Characterising Residual Limb Morphology and Prosthetic Socket Design Based on Expert Clinician Practice
Characterising Residual Limb Morphology and Prosthetic Socket Design Based on Expert Clinician Practice
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DOI：
10.3390/prosthesis3040027
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发表时间：
2021-12-01
期刊：
影响因子：
3.4
通讯作者：
Steer, Joshua
中科院分区：
文献类型：
--
作者：
Dickinson, Alexander;Diment, Laura;Steer, Joshua
功能齐全、舒适的假肢依赖于个性化的插座，目前的设计是采用专家主导的迭代过程，这可能既昂贵又不方便。计算机辅助设计和制造（CAD/CAM）提高了可重复性，但临床医生广泛的数字设计记录可以发挥更大的作用。使用智能模板的基于知识的插座设计可以整理成功的设计特征，并为新患者量身定制。基于67个残肢扫描和相应的套接字，本文开发了一种由专家假肢专家客观分析个性化设计方法的方法，使用机器学习：主成分分析（PCA）提取解剖和手术变异的关键类别，k-means聚类识别局部“纠正”设计特征。PCA自动识别了代表全表面承重和髌骨肌腱承重设计理念的矫正模式，揭示了符合临床指南的不同肢体形状的套孔设计选择的趋势。通过测量k-means聚类识别的局部修正的大小来量化专家设计实践。实现基于这些趋势的智能模板需要义肢专家的临床评估，而不是替代培训。该研究为基于人群的套孔设计分析提供了方法，并提供了示例数据，这将支持CAD/CAM临床实践的发展和生物力学研究的准确性。
Functional, comfortable prosthetic limbs depend on personalised sockets, currently designed using an iterative, expert-led process, which can be expensive and inconvenient. Computer-aided design and manufacturing (CAD/CAM) offers enhanced repeatability, but far more use could be made from clinicians' extensive digital design records. Knowledge-based socket design using smart templates could collate successful design features and tailor them to a new patient. Based on 67 residual limb scans and corresponding sockets, this paper develops a method of objectively analysing personalised design approaches by expert prosthetists, using machine learning: principal component analysis (PCA) to extract key categories in anatomic and surgical variation, and k-means clustering to identify local 'rectification' design features. Rectification patterns representing Total Surface Bearing and Patella Tendon Bearing design philosophies are identified automatically by PCA, which reveals trends in socket design choice for different limb shapes that match clinical guidelines. Expert design practice is quantified by measuring the size of local rectifications identified by k-means clustering. Implementing smart templates based on these trends requires clinical assessment by prosthetists and does not substitute training. This study provides methods for population-based socket design analysis, and example data, which will support developments in CAD/CAM clinical practice and accuracy of biomechanics research.