ArticleData in brief2023
Dataset of 3D gait analysis in typically developing children walking at three different speeds on an instrumented treadmill in virtual reality.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Gait Analysis in Rett Syndrome: Integrating Linear and Nonlinear Techniques.Journal of child neurology · 2026Article
- Integrating cognitive-behavioral training with immersive virtual reality intervention in ADHD: a case report.Frontiers in psychiatry · 2026Article
- Predicting normative walking biomechanics across the lifespan using seven simple features.Journal of neuroengineering and rehabilitation · 2025Article
- Evolution of joint power across the lifespan during walking.Journal of neuroengineering and rehabilitation · 2025Article
- Self-supervised learning enhances accuracy and data efficiency in lower-limb joint moment estimation from gait kinematics.Frontiers in bioengineering and biotechnology · 2025Article
- The Effect of a New Generation of Ankle Foot Orthoses on Sloped Walking in Children with Hemiplegia Using the Gait Real Time Analysis Interactive Lab (GRAIL).Bioengineering (Basel, Switzerland) · 2024Article
- 3D gait analysis in children using wearable sensors: feasibility of predicting joint kinematics and kinetics with personalized machine learning models and inertial measurement units.Frontiers in bioengineering and biotechnology · 2024Article
- Human Pose Estimation for Clinical Analysis of Gait Pathologies.Bioinformatics and biology insights · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this article, gait data of typically developing (TD) children (24 boys/31 girls, mean (95% confidence interval) age 9.38 (8.51 - 10.25) years, body mass 35.67 (31.40 - 39.94) kg, leg length 0.73 (0.70 - 0.76) m, and height 1.41 (1.35 - 1.46) m) walking at different walking speeds is shared publicly. Raw and processed data is presented for each child separately and includes data of each single step of both legs. Beside, the subject demographics and the results from the physical examination are presented allowing to select TD children from the database to create a matched group, based on specific parameters (e.g. sex and body weight). For clinical application, gait data is also presented per age group, which provides quick insight into the normal gait pattern of TD children of varying age. Gait analysis was performed during treadmill walking in a virtual environment using the Computer Assisted Rehabilitation Environment (CAREN). The human body lower limb model with trunk markers (HBM2) was used as biomechanical model. Children walked at comfortable walking speed, 30% slower and 30% faster (random sequence) while wearing gymnastic shoes and a safety harness to prevent falling. For each speed condition, 250 steps were recorded. Data quality check, step detection and the calculation of gait parameters was done by custom made Matlab algorithms. Raw data files are provided per walking speed, for each child separately. The raw data is exported from the CAREN software (D-flow) and is provided in .mox and .txt files. It includes the output from the models such as subject data, marker and force data, kinematic data (joint angles), kinetic data (joint moments, GRFs, joint powers), as well as CoM data and EMG data (the last two are not described in this manuscript), for each speed condition and each child. Unfiltered and filtered data are included. C3D files with raw marker and GRF data were recorded in Nexus (Vicon software) and are available upon request. After analyzing the raw data into Matlab (R2016a, Mathworks) using custom made Matlab algorithms, processed data is obtained. The processed data is provided in .xls files and is also presented for each child separately. It contains spatiotemporal parameters, 3D joint angles, anterior-posterior and vertical ground reaction forces (GRF), 3D joint moments and sagittal joint power of each step of the left and right leg. In addition to each individual's data, overview files (.xls) are created per walking speed condition. These overviews present the averaged gait parameter (e.g. joint angle), calculated over all valid steps, of each child.
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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.