ArticlePLoS computational biology2023
Discovering individual-specific gait signatures from data-driven models of neuromechanical dynamics.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- [Personalized lower-limb gait assessment method based on musculoskeletal modeling and machine learning].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Article
- Multidimensional biomechanical modulation of walking reveals a threshold decline in distal ankle propulsion across aging.European journal of applied physiology · 2026Article
- Wobble-Board Dynamics Identify Individual Signatures of Balance Control for Clinical Assessment.Annals of biomedical engineering · 2026Article
- Biomechanical Phenotyping of Forced Expiration for Precision Pulmonary Rehabilitation: A Machine Learning Approach to Identify Structural and Kinetic Drivers.Advances in respiratory medicine · 2026Article
- Loss of hand control expressiveness revealed by task- and individual-specificity in spatiotemporal finger coordination.bioRxiv : the preprint server for biology · 2026Article
- Neuromechanical gait signatures reveal holistic biomechanical responses to walking speed modulation in stroke survivors.Scientific reports · 2026Article
- The COMPWALK-ACL: A Dataset of Multi-pace IMU Gait Kinematics in Adolescents, Adults, and ACL Injured Patients.Scientific data · 2025Article
- Digital Pedoscopic Assessment and Data-Driven Classification of Pediatric Rearfoot Alignment.Children (Basel, Switzerland) · 2025Article
- Classifying simulated gait impairments using privacy-preserving explainable artificial intelligence and mobile phone videos.PLOS digital health · 2025Article
- Video-Based Biomechanical Analysis Captures Disease-Specific Movement Signatures of Different Neuromuscular Diseases.NEJM AI · 2025Article
- Explaining human motor coordination via the synergy expansion hypothesis.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Identification of Subtypes of Post-Stroke and Neurotypical Gait Behaviors Using Neural Network Analysis of Gait Cycle Kinematics.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025Article
- How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression.Applied sciences (Basel, Switzerland) · 2024Article
- Ethnokinesiology: towards a neuromechanical understanding of cultural differences in movement.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Gait signature changes with walking speed are similar among able-bodied young adults despite persistent individual-specific differences.Scientific reports · 2024Article
- Gait signature changes with walking speed are similar among able-bodied young adults despite persistent individual-specific differences.bioRxiv : the preprint server for biology · 2024Article
- Multi-Site Identification and Generalization of Clusters of Walking Behaviors in Individuals With Chronic Stroke and Neurotypical Controls.Neurorehabilitation and neural repair · 2023Article
- Multi-site identification and generalization of clusters of walking behaviors in individuals with chronic stroke and neurotypical controls.bioRxiv : the preprint server for biology · 2023Article
- A machine learning approach to quantify individual gait responses to ankle exoskeletons.bioRxiv : the preprint server for biology · 2023Article
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Authors and funding
6 authors.
Funding
Abstract
Locomotion results from the interactions of highly nonlinear neural and biomechanical dynamics. Accordingly, understanding gait dynamics across behavioral conditions and individuals based on detailed modeling of the underlying neuromechanical system has proven difficult. Here, we develop a data-driven and generative modeling approach that recapitulates the dynamical features of gait behaviors to enable more holistic and interpretable characterizations and comparisons of gait dynamics. Specifically, gait dynamics of multiple individuals are predicted by a dynamical model that defines a common, low-dimensional, latent space to compare group and individual differences. We find that highly individualized dynamics-i.e., gait signatures-for healthy older adults and stroke survivors during treadmill walking are conserved across gait speed. Gait signatures further reveal individual differences in gait dynamics, even in individuals with similar functional deficits. Moreover, components of gait signatures can be biomechanically interpreted and manipulated to reveal their relationships to observed spatiotemporal joint coordination patterns. Lastly, the gait dynamics model can predict the time evolution of joint coordination based on an initial static posture. Our gait signatures framework thus provides a generalizable, holistic method for characterizing and predicting cyclic, dynamical motor behavior that may generalize across species, pathologies, and gait perturbations.
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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.