Wearable Sensors Are Quietly Revolutionizing Multiple Sclerosis Monitoring

Multiple sclerosis is a progressive immune-mediated disease where disability accumulates over years or decades, yet the primary clinical measurement tool—the EDSS—is semi-quantitative, nonlinear, and typically administered only every three to six months. This creates major blind spots for detecting early change, guiding therapy, or powering clinical trials. The authors from Johns Hopkins argue that digital biosensors can fill these gaps by providing continuous, objective, quantitative data across multiple functional domains.

The review covers six core monitoring domains. For physical activity and circadian rhythmicity, accelerometers reliably show that people with MS are more sedentary, more active-to-sedentary transition-prone, and have weaker circadian rhythm amplitude than healthy controls—differences that are amplified in progressive MS. Critically, the HEAL-MS longitudinal cohort found that within-person increases in nighttime activity and decreases in morning activity predicted faster rates of whole-brain and gray matter atrophy over roughly one year, suggesting wearable metrics may serve as leading indicators of neurodegeneration.

For gait, both non-wearable systems (optical motion capture, force platforms, instrumented walkway mats like GAITRite) and wearable IMUs reveal reduced speed, altered stride length, increased stride-to-stride variability, and instability even in early MS patients without clinically apparent disability. Wearables extend this monitoring into real-world community settings, where gait performance is consistently worse than in-clinic measurements—a finding with direct implications for how we interpret trial endpoints. Sensorized cane/crutch tips have even been proposed for patients requiring assistive devices.

Balance assessment using IMU-instrumented versions of classic tests (e.g., Balance Error Scoring System, Romberg) and force platforms demonstrates postural instability in MS that correlates with fall risk and disability. Fine motor function—captured by finger-tapping apps, instrumented stylus devices, dynamometers, and novel textile gloves—detects subtle hand dexterity deficits often missed by standard assessments, including in early disease. Bladder sensors, including wearable ultrasound and electronic bladder diaries, offer objective, non-invasive monitoring of voiding patterns and urgency that surpass subjective questionnaire data.

The overarching theme is that biosensors consistently reveal subclinical impairment that standard clinical measures miss. Longitudinal associations between wearable-derived metrics and brain imaging outcomes suggest predictive validity. However, the field faces challenges: methodological heterogeneity across studies limits cross-study comparison, commercial sleep and autonomic algorithms are not validated in MS populations, and regulatory pathways for integrating these tools into trials remain underdeveloped. Larger longitudinal validation studies are needed before clinical adoption can be recommended broadly.