arXiv AI June 8, 2026 By Khoi T. N. Nguyen, Nghia D. Nguyen, Hui Yu Koh, Patrick W. H. Kwong, Karen Sui Geok Chua, Ananda Sidarta, Baosheng Yu

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

Read the original on arXiv AI →

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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning

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Enhancing Clinician Decision-Making via Uncertainty-Aware Multi-Expert Fusion for Stroke Rehabilitation

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arXiv Machine Learning

Jul 23

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arXiv AI

Jun 30

Digitizing Coaching Intelligence: An Agentic Framework for Holistic Athlete Profiling using VLM and RAG

arXiv:2606. 28570v1 Announce Type: cross Abstract: Athlete assessment is a critical process for tracking physical progress and identifying elite talent.

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llms rag agents computer-vision multimodal safety data-engineering

arXiv Machine Learning

Jun 29

Cross-view Multimodal Vision-Based Assessment Framework for Traditional Chinese Medicine Rehabilitation Training

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arXiv AI

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arXiv Machine Learning

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Autonomous Telerehabilitation via Skeletal Motion Prediction and Joint-Level Performance Assessment

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By Lara Pereira, Jo\~ao Ruivo Paulo, Pedro Santos, Paulo Peixoto

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