The Biomechatronics Group at MIT is using a data-driven approach to study the mechanics and control of human walking, with the goal of applying the findings to hardware control. PhD student David Hill is developing a model that could be used to improve assistive devices that can help maintain or correct the gait of people recovering from strokes.

David Hill of MIT’s Media Lab maps human locomotion in detail to improve rehabilitative and assistive robotics.

Human movement is a complicated and often taxing activity, though, even for healthy people. Support from robotic wearables could also help make the work of soldiers, construction workers, and other heavy lifters less physically detrimental.

Hill is currently working on modeling the lower extremities during walking to create robotic devices that mimic biological function as closely as possible. Hill’s model has to account for every minute angle and movement throughout the legs, from the hips all the way down to the joints in the foot. When completed, the model will be used to propel designs for mechanical devices for any part of the lower body, and for a myriad of uses.