Evidence map›Paper›PMID 42317623›Full record

ArticleData in brief2026

A public dataset of treadmill walking kinematics and kinetics at steady speeds in healthy individuals.

L Le Goff, F Chorin, N Reneaud, D Fontaine, E Piche

Abstract read
In one paragraph

Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

L Le GoffDepartment of Physical Medicine and Rehabilitation, Princess Grace Hospital, Monaco.
F ChorinClinique Gériatrique du Cerveau et du Mouvement, University Hospital of Nice, Nice, France.
N ReneaudDepartment of Physical Medicine and Rehabilitation, University Hospital of Nimes, Le Grau-du-Roi, France.
D FontaineUR2CA, Côte d'Azur University, Nice, France.
E PicheClinique Gériatrique du Cerveau et du Mouvement, University Hospital of Nice, Nice, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human motion analysis is widely used in clinical practice to characterise motor function, gait impairments, and fall risk. However, available gait datasets are predominantly acquired at self-selected walking speeds and rarely include standardised slower speeds, despite their relevance for clinical populations. This article describes a publicly available dataset of three-dimensional gait kinematics and kinetics collected in healthy adults under controlled treadmill conditions. Forty-five participants, including young and older adults, performed walking trials at six predefined speeds ranging from 0.6 to 1.6 m·s⁻¹. Data acquisition was conducted using an optoelectronic motion capture system combined with an instrumented treadmill. The dataset includes three-dimensional marker trajectories, pelvis and lower limb joint kinematics in the sagittal, frontal, and transverse planes, as well as ground reaction forces, joint moments, and joint power. Raw data are provided in C3D format, and processed data are available as MATLAB-compatible files containing time-normalised gait cycles with associated mean values and variability metrics. The dataset is structured to allow comparisons across walking speeds and age groups, with consistent acquisition protocols and standardised processing pipelines. Supplementary files include statistical descriptors and detailed biomechanical variables across the gait cycle. In addition, a composite metric derived from gait kinematic data across multiple speeds is provided to support integrative analyses of gait patterns. This dataset can be reused for methodological development, validation of biomechanical models, and comparative analyses in both research and clinical contexts. The inclusion of standardised slow walking speeds and age-stratified data enables its use as a reference framework for evaluating gait patterns under conditions commonly encountered in clinical populations, including longitudinal assessments and comparisons with altered locomotor function.

Indexed as

Gait analysisGround reaction forcesLocomotion biomechanicsLongitudinal assessmentMotion captureNormative reference

Identifiers

PMID42317623
PMCPMC13273904

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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.