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Objective Detection of the Speech Frequency Following Response (sFFR): A Comparison of Two Methods

Speech frequency following responses (sFFRs) are increasingly used in translational auditory research. Statistically-based automated sFFR detection could aid response identification and provide a basis for stopping rules when recording responses in clinical and/or research applications. In this brie...

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Detalles Bibliográficos
Autores principales: Cheng, Fan-Yin, Smith, Spencer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869319/
https://www.ncbi.nlm.nih.gov/pubmed/35200259
http://dx.doi.org/10.3390/audiolres12010010
Descripción
Sumario:Speech frequency following responses (sFFRs) are increasingly used in translational auditory research. Statistically-based automated sFFR detection could aid response identification and provide a basis for stopping rules when recording responses in clinical and/or research applications. In this brief report, sFFRs were measured from 18 normal hearing adult listeners in quiet and speech-shaped noise. Two statistically-based automated response detection methods, the F-test and Hotelling’s T(2) (HT(2)) test, were compared based on detection accuracy and test time. Similar detection accuracy across statistical tests and conditions was observed, although the HT(2) test time was less variable. These findings suggest that automated sFFR detection is robust for responses recorded in quiet and speech-shaped noise using either the F-test or HT(2) test. Future studies evaluating test performance with different stimuli and maskers are warranted to determine if the interchangeability of test performance extends to these conditions.