Date: Wednesday, July 14, 2021

Time: 2:00 pm - 4:00 pm (EST)

Location: GTMI Auditorium

Virtual access: BlueJeans

Link: https://bluejeans.com/955874875/5768

Meeting ID: 955 874 875

Committee Members:

Dr. Aaron J. Young (Advisor), School of Mechanical Engineering, Georgia Institute of Technology

Dr. Gregory S. Sawicki, School of Mechanical Engineering, Georgia Institute of Technology

Dr. Anirban Mazumdar, School of Mechanical Engineering, Georgia Institute of Technology

Dr. Omer T. Inan, School of Electrical and Computer Engineering, Georgia Institute of Technology

Dr. Geza F. Kogler, Department of Exercise Science and Sport Management, Kennesaw State University

Abstract:

The field of human augmentation has been studied for decades to expand the limitations of human mobility. Specifically, hip exoskeletons have garnered attention from different research groups, mainly due to the nature of the hip joint generating large amounts of mechanical power during locomotion. Additionally, hip exoskeleton application can be expanded to clinical populations such as stroke patients who tend to overtax the hip joint to compensate for lack of coordination and weakness in the distal muscles of the leg. Recent hip exoskeleton studies show promising results of benefiting the user both energetically and biomechanically. Unfortunately, most of these studies are extremely tailored for specific applications and users, which illustrates a huge gap in translating the control framework from a lab setting to a real-world scenario. Additionally, existing exoskeleton systems have limited high-level understanding of user state information, such as walking speed and ambulation mode, precluding exoskeleton assistance to adapt to the changes in user’s biomechanical demand during various locomotor tasks. Therefore, current exoskeleton assistance strategies are not optimal and need to be investigated further to develop an adaptive controller that can accommodate the dynamic changes of the user’s state as well as variant subject-dependent information. This work focuses on three key research objectives: 1) Explore the optimal hip exoskeleton design approach for maximal human exoskeleton performance during wide ranges of locomotor tasks, 2) Understand the contributions of sensor fusion-based user state estimation for improving the hip exoskeleton controls over a simulated community terrain, and 3) Quantify the biomechanical and clinical effects of a hip exoskeleton in improving a stroke patient’s community ambulation capability. The study findings provide valuable information for future exoskeleton designers in developing a more efficient exoskeleton system.

Inseung Kang