arXiv AI

Quantifying Rodda and Graham Gait Classification from 3D Markerless Kinematics derived from a Single-view Video in a Heterogeneous Pediatric Clinical Cohort

arXiv:2605. 11314v3 Announce Type: replace-cross Abstract: Cerebral Palsy (CP) is a neurological disorder of movement and the most common cause of lifelong physical disability in childhood.

Hugging Face Trending Papers
Jul 26

Markerless Motion Capture in Routine Clinical Upper Limb Assessments: Validity and Insights Beyond Ordinal Scoring

The Action Research Arm Test (ARAT) is a widely-used upper limb outcome measure in neurorehabilitation, but its ordinal scoring is subjective and suffers from limited sensitivity and specificity. We evaluated whether artificial-intelligence (AI)-based markerless motion capture (MMC), embedded into ARAT assessments during clinical routine, accurately reconstructs upper limb movement and yields valid, objective kinematic metrics carrying clinically meaningful information beyond the ordinal score.

arXiv Machine Learning
Jul 14

From Observed Viability to Internal Predictive Approximation: A Single-Subject Latent-Space Analysis of Gait Dynamics Under Occlusal Constraint

arXiv:2605. 15862v2 Announce Type: replace Abstract: Understanding adaptive biomechanical systems requires distinguishing observable performance, static multivariate representation, longitudinal displacement, and internal approximation of observed change.

By Jacques Raynal, Pierre Slangen, Elsa Raynal, Jacques Margerit
arXiv AI
Jun 8

OGA-AID: Clinician-in-the-loop AI Report Drafting Assistant for Multimodal Observational Gait Analysis in Post-Stroke Rehabilitation

arXiv:2604. 05360v2 Announce Type: replace-cross Abstract: Gait analysis is essential in post-stroke rehabilitation but remains time-intensive and cognitively demanding, especially when clinicians must integrate gait videos and motion-capture data into structured reports.

By Khoi T. N. Nguyen, Nghia D. Nguyen, Hui Yu Koh, Patrick W. H. Kwong, Karen Sui Geok Chua, Ananda Sidarta, Baosheng Yu
arXiv AI
Jun 2

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video

arXiv:2606. 02301v1 Announce Type: cross Abstract: Chronic pain diminishes quality of life by decreasing functional ability, yet objectively measuring this functional impact remains challenging in real-world settings.

By Pranav Mahajan, Amanda Wall, Eleonora Maria Camerone, Julie Stebbins, Eoin Kelleher, Shuangyi Tong, Annina Schmid, Katja Wiech, Anushka Irani, Ben Seymour
arXiv AI
Jul 1

Quantitative Movement Testing: Measuring Chronic Pain Patient Movements from a Single Smartphone Video

arXiv:2606. 02301v2 Announce Type: replace-cross Abstract: Chronic pain diminishes quality of life by decreasing functional ability, yet objectively measuring this functional impact remains challenging in real-world settings.

By Pranav Mahajan, Amanda Wall, Eleonora Maria Camerone, Julie Stebbins, Eoin Kelleher, Shuangyi Tong, Annina Schmid, Katja Wiech, Anushka Irani, Ben Seymour
arXiv Machine Learning
Jul 14

From Performance to Representational Adequacy: A Representational Bootstrap Framework for Adaptive Biological Systems

arXiv:2606. 01374v3 Announce Type: replace Abstract: Observable performance is commonly used to characterize biological systems, yet aggregated outputs may remain insufficient for uniquely resolving observational conditions, and richer multivariate representations may retain substantial ambiguity.

By Jacques Raynal, Pierre Slangen, Elsa Raynal, Jacques Margerit
arXiv Machine Learning
Jun 9

QDSP: An Interpretable Structured Learning Framework for Predicting Death or Cerebral Palsy in Very Low Birth Weight Infants

arXiv:2606. 07606v1 Announce Type: new Abstract: Very low birth weight infants (VLBWI) are at high risk of mortality and severe neurodevelopmental impairment, including cerebral palsy, yet reliable discharge-time prognostic stratification remains challenging in high-dimensional and data-limited clinical settings.

By Ling Wang, Xiaolong Li, Hui Zhou, Jing Shi, Fuhao Zhang, Dapeng Chen, Nan Mu