Basilakos Alexandra, Yourganov Grigori, den Ouden Dirk-Bart, Fogerty Daniel, Rorden Chris, Feenaughty Lynda, Fridriksson Julius
Department of Communication Sciences & Disorders, University of South Carolina, Columbia.
Department of Psychology, University of South Carolina, Columbia.
J Speech Lang Hear Res. 2017 Dec 20;60(12):3378-3392. doi: 10.1044/2017_JSLHR-S-16-0443.
Apraxia of speech (AOS) is a consequence of stroke that frequently co-occurs with aphasia. Its study is limited by difficulties with its perceptual evaluation and dissociation from co-occurring impairments. This study examined the classification accuracy of several acoustic measures for the differential diagnosis of AOS in a sample of stroke survivors.
Fifty-seven individuals were included (mean age = 60.8 ± 10.4 years; 21 women, 36 men; mean months poststroke = 54.7 ± 46). Participants were grouped on the basis of speech/language testing as follows: AOS-Aphasia (n = 20), Aphasia Only (n = 24), and Stroke Control (n = 13). Normalized Pairwise Variability Index, proportion of distortion errors, voice onset time variability, and amplitude envelope modulation spectrum variables were obtained from connected speech samples. Measures were analyzed for group differences and entered into a linear discriminant analysis to predict diagnostic classification.
Out-of-sample classification accuracy of all measures was over 90%. The envelope modulation spectrum variables had the greatest impact on classification when all measures were analyzed together.
This study contributes to efforts to identify objective acoustic measures that can facilitate the differential diagnosis of AOS. Results suggest that further study of these measures is warranted to determine the best predictors of AOS diagnosis.
言语失用症(AOS)是中风的一种后果,常与失语症同时出现。对其研究受到感知评估困难以及与同时出现的损伤相区分的限制。本研究在中风幸存者样本中检验了几种声学指标对AOS进行鉴别诊断的分类准确性。
纳入57名个体(平均年龄 = 60.8 ± 10.4岁;21名女性,36名男性;中风后平均月数 = 54.7 ± 46)。参与者根据言语/语言测试分组如下:AOS-失语症组(n = 20)、单纯失语症组(n = 24)和中风对照组(n = 13)。从连贯言语样本中获取归一化成对变异指数、扭曲错误比例、语音起始时间变异性和幅度包络调制谱变量。分析各指标的组间差异,并将其纳入线性判别分析以预测诊断分类。
所有指标的样本外分类准确率均超过90%。当对所有指标进行综合分析时,包络调制谱变量对分类的影响最大。
本研究有助于确定能够促进AOS鉴别诊断的客观声学指标。结果表明有必要对这些指标进行进一步研究,以确定AOS诊断的最佳预测指标。