Smartphone-based gait assessment for multiple sclerosis.

Area of Science:

• Neurology
• Biomedical Engineering
• Digital Health

Background:

• Multiple Sclerosis (MS) significantly impacts gait, even in early disease stages.
• Traditional gait assessment methods lack ecological relevance.
• The Mon4t® app utilizes smartphone sensors for gait parameter measurement.

Purpose of the Study:

• To evaluate the efficacy of Mon4t® technology for monitoring patients with Multiple Sclerosis.
• To assess the app's ability to detect gait changes in MS patients.

Main Methods:

• 100 MS patients and healthy controls (HC) were assessed using the Mon4t Clinic™ app and a human rater.
• Gait was analyzed during Timed up and go (TUG) and tandem walk tests.
• Digital gait markers were compared between MS and HC groups, including subgroups based on EDSS scores.

Main Results:

• Significant gait parameter differences were observed between MS patients and HC.
• Non-disabled MS patients (EDSS=0) showed altered gait compared to HC, distinguishable with high confidence (85.65% AUC).
• Gait parameters correlated with disability (EDSS>0) and were significantly different between disability levels.

Conclusions:

• Digital gait assessment via the Mon4t® app shows potential for augmenting traditional MS monitoring.
• The app provides a convenient, ecologically relevant tool for detecting early gait impairment in MS.
• Findings support the use of digital tools in clinical decision-making for MS management.