Young Receives NIH NCMRR Young Investigator Award

Aaron Young headshotAssistant professor Aaron Young has received a National Institutes of Health (NIH) National Center for Medical Rehabilitation Research Young Investigator Award for his project titled "Improving Community Ambulation for Stroke Survivors Using Powered Hip Exoskeletons with Adaptive Environmental Controllers." The two-year award comes with approximately $300,000 in funding over a two-year period and supports ongoing research in Young's Intelligent Prosthetic & Exoskeleton Controls (EPIC) Lab.
"The idea of this technology is to fill that gap for someone who can get around a bit in their home to hopefully helping them to become a full community ambulator," said Young. "We have a hip exoskeleton that provides significant positive power both in hip flexion and extension that modulates depending on what someone's trying to do. So whether they're trying to go faster or slower or go upstairs or ramps, it would assist them by adapting to the situation. That's the end goal."
According to the proposal abstract, this project will address the critical need for improving the locomotion capabilities of individuals who have walking impairments due to disease to increase their community mobility, independence, and health. Robotic exoskeletons have the potential to assist these individuals by increasing community mobility to improve quality of life. While these devices have incredible potential, current technology does not support dynamic movements common with locomotion such as transitioning between different gaits and supporting a wide variety of walking speeds. One significant challenge in achieving community ambulation with exoskeletons is providing an adaptive control system to accomplish a wide variety of locomotor tasks. Many exoskeletons today are developed without a detailed understanding of the effect of the device on the human musculoskeletal system. This research is interested in studying the question of how the control system affects human biomechanics including kinematic, kinetics and muscle activation patterns. By optimizing exoskeleton controllers based on human biomechanics and adapting control based on task, the biggest benefit to patient populations will be achieved to help advance the state-of-the-art with assistive hip exoskeletons.
The long-term research goal is to create powered assistive exoskeletons devices that are of great value to individuals with serious lower limb disabilities by improving clinical outcomes such as walking speed and community ambulation ability. The overall objective of the proposed project is to study the biomechanical effects of using a hip exoskeleton with adaptive controllers for assisting stroke survivors with lower limb deficits to improve their community ambulation capabilities. The central hypothesis overarching both aims is that exoskeleton control that adapts to environmental terrain will improve mobility metrics for human exoskeleton users on community ambulation tasks. The rationale is that since human biomechanics change based on task, exoskeleton controllers likewise need to optimize their assistance levels to match what the human is doing.
Aaron Young is an Assistant Professor in the Woodruff School of Mechanical Engineering at Georgia Tech and a member of the Institute for Robotics & Intelligent Machines. He also is a program faculty member of the Biomedical Engineering School. He is director of the Intelligent Prosthetic & Exoskeleton Controls (EPIC) Lab focused on lower limb robotic augmentation. His research focuses on optimizing control systems in wearable robotic devices by studying their effect on human locomotion biomechanics in clinical populations. The long term goal is to create clinically viable control systems for wearable robotic lower limb assistive devices that are smart and intuitive to use. His previous experience includes a post-doctoral fellowship at the University of Michigan in the Human Neuromechanics Lab working with lower limb exoskeletons and powered orthoses to augment human performance. His dissertation work at Northwestern University in the Center for Bionic Medicine at the Rehabilitation Institute of Chicago focused on using machine learning strategies for enabling intent recognition systems for powered lower limb prostheses.