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Qiao, Zhuhan (Calvin)

University of British Columbia

Standing balance deficits are common in aging populations and individuals with neurological disorders, including patients with traumatic brain injuries. Despite the prevalence, the neural mechanisms underlying such deficits remain unclear. Existing standing balance tests mainly focus on global postural stability metrics, often neglecting the roles of individual sensory organs and neural components. Therefore, new methods are required to better probe the standing balance circuit. The cerebellum emerges as a key neural center for managing standing balance control and its adaptability. While human-in-the-loop robotic balance platforms have been used to test balance adaptability, they are limited to the anteroposterior direction and lack direct cerebellar measurements. To address these limitations and investigate the underlying mechanisms of standing balance control deficits, this thesis has the following objectives: (1) conduct a literature review to summarize standing balance deficits, current test paradigms and their limitations, with a focus on patients with concussions, (2) achieve multidirectional control on a human-in-the-loop balance robot by adding mediolateral (ML) capabilities, (3) develop an accurate kinematics model for ML balance simulation, and (4) develop an experimental protocol that combines electroencephalography (EEG) with the robot to measure cerebellar activity during adaptation. The literature review confirmed relatively consistent post-concussion global balance stability changes and highlighted the need to develop more specific methodologies to probe the balance control circuit. After upgrading the balance robot to include ML control, its motion tracking performance achieved delays under 15 ms and submillimeter errors. A multi-segmental kinematics ML balance model was developed, validated through experiments, and improved through data-driven refinements. The refined model reduced root mean squared errors of the estimated trunk/pelvis position by 37.4-47.4%. Additionally, a balance adaptation study combining the balance robot and an EEG device revealed cerebellar power increases in delta, beta, and gamma bands during early adaptation followed by decreases to baselines post-adaptation in healthy individuals. These advancements enable the study of standing balance adaptability in multidirectional contexts and could help quantify deficits in standing balance adaptation and cerebellar function in various patient groups, leading to more tailored balance assessment and recovery management.

Text

2024-07-04

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/88568

Mechanical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/