Comparative Validation of a 3D Synthetic Data Approach for At-risk Patient Monitoring with Computer Vision: An Analysis of Frameworks and Strategies
https://doi.org/10.66967/jaics.2026.v2i105
Abstract
Training Computer Vision (CV) models for patient monitoring in clinical settings, such as rehabilitation beds, is often hindered by the impracticality of collecting real-world image data for at-risk scenarios. This study proposes and validates a methodology based on generating a synthetic dataset using 3D modeling. A virtual environment replicating a Reconfigurable Assistive Technology Platform (
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