Abstract
Modern 3D scanning technologies have revolutionized various industries, including healthcare and biomedical engineering. This research explores the application of 3D scanning in the field of medicine, focusing on the representation of 3D hand data using the SIREN (Sinusoidal Representation Network) approach. 3D scanning plays a vital role in hand prosthetics, enabling the development of personalized models that accurately replicate the shape and size of real hands. This allows for the production of prostheses tailored to the specific needs of patients, facilitating their reintegration into active life. RealSense 3D cameras, developed by Intel, are among the leading technologies for 3D scanning. However, the effective utilization of implicit representation of 3D data, such as SIREN, presents challenges in ensuring compatibility with the features and limitations of existing 3D scanning technologies. This study analyses the potential of SIREN for 3D hand data representation, addressing the existing constraints and limitations. By leveraging the capabilities of RealSense cameras and the flexibility of SIREN, we aim to enhance the analysis and processing of 3D data, opening new avenues for prosthesis design.