Technical development of the brain vital signs framework as an objective and practical test for concussion

Author: 
Date created: 
2020-06-24
Identifier: 
etd20926
Keywords: 
EEG
ERP
Portable technology
Concussion
Brain vital signs
Abstract: 

The engineering design criteria for an objective test for concussion dictate that it should be rapid, portable, practical, robust, and sensitive over the time-course of injury. This is an important technical challenge, which is yet to be solved. Currently, sports medicine professionals who treat concussions are limited by a lack of access to objective measurement tools for evidence-based treatment. Electroencephalography-based technologies present a unique opportunity to address these criteria. The brain vital signs framework uses electroencephalography to rapidly assess electrical brain responses to auditory stimuli and make interpretations on cognitive changes. However, applications in electroencephalography are typically recorded under controlled laboratory conditions and have not been validated under the uncontrolled, noisy environments necessary to evaluate concussions. These clinical and athletic environments are fundamentally different to those found in the laboratory and have a unique set of constraints that make traditional methods impractical. This thesis addresses the technical challenges to demonstrate that the brain vital signs framework can be used as an objective, practical tool for monitoring concussion. First, the brain vital signs framework was successfully deployed in a clinical environment. Markers of brain function demonstrated significant concussion-related changes in athletes that were undetected by standard concussion protocols. This is the first demonstration of a portable brain technology being implemented immediately at the point of care for concussion. However, there are additional technical challenges to improve the practicality of this framework. Subsequently, an automated framework for numerically assessing the signal quality of electroencephalography is presented. This framework is highly sensitive and specific to classifying artifacts and can approximate the signal-to-noise-ratio of a recorded signal. Finally, a new approach for recording event-related potentials from distant sensor locations is presented to optimise the speed and practicality of portable brain technologies. The presented body of work incorporates novel engineering developments to provide robust, technical solutions for a clinical problem. These are impactful and important results that will allow for improved medical applications in concussion.

Document type: 
Thesis
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Supervisor(s): 
Ryan D'Arcy
Department: 
Applied Sciences: School of Engineering Science
Thesis type: 
(Thesis) Ph.D.
Statistics: