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Development and Evaluation of Automated Tools for Auditory-Brainstem and Middle-Auditory Evoked Potentials Waves Detection and Annotation

Authors :
Ourania Manta
Michail Sarafidis
Nikolaos Vasileiou
Winfried Schlee
Christos Consoulas
Dimitris Kikidis
Evgenia Vassou
George K. Matsopoulos
Dimitrios D. Koutsouris
Source :
Brain Sciences, Vol 12, Iss 12, p 1675 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Auditory evoked potentials (AEPs) are brain-derived electrical signals, following an auditory stimulus, utilised to examine any obstructions along the brain neural-pathways and to diagnose hearing impairment. The clinical evaluation of AEPs is based on the measurements of the latencies and amplitudes of waves of interest; hence, their identification is a prerequisite for AEP analysis. This process has proven to be complex, as it requires relevant clinical experience, and the existing software for this purpose has little practical use. The aim of this study was the development of two automated annotation tools for ABR (auditory brainstem response)- and AMLR (auditory middle latency response)-tests. After the acquisition of 1046 raw waveforms, appropriate pre-processing and implementation of a four-stage development process were performed, to define the appropriate logical conditions and steps for each algorithm. The tools’ detection and annotation results, regarding the waves of interest, were then compared to the clinicians’ manual annotation, achieving match rates of at least 93.86%, 98.51%, and 91.51% respectively, for the three ABR-waves of interest, and 93.21%, 92.25%, 83.35%, and 79.27%, respectively, for the four AMLR-waves. The application of such tools in AEP analysis is expected to assist towards an easier interpretation of these signals.

Details

Language :
English
ISSN :
20763425
Volume :
12
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Brain Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.58a2c1bd4c804c41ae724f30f5033f10
Document Type :
article
Full Text :
https://doi.org/10.3390/brainsci12121675