Abstract:
Introduction. It is not possible to predict how multiple sclerosis (MS) will progress in any individual and
it’s difficult for a single specialist to manage all data of the disease and to offer an individual approach to
each patient. The existing management strategies require patients to attend regular follow-ups at the medical
centers, ideally at 6 or 12 months intervals. More regular personal consultations could improve disease
outcome, but are limited by the time, cost and geographical restraints. The spread of COVID-19 pandemic
has even further tightened the burden on monitoring chronic diseases like multiple sclerosis. Additionally,
studies find that patients with MS more often feel depressed, have a higher level of stress and feel
significantly less social support.
Aim of study. Review of literature on evaluation of the efficiency of new digital methods of monitoring
patients with multiple sclerosis.
Methods and materials. Published literature of the last 5 years, involving the digital technologies for
remote monitoring of patients with multiple sclerosis.
Results. Technological innovation is changing the traditional interaction between the patient and the
healthcare workers, enabling patients to contribute with more health data between the regular visits. The
most accessible device used is the smart-phone through apps or the internet. The apps can be divided in
four categories to evaluate: screening and assessment, monitoring and self-management, treatment and
rehabilitation and advice and education. The screening and assessment apps are an alternative to the
standard neurostatus scoring tests performed by the physicians. Apps for monitoring disease can be
combined with portable activity monitoring sensors, like wireless pressure sensors in patient shoes,
accelerometers, gyroscopes, grip sensors can detect small changes in patient’s gait, posture and balance.
Some applications can provide advice and education to stimulate the patient’s adherence to treatment and
rehabilitation exercise programs. To collect the high volume of information that certain tools generate we
can use Artificial Intelligence to create a digital twin paired to a patient's data, a technology in development
at the moment.
Conclusion. Digital technologies may be a game-changing strategy in monitoring multiple sclerosis,
however most of them need to be perfected and further studied before widespread adoption is likely.
Introduction of movement sensors and Artificial Intelligence could help detect small changes in the course
of the disease and alert the physicians. It remains to be studied if in the long term they benefit the patient’s
outcome.
