ArticlePloS one2018
Free-living and laboratory gait characteristics in patients with multiple sclerosis.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06666816 (Observational Study for the Identification of Fatigue and Gait Biomarkers in Populations With Neuromuscular Pathologies in the Clinical Context and Daily Life), which is not on this map. Cited by 62 papers, 4 of them syntheses that pooled it.
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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.
Observational Study for the Identification of Fatigue and Gait Biomarkers in Populations With Neuromuscular Pathologies in the Clinical Context and Daily Life
Who cites it
62 citing papers in PubMed, 4 syntheses or guidelines pooled it, 118 citations in OpenAlex.
- Wearable Sensors in Gait Assessment for Parkinson Disease and Stroke in Real-World Environments: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Characterizing gait in people with multiple sclerosis using digital data from smartphone sensors: A proposed framework.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Pooled it
- Sarcopenia screening based on the assessment of gait with inertial measurement units: a systematic review.BMC geriatrics · 2024Pooled it
- Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review.Sensors (Basel, Switzerland) · 2020Pooled it
- A smartphone sensor-based digital outcome assessment of multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Trial
- Learning Beyond the Clinic: Can Point of Choice Visual Feedback Prompts Elicit Motor Behavior Changes in Persons with Multiple Sclerosis?Research square · 2026Article
- Accurate quantification of steps from multiple smartphone positions.Scientific reports · 2026Article
- Laboratory Environments Mask Gait Differences Between Healthy Participants and Patients With Anterior Cruciate Ligament Reconstruction.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026Article
- Digital assessment of real-world walking in people with impaired mobility: How many hours and days are needed?The international journal of behavioral nutrition and physical activity · 2025Article
- Capture of Longitudinal Change in Real-Life Walking in Cerebellar Ataxia Increases Patient Relevance and Effect Size.Movement disorders : official journal of the Movement Disorder Society · 2025Article
- How do people with COPD walk? A European study on digitally measured real-world gait.The European respiratory journal · 2025Article
- Gait characteristics in people with Friedreich ataxia: daily life versus clinic measures.Frontiers in neurology · 2025Article
- Quantitative Gait and Balance Outcomes for Ataxia Trials: Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers.Cerebellum (London, England) · 2024Review
- Validation of Pelvis and Trunk Range of Motion as Assessed Using Inertial Measurement Units.Bioengineering (Basel, Switzerland) · 2024Article
- Automatic gait events detection with inertial measurement units: healthy subjects and moderate to severe impaired patients.Journal of neuroengineering and rehabilitation · 2024Article
- Assessing Free-Living Postural Sway in Persons With Multiple Sclerosis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2024Article
- Long-term continuous instrumented insole-based gait analyses in daily life have advantages over longitudinal gait analyses in the lab to monitor healing of tibial fractures.Frontiers in bioengineering and biotechnology · 2024Article
- Laboratory and free-living gait performance in adults with COPD and healthy controls.ERJ open research · 2023Article
- Challenges and advances in the use of wearable sensors for lower extremity biomechanics.Journal of biomechanics · 2023Article
- Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective.Journal of medical Internet research · 2023Article
2 more citing papers are in PubMed but not listed here.
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 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWearable sensors offer the potential to bring new knowledge to inform interventions in patients affected by multiple sclerosis (MS) by thoroughly quantifying gait characteristics and gait deficits from prolonged daily living measurements. The aim of this study was to characterise gait in both laboratory and daily life conditions for a group of patients with moderate to severe ambulatory impairment due to MS. To this purpose, algorithms to detect and characterise gait from wearable inertial sensors data were also validated.
methodsFourteen patients with MS were divided into two groups according to their disability level (EDSS 6.5-6.0 and EDSS 5.5-5.0, respectively). They performed both intermittent and continuous walking bouts (WBs) in a gait laboratory wearing waist and shank mounted inertial sensors. An algorithm (W-CWT) to estimate gait events and temporal parameters (mean and variability values) using data recorded from the waist mounted sensor (Dynaport, Mc Roberts) was tested against a reference algorithm (S-REF) based on the shank-worn sensors (OPAL, APDM). Subsequently, the accuracy of another algorithm (W-PAM) to detect and classify WBs was also tested. The validated algorithms were then used to quantify gait characteristics during short (sWB, 5-50 steps), intermediate (iWB, 51-100 steps) and long (lWB, >100 steps) daily living WBs and laboratory walking. Group means were compared using a two-way ANOVA.
resultsW-CWT compared to S-REF showed good gait event accuracy (0.05-0.10 s absolute error) and was not influenced by disability level. It slightly overestimated stride time in intermittent walking (0.012 s) and overestimated highly variability of temporal parameters in both intermittent (17.5%-58.2%) and continuous walking (11.2%-76.7%). The accuracy of W-PAM was speed-dependent and decreased with increasing disability. The ANOVA analysis showed that patients walked at a slower pace in daily living than in the laboratory. In daily living gait, all mean temporal parameters decreased as the WB duration increased. In the sWB, the patients with a lower disability score showed, on average, lower values of the temporal parameters. Variability decreased as the WB duration increased.
conclusionsThis study validated a method to quantify walking in real life in people with MS and showed how gait characteristics estimated from short walking bouts during daily living may be the most informative to quantify level of disability and effects of interventions in patients moderately affected by MS. The study provides a robust approach for the quantification of recognised clinically relevant outcomes and an innovative perspective in the study of real life walking.
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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.