SynthesisBrain and behavior2021
Which features of postural sway are effective in distinguishing Parkinson's disease from controls? A systematic review.
Synthesis in Brain and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Which features of postural sway are effective in distinguishing Parkinson's disease from controls? A systematic review.Brain and behavior · 2021Pooled it
- Frequency-based deep learning to identify subtle postural instability in early, untreated Parkinson's disease.NPJ Parkinson's disease · 2026Article
- From RGB-D to RGB-Only: Reliability and Clinical Relevance of Markerless Skeletal Tracking for Postural Assessment in Parkinson's Disease.Sensors (Basel, Switzerland) · 2026Article
- Using Loss of Balance to Understand Postural Instability Associated With Parkinson's Disease.Parkinson's disease · 2026Article
- High-Accuracy Classification of Parkinson's Disease Using Ensemble Machine Learning and Stabilometric Biomarkers.Neurology international · 2025Article
- Sway frequencies may predict postural instability in Parkinson's disease: a novel convolutional neural network approach.Journal of neuroengineering and rehabilitation · 2025Article
- Motor actions across psychiatric disorders: A research domain criteria (RDoC) perspective.Clinical psychology review · 2024Review
- A Comparison among Different Strategies to Detect Potential Unstable Behaviors in Postural Sway.Sensors (Basel, Switzerland) · 2022Article
- Critical evaluation of the benefits and limitations of foam posturography in vestibular disorders: a narrative review.Frontiers in neurologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPostural sway may be useful as an objective measure of Parkinson's disease (PD). Existing studies have analyzed many different features of sway using different experimental paradigms. We aimed to determine what features have been used to measure sway and then to assess which feature(s) best differentiate PD patients from controls. We also aimed to determine whether any refinements might improve discriminative power and so assist in standardizing experimental conditions and analysis of data.
methodsIn this systematic review of the literature, effect size (ES) was calculated for every feature reported by each article and then collapsed across articles where appropriate. The influence of clinical medication status, visual state, and sampling rate on ES was also assessed.
resultsFour hundred and forty-three papers were retrieved. 25 contained enough information for further analysis. The most commonly used features were not the most effective (e.g., PathLength, used 14 times, had ES of 0.47, while TotalEnergy, used only once, had ES of 1.78). Increased sampling rate was associated with increased ES (PathLength ES increased to 1.12 at 100 Hz from 0.40 at 10 Hz). Measurement during "OFF" clinical status was associated with increased ES (PathLength ES was 0.83 OFF compared to 0.21 ON).
conclusionsThis review identified promising features for analysis of postural sway in PD, recommending a sampling rate of 100 Hz and studying patients when OFF to maximize ES. ES complements statistical significance as it is clinically relevant and is easily compared across experiments. We suggest that machine learning is a promising tool for the future analysis of postural sway in PD.
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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.