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Development and evaluation of automated tools for auditory-brainstem and middle-auditory evoked potentials waves detection and annotation

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dc.contributor.author Manta, Ourania
dc.contributor.author Sarafidis, Michail
dc.contributor.author Vasileiou, Nikolaos
dc.contributor.author Schlee, Winfried
dc.contributor.author Consoulas, Christos
dc.contributor.author Kikidis, Dimitris
dc.contributor.author Vassou, Evgenia
dc.contributor.author Matsopoulos, George
dc.contributor.author Koutsouris, Dimitris
dc.date.accessioned 2023-04-07T12:59:57Z
dc.date.available 2023-04-07T12:59:57Z
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/57525
dc.identifier.uri http://dx.doi.org/10.26240/heal.ntua.25222
dc.rights Default License
dc.subject auditory evoked potential en
dc.subject auditory brainstem response en
dc.subject auditory middle latency response en
dc.subject waveforms en
dc.subject automated wave-annotation en
dc.title Development and evaluation of automated tools for auditory-brainstem and middle-auditory evoked potentials waves detection and annotation en
heal.type journalArticle
heal.classification tinnitus en
heal.language en
heal.access free
heal.recordProvider ntua el
heal.publicationDate 2022-12-06
heal.bibliographicCitation O. Manta et al., “Development and Evaluation of Automated Tools for Auditory-Brainstem and Middle-Auditory Evoked Potentials Waves Detection and Annotation,” Brain Sci. 2022, Vol. 12, Page 1675, vol. 12, no. 12, p. 1675, Dec. 2022, doi: 10.3390/BRAINSCI12121675 en
heal.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. en
heal.publisher MDPI en
heal.journalName Brain Sciences en
heal.journalType peer-reviewed
heal.fullTextAvailability false
dc.identifier.doi https://doi.org/10.3390/brainsci12121675 el


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