Going beyond PA: Assessing sensorimotor capacity with wearables in multiple sclerosis-a cross-sectional study.
Philipp Gulde, Heike Vojta, Stephanie Schmidle and 2 others
PMID 37735674WHAT IT FOUND
Smartwatch data from 90 people with MS linked movement patterns to clinical severity, but not reliably to specific upper-limb skills.
One metric tracked grip strength independently of disability scores, while others mixed activity volume with ability.
Key findings
01Activity fragmentation (FATREV) remained associated with upper-limb capacity and reaction times even after adjusting for disability severity (EDSS).
02Peak movement intensity (PEAKSTD) predicted grip strength independently of EDSS, but failed to predict dexterity or tapping once EDSS was included.
03Average walking cadence (CADENCE) correlated with many measures but was unspecific, serving more as a global indicator of condition than a measure of specific sensorimotor capacity.
STILL TO COME
How it was doneWhat they foundWhat it means for PTsWhat it means for OTs
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What it does not show
The study was exploratory and cross-sectional, using only one day of data, so it cannot establish reliability over time or causality. The sample was a convenience sample from an inpatient rehabilitation setting, excluding those with very high disability (EDSS >= 8.5) or severe nursing needs, limiting generalizability to other MS populations. Therapy content and intensity were not controlled for, so differences in movement patterns may reflect varying treatment schedules rather than patient capacity. The smartwatch metrics explained limited variance in lab-assessed capacity, indicating they are not yet ready to replace standard clinical assessments. The study did not measure fatigability or cognitive load directly, so it is unclear whether reduced activity fragmentation was due to physical weakness, fatigue, or cognitive factors.
Declared interests
Funded by the German Federal Ministry of Education and Research, the Free State of Bavaria, the TUM Innovation Network, and the Technical University of Munich. No commercial conflicts of interest with the smartwatch manufacturer (Huawei) were declared.
The easy way to misread this
Do not assume that smartwatch-derived movement metrics accurately measure specific sensorimotor capacity like dexterity or tapping speed. Most metrics were heavily influenced by overall disability severity (EDSS) or were too unspecific to distinguish between different types of impairment.