Tracking brain functions through remote patient monitoring

Our Partners

BeCare Link is proud to be able to collaborate with world class and highly influential partners.

MS research partner Weill Cornell Medicine
MS research partner Mount Sinai Hospital
MS research partner The Galien Foundation
MS research partner BayBridgeDigital
MS research partner Neurogen Research Foundation
MS research partner Yale University School of Medicine


BeCare has run two pilot studies, at Weill Cornell and Yale School of Medicine, comparing the remote neurologic assessment captured by and the Artificial Intelligence interpretation created using the BeCare MS Link data with the in-person neurologic assessment by clinicians.  There was a close correlation between the functional assessment and disability scores based on BeCare MS Link’s gamified activity and the EDSS score calculated in the MS centers.    

A review of available MS apps failed to show any other apps that collect quantified data and have AI interpretation of functional systems and disability scores similar to the BeCare MS Link.

           Rubin, L., M Kruse-Hoyer, C Litchman, S Stoll, D Putrino, S Shetty, C Engel, M Marcille,  S Gauthier, J Perumal, N Nealon, U Kaunzer, T Vartanian.  “Patient Centered Outcomes Analysis for Multiple Sclerosis Using a Mobile Application”   Fourth Annual American Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS),  Dallas, TX. Feb 2019. 

            Stoll, S., T Litchman, S Wesley, C Litchman, “Multiple sclerosis apps: The dawn of a new era: A comprehensive review” 71st Annual American Academy of Neurology (AAN), Philadelphia, PA . May 2019.

            Litchman, C., T Vartanian, L Rubin, N Rubin, S StollAutomated EDSS scoring using a mobile App & Machine Learning. 72st Annual American Academy of Neurology (AAN), Toronto, Canada, 2020. 

            Stoll, S.  N Rubin, L Rubin, T Litchman, J Keaney,T Vartanian, , C Litchman. Machine Learning Evaluation of MS patients during the time of COVID. 73rd Annual American Academy of Neurology (AAN), 2021.

           Liam Johnson, Adam Fry, Behdad Dehbandi,  Lawrence Rubin , Michael Halem, Alexandre Barachant , Anna H. Smeragliuolo, David Putrino  An automated, electronic assessment tool can accurately classify older adult postural stability , Journal of Biomechanics, BM 9228 No. of Pages 5, Model 5G 6 June 2019  

           Stoll, S., C Litchman, N Rubin, L Rubin, T Vartanian. Validated, Quantitative, Machine Learning-Generated Neurologic Assessment of Multiple Sclerosis Using a Mobile Application. Int J MS Care (2023)