ArticleScientific data2020
GaiTRec, a large-scale ground reaction force dataset of healthy and impaired gait.
Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 80 citations in OpenAlex.
- Multibody dynamics-based musculoskeletal modeling for gait analysis: a systematic review.Journal of neuroengineering and rehabilitation · 2024Pooled it
- Dual-Model Artificial Intelligence Framework Integrating AI-Based Markerless Motion Capture for Dynamic Gait Prediction and Health-Status Classification.Diagnostics (Basel, Switzerland) · 2026Article
- Clinical Translation of Artificial Intelligence-Driven Gait Analysis Using Plantar Pressure and Ground Reaction Force.Bioengineering (Basel, Switzerland) · 2026Review
- Associations between knee extensor strength and gait characteristics derived from shoe-based wearable sensors in older women.Scientific reports · 2026Article
- Recognition of Human Gait Under Asymmetric Loading.Sensors (Basel, Switzerland) · 2026Article
- A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds.Scientific data · 2025Article
- Biomechanical Effects of a Passive Lower-Limb Exoskeleton Designed for Half-Sitting Work Support on Walking.Sensors (Basel, Switzerland) · 2025Article
- DeepLabCut custom-trained model and the refinement function for gait analysis.Scientific reports · 2025Article
- Data augmentation of time-series data in human movement biomechanics: A scoping review.PloS one · 2025Article
- Article
- A Preliminary Study on Kinetic Analysis of Ground Reaction Force and Impulse During Gait in Patients With Total Hip Replacement and Implication for Rehabilitation.Orthopaedic surgery · 2024Observational
- Modelling individual variation in human walking gait across populations and walking conditions via gait recognition.Journal of the Royal Society, Interface · 2024Article
- A Biomechanical Dataset of 1,798 Healthy and Injured Subjects During Treadmill Walking and Running.Scientific data · 2024Article
- Article
- Static versus dynamic muscle modelling in extinct species: a biomechanical case study of thePeerJ · 2024Article
- Reduced adaptability to balance perturbations in older adults with probable cognitive impairment after a severe fall.PloS one · 2024Article
- Deep Metric Learning for Scalable Gait-Based Person Re-Identification Using Force Platform Data.Sensors (Basel, Switzerland) · 2023Article
- Real-world measurements of ground reaction forces of normal gait of young adults wearing various footwear.Scientific data · 2023Article
- Explainable AI for clinical and remote health applications: a survey on tabular and time series data.Artificial intelligence review · 2023Article
- Modeling biological individuality using machine learning: A study on human gait.Computational and structural biotechnology journal · 2023Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The quantification of ground reaction forces (GRF) is a standard tool for clinicians to quantify and analyze human locomotion. Such recordings produce a vast amount of complex data and variables which are difficult to comprehend. This makes data interpretation challenging. Machine learning approaches seem to be promising tools to support clinicians in identifying and categorizing specific gait patterns. However, the quality of such approaches strongly depends on the amount of available annotated data to train the underlying models. Therefore, we present GAITREC, a comprehensive and completely annotated large-scale dataset containing bi-lateral GRF walking trials of 2,084 patients with various musculoskeletal impairments and data from 211 healthy controls. The dataset comprises data of patients after joint replacement, fractures, ligament ruptures, and related disorders at the hip, knee, ankle or calcaneus during their entire stay(s) at a rehabilitation center. The data sum up to a total of 75,732 bi-lateral walking trials and enable researchers to classify gait patterns at a large-scale as well as to analyze the entire recovery process of patients.
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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.