Abstract

In this study, a noninvasive quantitative measure was used to identify short and long term post-concussion syndrome (PCS) both from each other and from healthy control populations. We used Electrovestibulography (EVestG) for detecting neurophysiological PCS consequent to a mild traumatic brain injury (mTBI) in both short-term (N = 8) and long-term (N = 30) (beyond the normal recovery period) symptomatic individuals. Peripheral, spontaneously evoked vestibuloacoustic signals incorporating - and modulated by - brainstem responses were recorded using EVestG, while individuals were stationary (no movement stimulus). Tested were 38 individuals with PCS in comparison to those of 33 age-and-gender-matched healthy controls. The extracted features were based on the shape of the averaged extracted field potentials (FPs) and their detected firing pattern. Linear discriminant analysis classification, incorporating a leave-one-out routine, resulted in (A) an unbiased 84% classification accuracy for separating healthy controls from a mix of long and short-term symptomatology PCS sufferers and (B) a 79% classification accuracy for separating between long and short-term symptomatology PCS sufferers. Comparatively, short-term symptomatology PCS was generally detected as more distal from controls. Based on the results, the EVestG recording shows promise as an assistive objective tool for detecting and monitoring individuals with PCS after normal recovery periods.

Details

Title
Quantitative measurement of post-concussion syndrome Using Electrovestibulography
Author
Suleiman Abdelbaset 1 ; Lithgow, Brian 2 ; Dastgheib Zeinab 1 ; Mansouri Behzad 3 ; Moussavi Zahra 1 

 Biomedical Engineering Program, University of Manitoba, Winnipeg, Canada (GRID:grid.21613.37) (ISNI:0000 0004 1936 9609) 
 Biomedical Engineering Program, University of Manitoba, Winnipeg, Canada (GRID:grid.21613.37) (ISNI:0000 0004 1936 9609); Monash Alfred Psychiatry Research Center, Monash University, Melbourne, Australia (GRID:grid.1002.3) (ISNI:0000 0004 1936 7857) 
 Biomedical Engineering Program, University of Manitoba, Winnipeg, Canada (GRID:grid.21613.37) (ISNI:0000 0004 1936 9609); Department of Internal Medicine (Neurology), University of Manitoba, Winnipeg, Canada (GRID:grid.21613.37) (ISNI:0000 0004 1936 9609) 
Publication year
2017
Publication date
Dec 2017
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1968994057
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.