## 5 Discussion  
In this study, a new automatic process based on the GD for the CAD modeling and manufacturing of customized orthoses was developed, providing a useful instrument for clinicians with no experience with CAD systems. This novel approach has been specifically applied to the design of a customized wrist orthosis, enabling medical staff to conduct 3D acquisition without the need for a specialist throughout the entire procedure [23]. For the 3D acquisition phase, photogrammetry was utilized, leveraging the camera of a smartphone to capture approximately 130 photos of the patient's wrist from various angles [35]. This method proved efficient as it did not require external devices to stabilize the patient's limb, although a support system for positioning and securing the wrist can be provided depending on the specific pathology of each patient.  
A key feature of this work is the modeling process simplification of the orthosis, which could be accomplished by merely delineating the immobilization area with two lines. The algorithm then automatically generates the orthosis model, complete with ventilation holes. The prototype orthosis, fabricated from ABS using a 3D FDM printer, was evaluated by an orthopedist to assess its practical usability, including the reliability of the closure system and the fit to the scanned arm [4,36].  
The methodological approach employed in this study has significant potential for future research and application [19,30]. It could facilitate the development of an automated workflow capable of easily identifying the optimal shape for each individual patient. Parameters such as wrist width, finger length and width, and palm size, along with the required degree of immobilization, could be easily obtained and replicated, further simplifying the customization process. The integration of recent innovative technologies, such as artificial intelligence, could enhance the user-friendliness and accuracy of the proposed approach, making it even more accessible and precise [37].  
Figure 11: Final prototype. In the figure, the prototype shows the different phases reported in the method: operator-dependent cuttings, hand (a) and elbow side (b); lateral orthosis opening (c); patient-specific shape design; and holes for ventilation (d).  
Figure 12: Final prototype worn by the patient.  
Moreover, this approach offers substantial benefits in terms of time and cost efficiency [24]. By reducing the dependency on highly skilled technicians and minimizing the need for specialized equipment, the overall process becomes more streamlined and accessible. This can lead to broader adoption in clinical settings, particularly in regions where access to specialized CAD modeling expertise is limited.  
However, the developed method could present some actual limitations, such as the use of commercial closed scanning software that cannot provide the accuracy parameter, the reduced clinical tests performed, and the choice of the cutting planes that have operator dependence.  
Future studies could expand on this foundation by exploring the integration of advanced AI algorithms to optimize the design process further. Machine learning techniques could analyze a larger dataset of wrist orthosis designs and patient outcomes to identify patterns and predict the best design parameters for new patients. Additionally, incorporating feedback from a wider range of clinicians and patients can provide valuable insights to refine the system, ensuring that it meets diverse clinical needs effectively.  
The development of this automated process for the CAD modeling and manufacturing of customized orthoses represents a significant advancement in personalized medical care. By harnessing the power of generative design and user-friendly 3D acquisition methods, this approach holds the promise of improving patient outcomes, enhancing clinician efficiency, and democratizing access to high-quality custom orthotic solutions.