TY - GEN
T1 - Customization and Analysis of Orthopedic Aids
AU - Praschl, Christoph
AU - Dalkilic, Mert
AU - Bauernfeind, Sophie
AU - Wakolbinger, Markus
AU - Zwettler, Gerald A.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025/4/24
Y1 - 2025/4/24
N2 - The provision of customized orthopedic aids, such as prostheses and orthoses, is essential for treating congenital malformations, chronic diseases, and musculoskeletal injuries. Traditionally, these aids have been crafted manually by skilled technicians. However, the advent of adaptive manufacturing techniques and digital methodologies, in the context of Industry 4.0, is revolutionizing this field. This paper explores the automated customization of orthopedic aids using a novel two-step pipeline that leverages digital scans and structural analysis. The first step involves adapting orthopedic aids based on 3D scans of the patient’s body, ensuring a precise fit. The second step employs the Finite Element Method (FEM) to analyze the structural integrity of these customized aids, focusing on aspects such as pressure distribution and heat conduction. While FEM has been extensively used in medical contexts to study human body structures, its application to the analysis of digitally customized orthopedic aids remains limited. The proposed methodology utilizes registered 3D meshes and reference skeletons to create patient-specific aids through an as-rigid-as-possible approach. The effectiveness of this process is evaluated by adapting a forearm and a foot orthosis based on patient-specific 3D scans. FEM analysis confirms that the customized aids maintain structural integrity comparable to their templates. This research demonstrates the feasibility of automated customization of orthopedic aids, paving the way for future applications involving a broader range of prostheses and orthoses, thereby enhancing the efficiency and accuracy of orthopedic treatments.
AB - The provision of customized orthopedic aids, such as prostheses and orthoses, is essential for treating congenital malformations, chronic diseases, and musculoskeletal injuries. Traditionally, these aids have been crafted manually by skilled technicians. However, the advent of adaptive manufacturing techniques and digital methodologies, in the context of Industry 4.0, is revolutionizing this field. This paper explores the automated customization of orthopedic aids using a novel two-step pipeline that leverages digital scans and structural analysis. The first step involves adapting orthopedic aids based on 3D scans of the patient’s body, ensuring a precise fit. The second step employs the Finite Element Method (FEM) to analyze the structural integrity of these customized aids, focusing on aspects such as pressure distribution and heat conduction. While FEM has been extensively used in medical contexts to study human body structures, its application to the analysis of digitally customized orthopedic aids remains limited. The proposed methodology utilizes registered 3D meshes and reference skeletons to create patient-specific aids through an as-rigid-as-possible approach. The effectiveness of this process is evaluated by adapting a forearm and a foot orthosis based on patient-specific 3D scans. FEM analysis confirms that the customized aids maintain structural integrity comparable to their templates. This research demonstrates the feasibility of automated customization of orthopedic aids, paving the way for future applications involving a broader range of prostheses and orthoses, thereby enhancing the efficiency and accuracy of orthopedic treatments.
KW - finite element method
KW - model transformation
KW - orthopedics
UR - https://www.scopus.com/pages/publications/105004255267
U2 - 10.1007/978-3-031-82957-4_32
DO - 10.1007/978-3-031-82957-4_32
M3 - Conference contribution
SN - 9783031829598
VL - 15173
T3 - Lecture Notes in Computer Science
SP - 380
EP - 387
BT - Computer Aided Systems Theory – EUROCAST 2024 - 19th International Conference, 2024, Revised Selected Papers
A2 - Quesada-Arencibia, Alexis
A2 - Affenzeller, Michael
A2 - Moreno-Díaz, Roberto
ER -