ReviewBrain sciences2019
The Role of Movement Analysis in Diagnosing and Monitoring Neurodegenerative Conditions: Insights from Gait and Postural Control.
Review in Brain sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 4 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
100 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- 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
- Outcome measures of instrumented gait analysis in hereditary spastic paraplegia: a systematic review.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Machine Learning Approaches for Dementia Detection Through Speech and Gait Analysis: A Systematic Literature Review.Journal of Alzheimer's disease : JAD · 2024Pooled it
- Experiment protocols for brain-body imaging of locomotion: A systematic review.Frontiers in neuroscience · 2023Pooled it
- A Double-Blind, Randomized, Placebo-Controlled Trial of Ursodeoxycholic Acid (UDCA) in Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2023Trial
- The effects of Pilates training combined with whole-body vibration on balance and mobility in people with multiple sclerosis: A single-blind randomized controlled clinical trial.Turkish journal of physical medicine and rehabilitation · 2026Article
- Multi-Task Wearable Parkinson's Disease Detection with a Pretrained Spatio-Temporal Graph Encoder and Task-Level Token Aggregation.Bioengineering (Basel, Switzerland) · 2026Article
- Detection of early-stage Parkinson's disease using wearable sensors at multiple body locations and convolutional neural networks.Scientific reports · 2026Article
- The Concurrent Validity and Test-Retest Reliability of a Smartphone-Based Markerless System.Sensors (Basel, Switzerland) · 2026Article
- The Clinician's Guide to Computer Vision in the Motion Capture Galaxy.Restorative neurology and neuroscience · 2026Article
- Estimation of the Knee Joint with Single-Camera Smartphone.Sensors (Basel, Switzerland) · 2026Article
- Sensorimotor Impairment and Incident Dementia in the US Medicare Beneficiaries.Journal of the American Geriatrics Society · 2026Article
- Identifying and predicting gait stability metrics in people with stroke in uneven-surface walking using machine learning.Scientific reports · 2026Article
- Predictive Value of Digital Neuropsychological and Gait Assessments on Shunt Outcome in Patients With Idiopathic Normal Pressure Hydrocephalus: Prospective Cohort Study.Journal of medical Internet research · 2025Article
- Dual-task walking for early detection of Alzheimer's disease: comparative analysis of tasks using whole-body gait variables.BMC geriatrics · 2025Article
- A Dataset of Clinical Gait Signals with Wearable Sensors from Healthy, Neurological, and Orthopedic Cohorts.Scientific data · 2025Article
- A systematic review of real-world gait-related digital mobility outcomes in Parkinson's disease.NPJ digital medicine · 2025Article
- A New Methodological Approach Integrating Motion Capture and Pressure-Sensitive Gait Data to Assess Functional Mobility in Parkinson's Disease: A Two-Phase Study.Sensors (Basel, Switzerland) · 2025Article
- Wearable devices in neurological disorders: a narrative review of status quo and perspectives.Annals of translational medicine · 2025Review
- Gait instability is a more specific predictor of corticospinal tract function than gait speed in clinically stable multiple sclerosis.Scientific reports · 2025Article
40 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantifying gait and postural control adds valuable information that aids in understanding neurological conditions where motor symptoms predominate and cause considerable functional impairment. Disease-specific clinical scales exist; however, they are often susceptible to subjectivity, and can lack sensitivity when identifying subtle gait and postural impairments in prodromal cohorts and longitudinally to document disease progression. Numerous devices are available to objectively quantify a range of measurement outcomes pertaining to gait and postural control; however, efforts are required to standardise and harmonise approaches that are specific to the neurological condition and clinical assessment. Tools are urgently needed that address a number of unmet needs in neurological practice. Namely, these include timely and accurate diagnosis; disease stratification; risk prediction; tracking disease progression; and decision making for intervention optimisation and maximising therapeutic response (such as medication selection, disease staging, and targeted support). Using some recent examples of research across a range of relevant neurological conditions-including Parkinson's disease, ataxia, and dementia-we will illustrate evidence that supports progress against these unmet clinical needs. We summarise the novel 'big data' approaches that utilise data mining and machine learning techniques to improve disease classification and risk prediction, and conclude with recommendations for future direction.
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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.