ArticleBehavior research methods2026
Walking towards the future: Exploring OpenTUG's validity in automatic walking activity analyses and the relationship to cognition in vestibular patients.
Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Vestibular disorders impair body orientation and spatial navigation, often causing cognitive and affective symptoms, reducing quality of life. Traditional assessments involve time-consuming physiological and neuropsychological evaluations. This study investigates the feasibility and validity of applying a 2D human pose estimation (OpenTUG) to automatically analyze the walking activity of patients with vestibular disorders. Forty-eight patients undergoing treatment for vestibular disorders and 26 mean age-matched controls performed the TUG at normal, slow, and fast walking speeds; neuropsychological evaluations assessing attention, and quality-of-life questionnaires. Patients required significantly more time and steps to complete the TUG than controls at normal and slow speeds (e.g., normal speed: 7319 ms vs. 5976 ms, p = .002). Automated OpenTUG and manual analyses were highly correlated (time: all r > .94, p < .001; steps: all r > .74, p < .001). Patients reported higher dizziness-related handicap (median DHI total: 30 vs. 0, p < .001) and psychological symptoms (median HADS total: 12 vs. 8, p = .005). Exploratory analyses revealed moderate correlations between TUG measures and attentional performance (Spearman's r = .30-.54, p < .05-.01), as well as postural stability indices (e.g., unstable platform with eyes open: r = .38-.57, p < .05-.01). These findings demonstrate the feasibility and validity of using OpenTUG to automatically extract clinically relevant gait parameters. The observed associations between TUG performance, attentional measures, and postural stability highlight the potential of combining simple walking tasks with pose estimation as a rapid, cost-effective preliminary assessment of vestibular patients' difficulties.
Indexed as
Identifiers
41860683What 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.