Presentation Title: Leveraging internal human biomechanical states to control wearable robotic systems

Presentation Abstract:

New end-to-end task agnostic AI systems have transformed the ability of wearable robotics to provide meaningful assistance to users across a diverse range of daily activities. This talk will present best practices for structuring real-time deep learning systems for wearable robotics that integrate seamlessly with the user’s underlying physiology. Outcome measures from related human subject experiments with test scenarios of these systems will be presented focused on both industrial and recreational tasking. These techniques can be applied to a very broad set of practical problems, and two unique deployment scenarios will be discussed. First, our research team recently completed a clinical trial in mobility impaired individuals from stroke using hip exosuits to enhance daily activities of living. Lastly, balance and stability are a primary struggle for many individuals with mobility deficits yet are very hard problems for wearable robotics to fully address. I will highlight some of our team’s recent successes by leveraging predictive internal state estimation in combination with wearable exoskeletons to improve balance during unstable gait.

About the speaker:

Aaron Young is an Associate Professor and Woodruff Faculty Fellow and James R. and Sarah R. Borders Faculty Fellow in the Woodruff School of Mechanical Engineering at Georgia Tech. He has directed the Exoskeleton and Prosthetic Intelligent Controls (EPIC) lab since 2016. Dr. Young received his MS and PhD degrees in Biomedical Engineering with a focus on neural and rehabilitation engineering from Northwestern University in 2011 and 2014 respectively. He received a BS degree in Biomedical Engineering from Purdue University in 2009. He also completed 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 research area is in advanced control systems for robotic prosthetic and exoskeleton systems for humans with movement impairment. He combines machine learning, robotics, human biomechanics, and control systems to design wearable robots to improve the community mobility of individuals with walking disability. He has received an NIH New Innovator Award (DP2), NIH NCMRR New Investigator award and IEEE New Faces of Engineering award, and his EPIC lab group won the International VIP Consortium Innovation Competition. He is a Senior Member of the IEEE and National Academy of Inventors (NAI).

View on site | Email this event

Presentation Title: Developing Accessible Biomarkers for Cardiovascular Disease Risk Stratification Using Wearable Device Biosensors

Presentation Abstract:

Modern advances in technology have made biological sensors inexpensive and widely accessible through commercial health devices. Harnessing these biosensors for real-time health monitoring could have a substantial impact on personalized medicine, including the timely detection and risk stratification of cardiovascular disease. However, significant challenges remain in translating these technologies from consumer and research applications into clinical practice. In this seminar, I will present the path that led to my research on cardiovascular health biomarkers, including the use of microvascular photoplethysmography and near-infrared spectroscopy to assess microvascular stiffness and cuffless blood pressure, and ultimately to detect lower-extremity peripheral artery disease. I will also discuss signal-processing strategies for facilitating the translation of biomarkers derived from wearable devices into clinical practice. Finally, I will discuss future research directions for detecting lower-extremity peripheral artery disease using pulse arrival time derived from photoplethysmography.

About the speaker:

Dr. Cody Anderson is an Assistant Professor in the School of Health and Kinesiology at the University of Nebraska at Omaha. He received his PhD in Biomechanics and Kinesiology, with a concentration in Physiology of Exercise, from the University of Nebraska at Omaha in 2026. His research training has included the study of gait in patients with peripheral artery disease using musculoskeletal modeling, as well as the investigation of the vascular and metabolic consequences of peripheral artery disease and the potential mechanistic links between physical inactivity and the development of cardiovascular diseases. Building on his training in data analytics and physiology, Dr. Anderson’s research focuses on developing cardiovascular health biomarkers that can be derived through signal processing of biosensors available in wearable devices, with the ultimate goal of improving the timely detection and risk stratification of cardiovascular disease.

View on site | Email this event