Lokwani Prateek, Prabhu Prashanth, Nisha Kavassery Venkateswaran
Department of Audiology, All India Institute of Speech and Hearing, Manasagangothri, Mysuru, 570 006, India.
J Otol. 2022 Oct;17(4):218-225. doi: 10.1016/j.joto.2022.08.001. Epub 2022 Aug 14.
Onset-based differences are understudied in Auditory Neuropathy Spectrum Disorder (ANSD) in dimensions such as voice, which is addressed in the study. The study aimed to profile and predict the best metrics of onset-related differences in acoustic vocal characteristics of early and late-onset ANSD patients.
31 participants (15 early and 16 late-onset) aged 15-30 years diagnosed with ANSD were included in the study. The sustained phonation of vowel /i/ recorded by the participants using android based smartphones of selected configuration was sent over email to the experimenter. Acoustic parameters (fundamental frequency, harmonic frequencies, jitter, shimmer, harmonic-to-noise ratio, cepstral peak prominence -CPP, and pitch sigma) were analysed using Praat software.
Results revealed significantly increased (p < 0.05) fundamental frequency along with decreased F2 and F3 of /i/ in the early-onset ANSD compared to the late-onset group, which can be explained based on differences in the pathophysiology of the disorder. Although not statistically significant, mean perturbations (jitter and shimmer), harmonic-to-noise ratio, cepstral peak prominence, and pitch sigma were more affected in the early-onset group, reflective of lowered auditory feedback and periodicity in their voice samples. Results of discriminant analysis marked the emergence of F2, F3, and CPP as the most sensitive metrics for onset-based group differences in voice characteristics.
The findings from the study highlight the role of acoustical voice evaluation (especially CPP, F2 & F3) in verifying the onset of ANSD disorder. The insights from the onset-based differences seen in vocal characteristics can indirectly help audiologists in deciding the management options for ANSD.
在听觉神经病谱系障碍(ANSD)中,基于发病时间的差异在诸如嗓音等维度上研究不足,本研究对此进行了探讨。该研究旨在剖析并预测早发型和晚发型ANSD患者声学嗓音特征中与发病时间相关差异的最佳指标。
本研究纳入了31名年龄在15至30岁之间、被诊断为ANSD的参与者(15名早发型和16名晚发型)。参与者使用选定配置的安卓智能手机录制的元音/i/的持续发声通过电子邮件发送给实验者。使用Praat软件分析声学参数(基频、谐波频率、抖动、闪烁、谐波噪声比、谐波峰值突出度-CPP和音高标准差)。
结果显示,与晚发型组相比,早发型ANSD患者的基频显著升高(p<0.05),同时/i/的F2和F3降低,这可以基于该疾病病理生理学的差异来解释。尽管无统计学意义,但早发型组的平均微扰(抖动和闪烁)、谐波噪声比、谐波峰值突出度和音高标准差受影响更大,这反映出他们嗓音样本中的听觉反馈和周期性降低。判别分析结果表明,F2、F3和CPP是嗓音特征中基于发病时间的组间差异最敏感的指标。
该研究结果突出了声学嗓音评估(尤其是CPP、F2和F3)在验证ANSD疾病发病时间方面的作用。从嗓音特征中基于发病时间的差异获得的见解可以间接帮助听力学家确定ANSD的管理方案。