On the development of control algorithms for lower limb prostheses
It's not easy to walk smoothly with a lower leg prosthesis. Some prostheses make walking easier with smart mechanical solutions, for instance by regulating stiffness and damping during walking. There are also powered lower limb prosthetic devices, that push off at the right moment in the walking cycle, thus making things lighter for the user.
Such powered lower limb prosthetic devices typically employ onboard sensors on the amputated side. But walking in a balanced way requires synchronized neural control to facilitate both limbs’ appropriate positioning and orientation. Building upon this idea, the research of Aniket Mazumder focused on designing multiple control architectures that utilize information acquired from various areas of the body using inertial measurement units (eg. the left shank, right thigh). Using these measurements, Mazumder generates the control commands for prosthesis prototypes.
Mazumder performed multiple trials with a healthy subject walking on level ground at different speeds and undertaking obstacle avoidance tasks. The results suggest that incorporating data from each sensor provides a more comprehensive understanding of the positions and orientations of the body; thereby allowing the prosthesis to perform precise control action through a comprehensive knowledge of the user’s gait states.