MIT engineers are reshaping the way runners choose their shoes. Their new model, reported in the Journal of Biomechanical Engineering, predicts how a shoe's properties impact a runner's performance. This model, a brainchild of Fay and Professor Anette "Peko" Hosoi, could revolutionize shoe design and selection.
The model simplifies the complex dynamics of running. It considers a person's physical dimensions and the shoe's characteristics, like midsole stiffness and springiness. This allows for the simulation of a runner's gait in various shoes, aiming to find the one that minimizes energy expenditure. As Fay, a postdoc in MIT's Sports Lab, stated:
"Our model could help [designers] design really novel shoes that are also high-performing."
However, the model has its limitations. It excels in comparing vastly different shoe types but struggles with similar designs, like most commercial running shoes. Thus, its current best application is as a tool for designers to push sneaker design boundaries.
The team's ambition doesn't stop here. They envision a future where consumers could use a similar model to select shoes tailored to their running style.
"Way down the road, we imagine that if you send us a video of yourself running, we could 3D print the shoe that's right for you."
This innovation sprouted from collaboration with sneaker industry leaders, who now 3D print shoes on a commercial scale. The technology allows for precise control over the shoe's material response, enabling customization like never before. Hosoi emphasizes the potential:
"With 3D printing, designers can tune everything about the material response locally."
The model's genesis traces back to Thomas McMahon's biomechanics studies at Harvard in the 1970s. McMahon's simple "spring and damper" model, which significantly influenced athletic performance design, laid the groundwork for Fay and Hosoi's work. Their model follows a similar principle, representing a runner as a center of mass with adjustable leg and shoe properties.
What sets their model apart is the consideration of a "biological cost function" – a subconscious goal to minimize certain biological measures like foot impact and leg energy expenditure. By simulating different gaits with varying assumed costs, they found that most runners tend to minimize these two factors. This discovery boosts the model's ability to predict realistic gaits and suitable shoes.
This MIT innovation opens a new chapter in shoe design and selection. It provides a quantitative method for creating efficient, personalized footwear, bridging the gap between intuitive design and scientific insight.
"Designers have an intuitive sense for that. But now we have a mathematical understanding that we hope designers can use as a tool to kickstart new ideas."