OGA-AID: Clinician-in-the-loop AI Report Drafting Assistant for Multimodal Observational Gait Analysis in Post-Stroke Rehabilitation
Summary: arXiv:2604.05360v1 Announce Type: 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 patient data, OGA-AID consistently outperforms single-pass multimodal baselines with low error. In clinician-in-the-loop settings, brief expert preliminary notes further reduce error compared to reference assessments. Our findings demonstrate the feasibility of multimodal agentic systems for structured clinical gait assessment and highlight the complementary relationship between AI-assisted analysis and human clinical judgment in rehabilitation workflows.
Introduction
Post-stroke rehabilitation requires precise and efficient gait analysis to facilitate patient recovery. Traditionally, clinicians spend considerable time interpreting gait videos and motion-capture data, which can be mentally taxing and prone to error. The introduction of AI technologies promises to streamline this process, allowing clinicians to focus on patient care while ensuring accurate assessments.
Overview of OGA-AID
OGA-AID stands for Observational Gait Analysis Aid, a sophisticated system designed to assist clinicians in drafting reports by leveraging advanced AI techniques. The system employs a clinician-in-the-loop approach, meaning that human insights are integrated into the AI’s functioning to enhance accuracy and reliability.
Key Features of OGA-AID
- Multi-Agent Coordination: OGA-AID utilizes three specialized agents that work together to synthesize various data types.
- Integration of Multimodal Data: The system combines patient movement recordings, kinematic trajectories, and clinical profiles to create comprehensive reports.
- Expert Evaluation: OGA-AID has been evaluated by physiotherapists on actual patient data, validating its efficacy in real-world settings.
- Enhanced Accuracy: The system has demonstrated consistently lower error rates compared to traditional single-pass multimodal approaches.
- Clinician Feedback Loop: Incorporating brief expert preliminary notes further minimizes errors, emphasizing the importance of human judgment in the assessment process.
Results and Evaluation
The evaluation of OGA-AID involved collaboration with expert physiotherapists, who tested its functionality using real patient data. The results indicated that the AI-assisted system significantly outperformed conventional methods, showcasing its potential as a reliable tool for gait analysis in rehabilitation settings.
Conclusion
OGA-AID represents a significant advancement in the integration of AI technologies within clinical environments. Its ability to assist clinicians in drafting structured gait assessments not only enhances efficiency but also supports better patient outcomes. By emphasizing the collaborative nature of AI and human expertise, OGA-AID sets a precedent for future developments in rehabilitation technologies.
Future Directions
As AI technology continues to evolve, further research will focus on refining the capabilities of OGA-AID and exploring its application across different areas of rehabilitation. The goal is to create a more intuitive and user-friendly interface while maintaining the high standards of accuracy and efficiency that OGA-AID has already achieved.