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. We present OGA-AID, a clinician-in-the-loop multi-agent large language model system for multimodal report drafting. The system coordinates 3 specialized agents to synthesize patient movement recordings, kinematic trajectories, and clinical profiles into structured assessments. Evaluated with expert physiotherapists on real pat
The proliferation of advanced large language models and multi-agent systems is enabling the automation and augmentation of complex, data-rich processes like medical report generation.
This development represents a concrete application of AI agents in a high-stakes, knowledge-intensive domain, demonstrating their potential to improve clinical efficiency and patient outcomes.
Clinicians will be increasingly supported by AI systems that can integrate diverse data types and draft detailed reports, reducing manual burden and potentially standardizing assessment quality.
- · AI software developers
- · Healthcare providers
- · Patients undergoing rehabilitation
- · Tasks requiring manual data synthesis
- · Traditional medical report drafting services
Clinicians' time allocation shifts from report drafting to patient interaction and higher-level analysis.
Increased demand for robust data privacy and security measures as more sensitive patient data is processed by AI systems.
Evolution of medical training to incorporate AI-assisted workflows and critical evaluation of AI-generated content.
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Read at arXiv cs.AI