In trans-tibial prostheses the interface between the residual limb and prosthetic socket is not always flush. This misalignment creates added pressure on the residual limb which causes greater discomfort, skin lesions, and muscle atrophy. This problem recurs as the residual limb heals and grows.

Even with a proper initial fit, short-term changes create new discomfort. The volume of the residual limb changes over time, and even throughout the day, making an accurate fit even more difficult. Since the current socket fabrication process involves a great deal of trial-and-error we found that it is not unusual for a patient to require three or four appointments just to get an initial socket fit. Some patient can require more than ten prosthetic sockets just to find an initial fit. To make matters worse, constant follow-up appointments and re-fittings are necessary as a patient's lifestyle changes.

It is estimated that as many as 41% of trans-tibial amputees suffer from poorly fit sockets. This problem is more relevant today than ever as it is projected that the amputee population will more than double by the year 2050 to 3.6 million, primarily due to diabetes patients who are also at risk for peripheral neuropathy. While most amputees can communicate their socket comfort during the fitting process, creeping nerve damage in patients with peripheral neuropathy makes it difficult or impossible for them to detect the misalignment. Since this nerve damage occurs slowly over time the problem of poor socket-fit has become more widespread as the life-expectancy of patients with peripheral neuropathy increases.
The ADAPT™ Prosthetic Platform solves the problem of poor socket-fit using Industry 4.0 techniques to collect patient data, monitor comfort, and generate new, custom designs as needed.

The ADAPT Smart Sock measures key pressure points between the residual limb and socket lining. An array of force sensitive resistors are sewn into the spandex sock and their readings are taken on a microprocessor embedded in the prosthetic shin. This data is sent wirelessly to the ADAPT Patient Portal and can be used to monitor patient health and inform prosthetic design. A prosthetic technician can use the Patient Portal to generate new socket and foot concepts based on a patient's particular needs and lifestyle. By applying generative design and finite-element-analysis to the data collected, the Patient Portal can automatically simulate hundreds of design studies to arrive at a solution that is truly unique to the end user.

Since there are already countless prosthetic redesigns we decided to use this project to instead rethink the process by which a patient interacts with their prosthetist and technician. Prosthetics need to be custom made to best fit their end user, but the current techniques for arriving at an end solution rely heavily on trial-and-error and anecdotal research. We sought to instead envision an end-to-end platform that used connected services to inform generative design studies. The ADAPT™ Prosthetic Platform solves the problem of poor socket-fit using Industry 4.0 techniques to collect patient data, monitor comfort, and generate new, custom designs as needed.

The ADAPT Smart Sock measures key pressure points between the residual limb and socket lining. An array of force sensitive resistors are sewn into the spandex sock and their readings are taken on a microprocessor embedded in the prosthetic shin. This data is sent wirelessly to the ADAPT Patient Portal and can be used to monitor patient health and inform prosthetic design. A prosthetic technician can use the Patient Portal to generate new socket and foot concepts based on a patient's particular needs and lifestyle. By applying generative design and finite-element-analysis to the data collected, the Patient Portal can automatically simulate hundreds of design studies to arrive at a solution that is truly unique to the end user.

Generative design is a process by which hundreds or thousands of new form studies and design concepts are developed as genetic variations of eachother through mutation and crossovers. A design criteria is used to refine the concepts down in increasingly favorable generations until arriving at an optimal solution. Because these studies are done digitally the entire ideation phase of a design can happen in minutes.
For the purposes of our proof-of-concept we used Dynamo Studio's visual programming language Primer to create logic-driven parametric conceptual designs. Each parametric property of the template foot, including the Keel Height, Heel Distance, Spring Height, Midfoot Arc Height, Midfoot Arc Weight, and multipliers of each, is then seeded with random data to generate a wide sampling of first generation options. As can be seen in our attached images, many of these first generation feet are so primitive they did not even result in actual 3D geometry. These options are refined through user selection of preferential results, the inputs of which are then randomized and used to seed the subsequent generations
Once an acceptable level of refinement has been reached (in our case usable geometry began to emerge around the fourth generation and was determined acceptable by the sixth generation) the resulting models can be exported to FEA simulation software to be analyzed against the data collected from the Smart Socket. For the purposes of this demonstration the downward force from the residual limb, as measure in the Smart Socket, was chosen as the simulation input. In practice, a prosthetics doctor– called a prosthetist– might choose to use simulation inputs specific to a patient's lifestyle. For a ballet dancer, for instance, a combination of angular velocity, rotational inertia, and angular momentum forces might be used to simulate a pirouette or other special case. We envision prosthetists could work with patients to create several specialized prosthetics designed specifically to their lifestyle or specific activities.
The design of our proof-of-concept foot was informed by our generative design process using a combination of actual patient data and simulation data. In this case the keel and lower are uniquely joined together at the midfoot and the heel is heavily reinforced. In practice this is an "open design" since the results would vary for each patient.