Development and validation of a morphable human forearm model based on 3D surface scans: enabling semi-automated design of patient-specific splints for military and civilian acute care

Three-dimensional (3D) printed, patient-specific splints may offer an alternative for conventional immobilization methods by enhancing comfort, aeration, and hygiene. However, their broader clinical use remains limited by the complexity of current design workflows. Most existing workflows depend on 3D scans processed with commercial software and on manual or semi-automated CAD procedures that are difficult to reproduce, time-intensive, and often require pot-fit adjustments that are challenging to implement. A scalable modeling framework capable of capturing the substantial anatomical variability of the human forearm is needed to support more automated design pipelines. Morphable models address these limitations by establishing dense point-to-point correspondence across anatomical meshes, enabling a reference shape with fixed topology to deform through a set of parameters to approximate individual anatomies accurately. This study developed and validated a morphable forearm model using 200 structured light scans from 100 healthy adults (41 ± 19 years). Mesh preprocessing, anatomical alignment, and iterative registration were performed using a standardized framework, after which a statistical shape model was constructed and evaluated by comparing deformed mean shapes to original geometries using vertex-to-surface distance metrics. The model achieved a mean reconstruction error of 0.05 ± 0.11 mm, with the largest deviations near mesh boundaries at the hand and upper arm. These results demonstrate that the morphable model accurately represents forearm shape variability and provides a reproducible foundation for semi-automated, patient-specific splint design, thereby supporting the more efficient and clinically scalable implementation of 3D-printed immobilization solutions.