Automated cortical auditory response detection strategy.

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dc.contributor.author Bardy, Fabrice en
dc.contributor.author Van Dun, Bram en
dc.contributor.author Seeto, Mark en
dc.contributor.author Dillon, Harvey en
dc.date.accessioned 2020-08-17T01:14:37Z en
dc.date.issued 2020-06-26 en
dc.identifier.citation International journal of audiology 59(11):835-842 Nov 2020 en
dc.identifier.issn 1499-2027 en
dc.identifier.uri http://hdl.handle.net/2292/52575 en
dc.description.abstract Objective: This study describes a new automated strategy to determine the detection status of an electrophysiological response.Design: Response, noise and signal-to-noise ratio of the cortical auditory evoked potential (CAEP) were characterised. Detection rules were defined: when to start testing, when to conduct subsequent statistical tests using residual noise as an objective criterion, and when to stop testing.Study sample: Simulations were run to determine optimal parameters on a large combined CAEP data set collected in 45 normal-hearing adults and 17 adults with hearing loss.Results: The proposed strategy to detect CAEPs is fully automated. The first statistical test is conducted when the residual noise level is equal to or smaller than 5.1 µV. The succeeding Hotelling's T2 statistical tests are conducted using pre-defined residual noise levels criteria ranging from 5.1 to 1.2 µV. A rule was introduced allowing to stop testing before the maximum number of recorded epochs is reached, depending on a minimum p-value criterion.Conclusion: The proposed framework can be applied to systems which involves detection of electrophysiological responses in biological systems containing background noise. The proposed detection algorithm which optimise sensitivity, specificity, and recording time has the potential to be used in clinical setting. en
dc.format.medium Print-Electronic en
dc.language eng en
dc.relation.ispartofseries International journal of audiology en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri https://authorservices.taylorandfrancis.com/sharing-your-work/ en
dc.title Automated cortical auditory response detection strategy. en
dc.type Journal Article en
dc.identifier.doi 10.1080/14992027.2020.1767808 en
pubs.begin-page 1 en
dc.rights.holder Copyright: Taylor & Francis Group en
pubs.end-page 9 en
pubs.publication-status Published en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Journal Article en
pubs.elements-id 804696 en
pubs.org-id Science en
pubs.org-id Psychology en
dc.identifier.eissn 1708-8186 en
pubs.record-created-at-source-date 2020-06-27 en
pubs.dimensions-id 32589064 en


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