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Recognition of Forward Head Posture Through 3D Human Pose Estimation With a Graph Convolutional Network: Development and Feasibility Study

Recognition of Forward Head Posture Through 3D Human Pose Estimation With a Graph Convolutional Network: Development and Feasibility Study

The primary contributions of our work are 2-fold: first, we formulated an FHP detection system using recent computational techniques and developed a graph convolutional network (GCN)–based robust algorithm specifically designed to recognize FHP from 3 D human posture estimated from 2 D images. Second, through our comprehensive experimental validation, we established the reliability and accuracy of our method in a real-world context.

Haedeun Lee, Bumjo Oh, Seung-Chan Kim

JMIR Form Res 2024;8:e55476