Movement Anywhere: An Open-Source Distributed 2D Video-Based Movement Analysis Platform Empowered by Active Learning.

Area of Science:

• Biomedical Engineering
• Clinical Biomechanics
• Medical Technology

Background:

• Movement analysis is crucial for diagnosing and monitoring neurodegenerative and musculoskeletal diseases.
• Traditional motion capture tools are expensive and require significant space, limiting accessibility.
• There is a need for cost-effective and accessible movement analysis solutions.

Purpose of the Study:

• To introduce Movement Anywhere, an open-source, distributed platform for 2D video-based movement analysis.
• To develop advanced tracking algorithms capable of handling patient assistance scenarios.
• To establish conditions for accurate depth information extraction for precise motion parameter estimation.

Main Methods:

• Developed an open-source, distributed platform utilizing 2D video analysis.
• Incorporated advanced tracking algorithms for robust patient assistance scenarios.
• Integrated an active learning framework for streamlined algorithm updates and adaptability to various 2D cameras.
• Established conditions for precise depth information extraction.

Main Results:

• Movement Anywhere demonstrates substantial improvements over previous methods in movement analysis.
• The platform provides cost-effective, scalable, extensible, and user-friendly disease monitoring.
• Advanced tracking handles scenarios requiring patient assistance.
• Accurate depth information extraction is achieved for precise motion parameter estimation.

Conclusions:

• Movement Anywhere offers a viable, accessible solution for movement analysis in clinical settings.
• The platform facilitates effective disease monitoring and progression tracking for neurodegenerative and musculoskeletal conditions.
• Open-source accessibility and adaptability enhance its utility in research and clinical practice.