How generative design is reshaping prosthetic limbs for athletes
American athlete Mike Schultz designing in Autodesk Fusion (photo: Autodesk)
Denise Schindler wanted a cycling prosthesis she could train in comfortably, without sacrificing performance. Spending hours turning the pedals meant that the fit of the connection between her body and bicycle was fundamental to every ride.
The German para-cyclist was already a Paralympic medallist when she began working with Autodesk, the US design and engineering software company, on a different way to make her sports prosthesis. Together, they combined digital scanning, computer modelling and generative design to develop a lighter, 3D-printed limb.
That work reached the sporting stage in 2016, when Schindler competed at the Rio Paralympics with a printed prosthesis and returned with silver in the time trial and bronze in the road race. She also earned a Guinness World Records entry for the first use of a 3D-printed prosthetic limb at the Games.
Her results reflected an athlete’s years of preparation, with the engineering team contributing equipment developed around the demands of her sport.
A 3D-printed cycling prosthesis, developed in 52 versions
Making Schindler’s previous prosthesis had involved plaster casting and weeks of skilled manual refinement. The new approach began with a scan of her residual limb, giving collaborators in Germany, Britain and the United States a digital model to work from.
They explored 52 digital versions, using Fusion 360 software to develop the design and Autodesk Within’s generative design capabilities to help reduce its weight before printing.
According to Autodesk, the combined workflow could shorten a process of around ten weeks to as little as five days, at roughly a quarter of the cost. These were project-specific figures, but they illustrated the potential of bringing scanning, design and manufacturing closer together.
Schindler’s experience remained central throughout: comfort was her priority, and a promising design needed to work through long training sessions. Her feedback helped connect what the team could calculate with what she could comfortably ride.
How generative design works
Generative design uses computational methods to explore possible designs within requirements set by engineers. Those requirements might include attachment points, expected forces, available materials and an objective such as reducing weight while maintaining sufficient strength.
To picture the process, imagine redesigning a bracket connecting two parts of a prosthetic limb. Its bolts must stay in specific positions, there must be room for movement, and the component must withstand the loads expected during use.
The engineer gives the software these conditions, allowing it to explore candidate shapes. Some may resemble branching bones or narrow ribs, with openings where a conventional component would contain solid material.
A useful way to understand those shapes is to imagine routes through which forces travel between the attachment points. Material supports those routes, while areas contributing less to the required performance may offer opportunities to save weight.
The manufacturing method also shapes the result. A component suitable for 3D printing might be difficult to cut from a block of metal, so production requirements become part of the design brief.
Once the options are available, engineers select and refine a candidate for further analysis, manufacture and physical testing. Generative design broadens their search, while their judgement—and feedback from the wearer—helps determine which ideas should become equipment.
Mike Schultz’s route from racing to prosthetic design
For American athlete Mike Schultz, the design brief came from a deeply personal ambition: returning to the sports he loved.
A snowmobile racing accident in 2008 led to the amputation of his left leg above the knee. When the available prosthetic equipment could not handle the riding he wanted to do, he turned to skills he already had.
His background in fabrication and racing suspension helped him develop a prosthetic knee with the movement and impact resistance his activities demanded. As interest grew, he founded BioDapt in 2010 to make equipment for other people.
The company’s Moto Knee uses a shock, air spring and mechanical linkage to manage bending and extension, with adjustable resistance and damping for different activities and conditions. There is a familiar principle behind it for anyone who rides a mountain bike: controlled suspension helps absorb impacts while supporting the rider’s movements.
For Schultz, seeing another person use his invention brought home how far that principle could reach.
Equipment worth sharing with your competitors
In a first-person account published in 2015, Schultz recalled meeting snowboarder and Army veteran Keith Deutsch, who had lost a leg while serving in Iraq.
They tested the Moto Knee together in 2011. According to Schultz, Deutsch was soon carving, jumping and spinning down the mountain before greeting him at the bottom with an enthusiastic high-five. He became BioDapt’s first client.
As Schultz’s own snowboarding career progressed, his equipment reached fellow competitors, creating an unusual relationship between his ambitions as an athlete and his work as a maker.
“The technology I’m building to make myself faster is also helping my competitors,” he explained in an Autodesk interview.
Every improvement could give another rider a better chance of challenging him. It also meant more people reaching the start line with equipment designed for what they wanted to do.
Digital engineering supports the next improvements
That development continues with newer tools. In 2026, Autodesk announced a partnership with BioDapt following work to improve an ankle frame and binding brace using its Fusion platform.
The team increased stiffness without extending 3D-printing time and revised attachment patterns so a component could fit multiple BioDapt leg models. Autodesk reported improved durability during training.
These advances used digital design, simulation and manufacturing workflows, with AI-assisted generation and evaluation of improvements identified as a future area of exploration. Schindler’s project demonstrates generative design in use; Schultz’s illustrates the wider contribution of digital engineering to sports prosthetics.
Extending those benefits to more people also requires affordable equipment, skilled fitting and ongoing support. Faster development can contribute, particularly when the wearer’s experience guides what gets improved.
Deutsch’s first ride with Schultz’s knee offers a memorable measure of that progress. After the drawings, adjustments and testing came a snowboarder carving down a mountain; and a high-five waiting at the bottom.
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