A good shoe can make a huge difference for runners, from career marathoners to couch-to-5K first-timers. But every runner is unique, and a shoe that works for one might trip up another. Outside of trying on a rack of different designs, there’s no quick and easy way to know which shoe best suits a person’s particular running style.
MIT engineers are hoping to change that with a new model that predicts how certain shoe properties will affect a runner’s performance.
The simple model incorporates a person’s height, weight, and other general dimensions, along with shoe properties such as stiffness and springiness along the midsole. With this input, the model then simulates a person’s running gait, or how they would run, in a particular shoe.
Using the model, the researchers can simulate how a runner’s gait changes with different shoe types. They can then pick out the shoe that produces the best performance, which they define as the degree to which a runner’s expended energy is minimized
While the model can accurately simulate changes in a runner’s gait when comparing two very different shoe types, it is less discerning when comparing relatively similar designs, including most commercially available running shoes. For this reason, the researchers envision the current model would be best used as a tool for shoe designers looking to push the boundaries of sneaker design.
“Shoe designers are starting to 3D print shoes, meaning they can now make them with a much wider range of properties than with just a regular slab of foam,” says Sarah Fay, a postdoc in MIT’s Sports Lab and the Institute for Data, Systems, and Society (IDSS). “Our model could help them design really novel shoes that are also high-performing.”
The team is planning to improve the model, in hopes that consumers can one day use a similar version to pick shoes that fit their personal running style.
“We’ve allowed for enough flexibility in the model that it can be used to design custom shoes and understand…