Estimating Body Volume and Height Using 3D Data
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913530196787200 |
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| author | Sonar, Vivek Ganesh Jan, Muhammad Tanveer Wells, Mike Pandya, Abhijit Engstrom, Gabriela Shih, Richard Furht, Borko |
| author_facet | Sonar, Vivek Ganesh Jan, Muhammad Tanveer Wells, Mike Pandya, Abhijit Engstrom, Gabriela Shih, Richard Furht, Borko |
| contents | Accurate body weight estimation is critical in emergency medicine for proper dosing of weight-based medications, yet direct measurement is often impractical in urgent situations. This paper presents a non-invasive method for estimating body weight by calculating total body volume and height using 3D imaging technology. A RealSense D415 camera is employed to capture high-resolution depth maps of the patient, from which 3D models are generated. The Convex Hull Algorithm is then applied to calculate the total body volume, with enhanced accuracy achieved by segmenting the point cloud data into multiple sections and summing their individual volumes. The height is derived from the 3D model by identifying the distance between key points on the body. This combined approach provides an accurate estimate of body weight, improving the reliability of medical interventions where precise weight data is unavailable. The proposed method demonstrates significant potential to enhance patient safety and treatment outcomes in emergency settings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_02800 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Estimating Body Volume and Height Using 3D Data Sonar, Vivek Ganesh Jan, Muhammad Tanveer Wells, Mike Pandya, Abhijit Engstrom, Gabriela Shih, Richard Furht, Borko Computer Vision and Pattern Recognition Artificial Intelligence Accurate body weight estimation is critical in emergency medicine for proper dosing of weight-based medications, yet direct measurement is often impractical in urgent situations. This paper presents a non-invasive method for estimating body weight by calculating total body volume and height using 3D imaging technology. A RealSense D415 camera is employed to capture high-resolution depth maps of the patient, from which 3D models are generated. The Convex Hull Algorithm is then applied to calculate the total body volume, with enhanced accuracy achieved by segmenting the point cloud data into multiple sections and summing their individual volumes. The height is derived from the 3D model by identifying the distance between key points on the body. This combined approach provides an accurate estimate of body weight, improving the reliability of medical interventions where precise weight data is unavailable. The proposed method demonstrates significant potential to enhance patient safety and treatment outcomes in emergency settings. |
| title | Estimating Body Volume and Height Using 3D Data |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2410.02800 |