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[Components and characteristics of speech-ABR from healthy young adults.]. | LitMetric

[Components and characteristics of speech-ABR from healthy young adults.].

Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi

Department of Otorhinolaryngology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.

Published: November 2009

AI Article Synopsis

  • The study aimed to investigate the characteristics of speech-evoked auditory brainstem responses (ABR) and how they relate to the acoustic properties of speech sounds, comparing these with traditional click-ABR.
  • Data was collected from 31 healthy young adults using synthesized speech and standard click sounds to identify and analyze ABR components through established protocols and advanced software.
  • Results showed distinct components in speech-ABR with significant correlations in latencies, indicating similarities with click-ABR and highlighting specific delays in response to speech sounds versus clicks.

Article Abstract

Objective: To determine the electrophysiological characteristics of speech evoked-ABR, which are then related to the acoustic properties of stimulus sound in terms of the latencies of the main components, and moreover compared to the conventional click-ABR to explore their underlying relationships.

Methods: The speech-ABR and click-ABR were recorded from 31 healthy young adults without any hearing problem examined by audiometric screen processes. The speech syllable/da/was synthesized by Klatt method. The ABRs recorded by the same clinic certificated instrument following established protocols and the stimulus sound was processed and analyzed in both time and frequency domain by a software package developed on Matlab platform.

Results: The main components of speech-ABR were clearly identified, and were categorized into onset response, frequency following response, transitional response and offset response in responding to the stimulus sound structure involving consonant and vowel portions. The latency of peak A significantly correlated with that of peaks V, C, D, E and F respectively (P < 0.05), especially with V. Furthermore, the latencies of peak D, E, and F are significantly correlated with each other (P < 0.01). Transitional component peak C was only correlated with peak V and A (P < 0.05); and offset wave O was independent to all the other peaks (P > 0.05). The latencies of speech-V and peak III were significantly delayed in comparison with their counterparts of click-ABR (P < 0.01). It was observed that the appearance rate of wave III was significantly lower than that of click-III (P < 0.01), while there was no significant delay and low appearance rate for wave-I observed in speech-ABR (P > 0.05).

Conclusions: This study verified the clear patterns of speech-ABR from healthy adults, the main components of which are closely related and analogues to the combination of the main waves of click-ABR, SN10 and FFR evoked by low-frequency tone. It offers a promising tool in the study of speech coding and processing mechanism.

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