Data-driven biomechanical optimisation of bicycle and crank-pedal design for maximizing power output.

This paper presents a novel crank-pedal mechanism designed to optimize pedal-path kinematics. The goal of the design is to maximize power throughput by utilizing torque-generating capabilities produced by individual riders. The dimensions of the design are determined through an optimization algorithm that modifies the crank length, pedal shape, and frame geometry. The optimization uses the joint position, velocity, and torque relationships of a user. As such, the solver can take advantage of musculoskeletal motions that generate sustained large torques. The approach is tested in simulation with data from two user profiles, demonstrating similarities and variations that morphologies can produce in the design. In both cases, the optimized designs with the new crank-pedal mechanism improved the mean crank power during a crank revolution by approximately 15% compared to a traditional personalized bicycle. These results suggest that altering the dimensions of a bike using biomechanical data in the design process could have a significant impact on the pedaling performance of individuals, ranging from everyday users to athletes and individuals with motor impairments.