Is it possible to predict optimal rocker shoe design using barefoot gait parameters?

Background Curved rocker shoes are routinely prescribed for people with diabetes in order reduce in-shoe plantar pressures. However, previous research has shown that different individuals may require different rocker outsole geometries in order to optimise pressure reduction [1,2]. This has led some researchers to suggest that every individual should try a range of possible outsole designs to identify the design which maximises pressure reduction [1]. However, this process may not be feasible in a clinical setting. Given that plantar pressure has been shown to depend on specific gait variables [3], it may be possible to develop an algorithm which could predict an individual’s pressure response to a specific rocker outsole design using an input of gait data. Such an algorithm would remove the need to try on a large number of pairs of rocker shoes.