The prosthetic interface consists of a compliant liner and rigid socket, and conventionally has been made through a very hands-on artisinal process. This project has developed a prosthetic interface design and manufacturing pipeline that uses a novel computational algorithm to create subject-specific transtibial liner and socket components that can be additively manufactured at low cost. The novel interfaces are compared to conventional counterparts through a clinical trial that involves kinematic gait, pressure, and thermal metrics as well as a qualitative feedback questionnaire.
The design process consists of the following. The residual limb is imaged using a magnetic resonance imaging (MRI) device, and the image set is segmented into a three-dimensional model. This approach is superior to other 3D-modeling prosthetic interface techniques as it is able to capture bone geometries and soft tissue depths of the residuum. A more accurate topology of the skin is captured using digital image correlation (DIC), and this mesh is used in replacement of the MRI skin. The socket is divided into four distinct pressure regions, and the nominal pressure applied at each region can be adjusted to be patient-specific. Finite element analysis is run to simulate liner donning and bodyweight loading upon the interface to generate the final pressure map and liner-socket geometries. Manual modifications to the mesh can be made based on subject feedback. The final model is then sent for fabrication via 3D printing.
Clinical evaluation involves several steps. The subject conducts a 5 minute walking trial on one randomly selected prosthetic interface (conventional or novel), during which three data captures are taken. Gait parameters are extracted from these collections. Immediately after walking, the subject doffs the interface and thermal images are taken. The subject is then allowed to rest for 10-15 min and the process is repeated on the other interface. After these tests, the pressure test is conducted by taping sensors to the residuum and having the subject stand on their affected leg. The final step is the completion of the questionnaire, which asks the subject to compare the comfort of the novel interface to their conventional.
The findings and results of this project have many beneficial applications in the prosthetics industry. The pipeline reduces the amount of required in-person time from the patient, as design can be done remotely once the image set is obtained. This will help those who do not have the time or means to travel to a prosthetic clinic often. The design algorithm also retains a memory of subject-specific liner and socket preferences, so that future sockets built on the algorithm are more likely to be comfortable on the first try. This will reduce repetition in the interface design process, shortening the lead times for comfortable sockets and allowing more patients to be seen. 3D printing from a digital model shortens the time and reduces the cost for check sockets, and by printing multiple check socket variations a patient will have the opportunity to directly compare different socket designs. We hope that the host of benefits from this design method will enable better prosthetic comfort and care for all people with amputation, and will have a profound effect on those in developing countries.