ArticleMultiple sclerosis (Houndmills, Basingstoke, England)2021
Wearable technologies to measure clinical outcomes in multiple sclerosis: A scoping review.
Article in Multiple sclerosis (Houndmills, Basingstoke, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 68 citations in OpenAlex.
- Characterizing gait in people with multiple sclerosis using digital data from smartphone sensors: A proposed framework.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Pooled it
- Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review.Journal of medical Internet research · 2022Pooled it
- Targeting progressive multiple sclerosis: Toward mechanism-informed precision medicine.Journal of internal medicine · 2026Review
- Stride-level measurement of gait as an early sensitive marker of disability progression in ambulatory patients with multiple sclerosis.EClinicalMedicine · 2026Article
- Smartphone-based gait analysis in the assessment of fatigue and fatigability in people with multiple sclerosis: a supervised cohort study.Journal of neurology · 2025Article
- Improving telehealth for persons with multiple sclerosis - a cross-sectional study from the Australian MS longitudinal study.Disability and rehabilitation · 2024Article
- Sufficiency for PSS tracking gait disorders in multiple sclerosis: A managerial perspective.Heliyon · 2024Article
- Exploring the Major Barriers to Physical Activity in Persons With Multiple Sclerosis: Observational Longitudinal Study.JMIR rehabilitation and assistive technologies · 2024Article
- No Increase in Symptoms Toward the End of the Ocrelizumab Infusion Cycle in Patients With Multiple Sclerosis: Symptom Burden on Ocrelizumab: A Longitudinal Study (SymBOLS).Neurology. Clinical practice · 2023Article
- Multiple sclerosis functional tests and their comparability with self-administered values: A pilot studyBiomedica : revista del Instituto Nacional de Salud · 2023Article
- Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective.Journal of medical Internet research · 2023Article
- Machine learning based estimation of dynamic balance and gait adaptability in persons with neurological diseases using inertial sensors.Scientific reports · 2023Article
- Personalized monitoring of ambulatory function with a smartphone 2-minute walk test in multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2023Article
- Locomotor Strategy to Perform 6-Minute Walk Test in People with Multiple Sclerosis: A Prospective Observational Study.Sensors (Basel, Switzerland) · 2023Observational
- Progression events defined by home-based assessment of motor function in multiple sclerosis: protocol of a prospective study.Frontiers in neurology · 2023Article
- Autonomic response to walk tests is useful for assessing outcome measures in people with multiple sclerosis.Frontiers in physiology · 2023Article
- Management of multiple sclerosis fatigue in the digital age: from assessment to treatment.Frontiers in neuroscience · 2023Review
- Balance Impairments in People with Early-Stage Multiple Sclerosis: Boosting the Integration of Instrumented Assessment in Clinical Practice.Sensors (Basel, Switzerland) · 2022Article
- Digital Biomarker-Based Studies: Scoping Review of Systematic Reviews.JMIR mHealth and uHealth · 2022Article
- Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development and Usability Study.JMIR human factors · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wearable technology refers to any sensor worn on the person, making continuous and remote monitoring available to many people with chronic disease, including multiple sclerosis (MS). Daily monitoring seems an ideal solution either as an outcome measure or as an adjunct to support rater-based monitoring in both clinical and research settings. There has been an increase in solutions that are available, yet there is little consensus on the most appropriate solution to use in either MS research or clinical practice. We completed a scoping review (using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines) to summarise the wearable solutions available in MS, to identify those approaches that could potentially be utilised in clinical trials, by evaluating the following: scalability, cost, patient adaptability and accuracy. We identified 35 unique products that measure gait, cognition, upper limb function, activity, mood and fatigue, with most of these solutions being phone applications.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.