Daliri Mahla, Rajabi Mahla, Rastaghi Sedigheh, Ataei Mehdi, Meybodi Mona, Jirofti Nafiseh, Mohadesi Mohadeseh, Jahani Afsaneh, Moradi Ali
Orthopedics Research Center, Department of Orthopedic Surgery, Mashhad University of Medical Sciences, Mashhad, Iran.
Department of Biostatistics, School of Public Health, Mashhad University of Medical Sciences, Mashhad, Iran.
Arch Bone Jt Surg. 2024;12(9):622-630. doi: 10.22038/ABJS.2024.73439.3435.
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.
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.
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.
Based on the findings, 2D image processing could be an appropriate method for designing personalized cock-up splints.
夹板设计中，耗时的传统方法和昂贵的三维（3D）方法之外的另一种选择是使用二维（2D）图像。本研究利用图像处理实现一种自动且实用的人体测量方法，以设计和构建个性化远程伸腕夹板。该方法适用于无法亲自到诊所就诊的患者。
对100名成年参与者的伸腕夹板的定义标志点进行手动测量。每个个体使用定制成像设备拍摄其上肢的2D图像。然后识别与手动测量相对应的2D图像部分，并使用MATLAB软件以像素为单位获取其大小。为了找到手动三维测量与二维图像处理测量之间的方程，对标志点变量进行多元线性回归分析。
我们能够确定基于2D图像数据估计手动尺寸的方程。在男性组中，我们可以预测第三指长度、三个水平的前臂周长以及最大前臂周长。在女性组中，除了男性组预测的变量外，还可以使用所确定的方程预测远侧掌横纹和第一蹼水平的手周长以及上臂周长。
基于这些发现，二维图像处理可能是设计个性化伸腕夹板的合适方法。
