Using isolated vowel sounds for classification of Mild Traumatic Brain Injury Conference

Falcone, M, Yadav, N, Poellabauer, C et al. (2013). Using isolated vowel sounds for classification of Mild Traumatic Brain Injury . 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 7577-7581. 10.1109/ICASSP.2013.6639136

cited authors

  • Falcone, M; Yadav, N; Poellabauer, C; Flynn, P

authors

abstract

  • Concussions are Mild Traumatic Brain Injuries (mTBI) that are common in contact sports and are often difficult to diagnose due to the delayed appearance of symptoms. This paper explores the feasibility of using speech analysis for detecting mTBI. Recordings are taken on a mobile device from athletes participating in a boxing tournament following each match. Vowel sounds are isolated from the recordings and acoustic features are extracted and used to train several one-class machine learning algorithms in order to predict whether an athlete is concussed. Prediction results are verified against the diagnoses made by a ringside medical team at the time of recording and performance evaluation shows prediction accuracies of up to 98%. © 2013 IEEE.

publication date

  • October 18, 2013

published in

Digital Object Identifier (DOI)

International Standard Book Number (ISBN) 13

start page

  • 7577

end page

  • 7581