ArticleScientific reports2022
Explaining the differences of gait patterns between high and low-mileage runners with machine learning.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 5 of them syntheses that pooled it.
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Who cites it
85 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Effect of core strength training on the badminton player's performance: A systematic review & meta-analysis.PloS one · 2024Pooled it
- Biomechanical Risks Associated with Foot and Ankle Injuries in Ballet Dancers: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Mixed Comparison of Different Exercise Interventions for Function, Respiratory, Fatigue, and Quality of Life in Adults With Amyotrophic Lateral Sclerosis: Systematic Review and Network Meta-Analysis.Frontiers in aging neuroscience · 2022Pooled it
- A Mixed Comparison of Interventions for Kinesiophobia in Individuals With Musculoskeletal Pain: Systematic Review and Network Meta-Analysis.Frontiers in psychology · 2022Pooled it
- Sex-specific differences in biomechanics among runners: A systematic review with meta-analysis.Frontiers in physiology · 2022Pooled it
- Integrating statistical parametric mapping, functional principal component analysis, explainable machine learning, and equivalence testing for multimodal gait signal analysis.BMC biomedical engineering · 2026Article
- Biomechanical assessment of manual handling to enhance workplace safety based on gait and center of mass analysis.Scientific reports · 2026Article
- Recognition of Human Gait Under Asymmetric Loading.Sensors (Basel, Switzerland) · 2026Article
- AI-powered biomechanical modeling for ACL-reconstructed knees: predicting knee joint contact forces via computer vision and deep learning.Journal of neuroengineering and rehabilitation · 2026Article
- Effects of running distance on per-step and cumulative lower-extremity loading during a simulated treadmill half marathon.Frontiers in public health · 2026Article
- Optimizing wearable IMU configurations for running gait analysis: a machine learning-based sensor fusion approach.Frontiers in bioengineering and biotechnology · 2026Article
- Article
- Comparison of muscle activation and proprioception during landing at different angles between individuals with chronic ankle instability and healthy controls.BMC musculoskeletal disorders · 2025Article
- The effects of kinesiology taping on joint stability during descending stairs in patients with acute ankle injuries.BMC sports science, medicine & rehabilitation · 2025Article
- Entropy, Irreversibility, and Time-Series Deep Learning of Kinematic and Kinetic Data for Gait Classification in Children with Cerebral Palsy, Idiopathic Toe Walking, and Hereditary Spastic Paraplegia.Sensors (Basel, Switzerland) · 2025Article
- Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome.Scientific reports · 2025Article
- Analysis of Quadriceps Fatigue Effects on Lower Extremity Injury Risks During Landing Phases in Badminton Scissor Jump.Sensors (Basel, Switzerland) · 2025Article
- Exploring Lower Limb Biomechanical Differences in Competitive Aerobics Athletes of Different Ability Levels During Rotational Jump Landings.Bioengineering (Basel, Switzerland) · 2025Article
- Prediction of Vertical Ground Reaction Forces Under Different Running Speeds: Integration of Wearable IMU with CNN-xLSTM.Sensors (Basel, Switzerland) · 2025Article
- Article
25 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mileages. In recent years, machine learning algorithms have been used for pattern recognition and classification of gait features to emphasize the uniqueness of gait patterns. However, they all have a representative problem of being a black box that often lacks the interpretability of the predicted results of the classifier. Therefore, this study was conducted using a Deep Neural Network (DNN) model and Layer-wise Relevance Propagation (LRP) technology to investigate the differences in running gait patterns between higher-mileage runners and low-mileage runners. It was found that the ankle and knee provide considerable information to recognize gait features, especially in the sagittal and transverse planes. This may be the reason why high-mileage and low-mileage runners have different injury patterns due to their different gait patterns. The early stages of stance are very important in gait pattern recognition because the pattern contains effective information related to gait. The findings of the study noted that LRP completes a feasible interpretation of the predicted results of the model, thus providing more interesting insights and more effective information for analyzing gait patterns.
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