Speaker: Gabrielle Labrozzi
Advisors: Dr. Ronald Triolo and Dr. Musa Audu
Location NORD 400 and hybrid (see nec.ceneter announcement of link)
Title: Fuzzy Logic Systems for Post-SCI Gait using Center of Mass Kinematics
Abstract: For over a decade, individuals after a spinal cord injury (SCI) have identified restoration of walking as a top priority. Current approaches facilitate gait and automate stepping post-SCI with functional neuromuscular stimulation. Despite the ability to initiate steps in a feedforward manner, these neural stimulation paradigms result in variable, discontinuous, and asymmetrical gait patterns. This requires extensive upper extremity effort to remain stable and results in rapid muscle fatigue and high metabolic energy expenditure. To approach nominal gait patterns post-SCI requires a feedback controller that drives a continuous walking pattern and modulates the muscle activations based on a control parameter. The center of mass (CoM) is a global kinematic parameter that reflects whole-body movement, follows well-defined trajectories during normal gait, and changes predictably with various gait impairments including SCI. We have previously developed and trained a neural network to estimate each dimension of the CoM from inertial measurement units and explored the impact of number and location of IMUs on network predication accuracy. Three to five sensors located on the legs and medial trunk were the most promising reduced sensor sets for achieving CoM estimates suitable for post-SCI gait control. Now, we are investigating the application of Fuzzy Logic Control systems to determine when in the gait cycle to activate/deactivate muscle groups and automate the initiation of sequential steps. From data previously collected with 5 able-bodied individuals, we divided the CoM trajectories into six phases of the gait cycle, and generated Gaussian membership curves in order to construct rules for transitioning between sub-patterns of stimulation to accomplish each phase, and even modulate stimulation within phases based on progress of the CoM. In this presentation, I will address the progress of our exploration of the application of this fuzzy logic control approach to facilitate walking after paralysis. The results should provide the framework for developing a feedback controller for more consistent, automatic and responsive stimulation assisted gait post-SCI.