Document Type : RESEARCH PAPER
Authors
1
Orthopedics Research Center, Department of Orthopedic Surgery, Mashhad University of Medical Sciences, Mashhad, Iran
2
Department of Biostatistics, School of Public Health, Mashhad University of Medical Sciences, Mashhad, Iran
3
Orthopedics Research Center, Department of Orthopedic Surgery, Mashhad University of Medical Sciences, Mashhad, Iran Bone and Joint Research Laboratory, Ghaem Hospital, Mashhad University of Medical Science, Mashhad, Iran Department
4
Orthopedic Research Center, Department of Orthopedic Surgery, Mashhad University of Medical Science, Mashhad, Iran Bone and Joint Research Laboratory, Ghaem Hospital, Mashhad University of Medical Science, Mashhad, Iran Faculty of
5
Orthopedics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
6
Orthopedic Research Center, Department of Orthopedic Surgery, Mashhad University of Medical Science, Mashhad, Iran.
10.22038/abjs.2024.73439.3435
Abstract
Objectives: An alternative to both the time-consuming traditional and the expensive three-dimensional (3D) methods for splint design is to use two-dimensional (2D) images. The present study utilized image processing to achieve an automatic and practical method of anthropometry measurement to design and build a personalized and remote cock-up splint. This method is applicable for patients unable to personally attend clinic appointments.
Methods: The defined landmarks of the cock-up splint of 100 adult participants were measured manually. Each individual had a 2D image taken of their upper limb using a customized imaging device. The 2D image portions that corresponded to the manual measurements were then identified, and their sizes were retrieved in pixels using MATLAB software. To find equations between manual 3D measurements and 2D image processing ones, multiple linear regression analysis was performed on landmark variables.
Results: We were able to determine equations to estimate manual dimensions based on 2D image data. In the men’s group, we could predict the third finger length, forearm circumference at three levels, and the largest forearm circumference. In the women’s group, in addition to variables predicted for men, hand circumference at the distal palmar crease and first web levels, as well as arm circumference, could be predicted using the identified equations.
Conclusion: Based on the findings, 2D image processing could be an appropriate method for designing personalized cock-up splints.
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