Development of a Robotic Assistive Device with Neuromuscular Insight

Robotically assisted device

Project overview:
Find the minimal amount of assistance that will restore healthy gait in stroke patients with Stiff-Knee gait (SKG) after stroke.

Project description:
Our initial study assisting knee flexion torque during preswing predictably improved knee flexion, but surprisingly increased hip abduction. Since biomechanics could not identify this phenomenon, we concluded that there must be an abnormal discoordination. The aim of this project is to identify the nature of this discoordination, include it in a novel neuromuscular model, and then simulate the effects of other kinds of assistance to predict what the optimal assistance should be.

Previous studies show different classes of lower-limb discoordination (i.e. reflex and voluntary) following stroke, but they have never been identified during gait due to lack of perturbation studies such as ours. The first stage of this project is to verify the existence of these mechanisms during gait using the collected data during perturbations from our existing dataset and execute dynamic simulations. The next stage is to develop a patient-specific neuromuscular simulation workflow for SKG assistance which incorporates neuromuscular impairments (discoordination, reflexes etc.) specific to SKG and than obtain optimal assistance using a virtual assistive device with forward dynamic simulation. Finally we will design and test a device capable of providing the type of assistance provided by simulations.