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

Manta, Ourania; Sarafidis, Michail; Vasileiou, Nikolaos; Schlee, Winfried; Consoulas, Christos; Kikidis, Dimitris; Vassou, Evgenia; Matsopoulos, George; Koutsouris, Dimitris

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