Passive digital monitoring via mobile apps and wearables in multiple sclerosis: A systematic review.
Paolo De Blasiis, Annunziata Attena, Allegra Fullin et al.
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In 30 seconds
This PRISMA-guided systematic review synthesized 14 studies of passive digital monitoring in people with multiple sclerosis. The studies assessed unobtrusively collected smartphone and wearable data, including touchscreen interactions, movement, and physiological signals, and compared derived features with standard clinical scales. Across motor, cognitive, and symptomatic domains, digital biomarkers showed significant correlations with clinical scores. Typing and gait measures aligned with upper-limb dexterity and walking ability, while keystroke latency reflected cognitive processing speed; multimodal markers also tracked fatigue, depression, and sleep quality.
Key findings
- Across 14 included studies, passive digital biomarkers showed significant correlations with established clinical scores across motor, cognitive, and symptomatic domains.
- Typing kinematics and gait parameters aligned with measures of upper-limb dexterity and walking ability, respectively.
- Keystroke latency metrics were sensitive to cognitive processing speed.
- Multimodal physiological and behavioral markers tracked fatigue, depression, and sleep quality.
Why it matters
Episodic clinical assessments may miss subtle changes in everyday functioning. Passive smartphone and wearable measures could complement standard scales by capturing activity and symptoms between visits, including cognitive and non-motor domains. This may help characterize real-world function more continuously, although the review reports associations with clinical scores rather than evidence that monitoring improves outcomes.
What to keep in mind
The review included 14 studies, and the abstract does not report evidence that digital monitoring improves clinical outcomes or therapeutic decisions.