Project Abstract
Stroke survivors experience profound mobility challenges limiting community ambulation which impacts overall quality
of life. Studies show mobility is strongly linked to quality of life, participation, and well-being, and robotic exoskeleton
assistive devices have significant potential to improve mobility by providing assistance at lower limb joints. However, no
technology enabling personalization to individuals with varying mobility needs exists. This proposal aims to understand
how optimized ankle and hip exoskeletons in combination with biofeedback can impact mobility post-stroke.
The overarching hypothesis is that targeted biofeedback combined with optimized exoskeleton assistance can
improve community ambulation capability across a cohort of stroke survivors with variable baseline gait function.
In order to optimize exoskeleton assistance for individuals post-stroke, the team will address 3 aims. Aim 1 will
determine and compare the benefit of personalized hip and ankle exoskeleton assistance for bilateral improvement
of post-stroke gait. To compensate for distal ankle weakness, stroke survivors often compensate with the hip joint.
Therefore, the hypothesis is that assistance targeted at the hip may provide a larger improvement in walking speed. Aim 2
will combine exoskeleton technology with biofeedback to enhance and synchronize wearable robotic assistance to
an individual stroke survivor’s gait pattern. The hypothesis is that biofeedback to improve paretic leg positioning will
work synergistically with both hip and ankle exoskeletons to improve stroke gait mechanics and walking speed. Further, it
is expected that larger improvements will be observed with the ankle exoskeleton assistance combined with biofeedback
because improved paretic leg positioning will enable greater forward propulsion of the CoM during ankle exoskeleton use.
Aim 3 will evaluate and compare clinically relevant outcomes with and without the optimized technologies in real-
world environments in an effort toward clinical translation.
This work leverages a novel self-adaptive AI system to optimize performance of post-stroke gait coupled with
biofeedback in clinically-applicable exoskeletons. This work will fundamentally innovate new technology in 3 key areas:
1) New AI and optimization systems to personalize exoskeleton control to post-stroke gait, 2) A new wearable overground
biofeedback system to cue exoskeleton users to improve gait mechanics, and 3) Implementation of these systems on state-
of-the-art exoskeletons with clinical testing in stroke survivors and applications to community ambulation. Concurrently,
the work has scientific impact through the analysis of the biomechanics of hip compensation for ankle weakness and the
associated hip-ankle trade-off changes that occur with ankle and hip exoskeletons and targeted biofeedback. Lastly, this
work aims to push for clinical translation through targeted comparisons of clinical outcomes in stroke survivors
ambulating in real world settings with and without the new technologies.
Ultimately, the project outcomes will enable personalized assistive devices to improve post-stroke community mobility
and overall quality of life.
