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Go to Editorial ManagerThe purpose of this research is to manufacture and test adjustable sockets for below-knee amputation. This article studies using the pnuematic–pads for adjustable sockets. The manufacturing of an adjustable socket with pneumatic pads goes through several stages: In the theoretical design of the adjustable socket, the suggested materials were studied for the pneumatic pads, tubes, and pneumatic pump which should be suitable for the suggested application. In the experimental work, using composite materials for manufacturing the socket consisting of perlon and resin to achieve the rigid shape and required flexibility for the prosthetic user with the pneumatic pads. After assembling the adjustable socket parts, the pneumatic pads, the pump and the tubes, the socket were tested for several times on the patient. In the last stage, the pressure between the socket and the residual limb was measured using F-socket, and it was found that the results were: anterior (160kPa), lateral (167kPa), posterior (153kPa) and medial (348kPa). By comparing these results with what was previously studied, the pressure between the socket and the residual limb is within the acceptable range. The design provides good suspension and more adaptability to the change in stump volume. A posative feedback was given by the patient who used the prosthetic patient for several days as a trial to measure its safety and comfortablty.
Recently, three-dimensional models 3DM in the prosthetics field gained popularity, especially in the context of residual limb shape creation resulting from collecting medical images in Digital Imaging and Communications in Medicine DICOM format from a magnetic resonance imaging MRI after image processing accurately. In this study, a three-dimensional model of the residual limb for a patient with transtibial amputation was realized with the integration of artificial intelligence and a computer vision approach demonstrating the benefits of AI segmentation tools and artificial algorithms to generate higher accuracy three-dimensional model before prosthetic socket design or in case of comparison the 3D model generated from MRI with another 3D model generated from another technique, where a residual limb of a 23 years old male patient with amputation in the left leg wearing a prosthetic socket liner, and having 62 kg weight, 168 cm height, with high activity level. The patient was scanned using GE Medical Systems, 1,5 Tesla Signa Excite. MRI images in DICOM format were read to retrieve essential metadata such as pixel spacing and slice thickness. These images were processed to obtain a model that reflects the real shape of the residual limb using a specific algorithm, and the 3D model was extracted using AI segmentation tools. The obtained 3D model result with high resolution proves the potential of the artificial intelligence approach with deep learning to reconstruct 3D models concluding that AI has an instrumental role in medical image analysis, particularly in the areas of organ and tissue classification and segmentation., thus generating automatic and repetitive a 3D model.