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Using isolated vowel sounds for classification of Mild Traumatic Brain Injury

机译:使用孤立的元音对轻度创伤性脑损伤进行分类

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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%.
机译:脑震荡是轻度创伤性脑损伤(mTBI),在接触运动中很常见,由于症状的出现延迟,通常难以诊断。本文探讨了使用语音分析检测mTBI的可行性。每次比赛之后,参加拳击比赛的运动员都会在移动设备上进行记录。元音与录音分离,并提取声学特征,并将其用于训练几种一类机器学习算法,以预测运动员是否受到脑震荡。预测结果根据马戏团医疗队在记录时所做的诊断进行验证,性能评估显示预测准确性高达98%。

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