Work

Smartphone-Based Automated Photogrammetry for Reconstruction of Residual Limb Models in Prosthetic Design

Year: 2026

Type: article

Abstract: Accurate modeling of residual limb geometry is essential for prosthetic socket design, yet current scanning techniques can be costly, operator-dependent, or impractical for repeated clinical use. This study presents a fully automated, low-cost photogrammetry workflow capable of generating metrically accurate 3D models of lower-limb residual limbs using video and still images acquired with a standard smartphone or a full-frame digital camera. The pipeline integrates adaptive frame selection, deep learning-based background removal, robust metric scaling via ArUco markers, and open-source Structure-from-Motion and Multi-View Stereo reconstruction, requiring no manual post-processing or proprietary software. Accuracy and repeatability were evaluated using four 3D-printed limb phantoms and high-resolution CT-derived meshes as ground truth. Smartphone video and full-frame camera acquisitions achieved sub-millimeter surface accuracy, volume and perimeter errors within ±1%, and high inter-session repeatability, all within clinically accepted thresholds for prosthetic socket fabrication. In contrast, smartphone still-photo reconstructions showed larger deviations and reduced stability. Acquisition time was under five minutes, and complete reconstruction required approximately 1 h and 30 min. These results demonstrate that smartphone video-based photogrammetry provides a practical, scalable, and clinically viable alternative for residual limb modeling, particularly in resource-constrained or remote care settings.

Source: Sensors

DOI: 10.3390/s26041251

Authors: Lander De Waele, Jolien Gooijers, Dante Mantini

Institution: KU Leuven

Language: English

Topic: 3D Surveying and Cultural Heritage

Subfield: Geology

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,137