Optimization Principles in Hemiparetic Gait

Toward a Mechanistic Understanding of Optimization Principles Underlying Hemiparetic Gait

This project seeks to identify the how walking impairments in stroke survivors contribute to mobility deficits through the use of behavioral observations and computational models. The chosen approach integrates biomechanical analyses, physiological assessments and machine learning algorithms to explain how asymmetries during walking influence balance and the effort required to walk. Ultimately, the results of this work may lead to more personalized rehabilitation strategies to improve walking capacity and efficiency, and ultimately reduce fall risk in stroke survivors.

Inclusion Criteria for Control Participants:

• No musculoskeletal injury or conditions that limit walking ability
• No history of neurological disorders or severe head trauma
• Absence of cognitive impairment as demonstrated by a Mini-Mental score greater than 24

Inclusion Criteria for Post-Stroke Participants

• Presence of unilateral brain lesion from a single stroke
• Weakness confined to one side
• Ability to walk on a treadmill for five minutes continuously without a cane or walker
• Absence of cognitive impairment as demonstrated by a Mini-Mental score greater than 24