Vestibular Response Pattern Recognition in Relation to Concussion

This proposal presents research projects to evaluate a new technology, Electrovestibulography (EVestGTM) that holds potential to objectively, quickly and quantitatively measure the severity of concussion, thus aiding in its diagnosis. EVestG signals are recorded painlessly and non-invasively from the external ear in response to a vestibular stimulus; they are the brain signals modulated by the vestibular response. When concussed, people commonly experience balance (vestibular) problems and dizziness, as well as confused thinking. Considering the well-known bidirectional anatomical links of the vestibular system, following an impact concussion the EVestG signals will change, and should be indicative of a concussion. Data will be collected from referred patients, who have had concussion, as well as age and gender-matched controls. Two different signal processing will be used to derive characteristic features specific to concussion. Expert diagnostic classifiers will be developed using the statistically significant features of the two groups of participants, and the results will be compared with clinical diagnoses. The proposed research may lead to a technology that can be used for both objective diagnosis and recovery monitoring of concussion.

Faculty Supervisor:

Dr. Zahra Kazem-Moussavi

Student:

Abed Sulieman & TBD

Partner:

Neural Diagnostics (Canada) Inc.

Discipline:

Engineering - biomedical

Sector:

Medical devices

University:

University of Manitoba