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Efficient detection of cortical auditory evoked potentials in adults using bootstrapped methods

Efficient detection of cortical auditory evoked potentials in adults using bootstrapped methods
Efficient detection of cortical auditory evoked potentials in adults using bootstrapped methods
Background: Statistical detection methods are useful tools for assisting clinicians with cortical auditory evoked potential (CAEP) detection, and can help improve the overall efficiency and reliability of the test. However, many of these detection methods rely on parametric distributions when evaluating test significance, and thus make various assumptions regarding the electroencephalogram (EEG) data. When these assumptions are violated, reduced test sensitivities and/or increased or decreased false-positive rates can be expected. As an alternative to the parametric approach, test significance can be evaluated using a bootstrap, which does not require some of the aforementioned assumptions. Bootstrapping also permits a large amount of freedom when choosing or designing the statistical test for response detection, as the distributions underlying the test statistic no longer need to be known prior to the test.

Objectives: To improve the reliability and efficiency of CAEP-related applications by improving the specificity and sensitivity of objective CAEP detection methods.

Design: The methods included in the assessment were Hotelling's T test, the Fmp, four modified q-sample statistics, and various template-based detection methods (calculated between the ensemble coherent average and some predefined template), including the correlation coefficient, covariance, and dynamic time-warping (DTW). The assessment was carried out using both simulations and a CAEP threshold series collected from 23 adults with normal hearing.

Results: The most sensitive method was DTW, evaluated using the bootstrap, with maximum increases in test sensitivity (relative to the conventional Hotelling's T test) of up to 30%. An important factor underlying the performance of DTW is that the template adopted for the analysis correlates well with the subjects' CAEP.

Conclusion: When subjects' CAEP morphology is approximately known before the test, then the DTW algorithm provides a highly sensitive method for CAEP detection.
0196-0202
574-583
Chesnaye, M.A.
5f337509-3255-4322-b1bf-d4d3836b36ec
Bell, S.L.
91de0801-d2b7-44ba-8e8e-523e672aed8a
Harte, James
cb728bc5-e20c-4547-8b1a-e76ff43977b5
Simonsen, L.B.
6cb1b8bb-edca-40ca-ab06-4cb831f3a072
Visram, A.
fc4d761f-6800-4dfe-ade3-11e2a19cf347
Stone, M.A.
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Munro, K.J.
bcb0f186-5af1-433e-9ed1-a2ee77f46381
Simpson, D.M.
53674880-f381-4cc9-8505-6a97eeac3c2a
Chesnaye, M.A.
5f337509-3255-4322-b1bf-d4d3836b36ec
Bell, S.L.
91de0801-d2b7-44ba-8e8e-523e672aed8a
Harte, James
cb728bc5-e20c-4547-8b1a-e76ff43977b5
Simonsen, L.B.
6cb1b8bb-edca-40ca-ab06-4cb831f3a072
Visram, A.
fc4d761f-6800-4dfe-ade3-11e2a19cf347
Stone, M.A.
11600fb5-532b-4b5e-b07a-f96047dae057
Munro, K.J.
bcb0f186-5af1-433e-9ed1-a2ee77f46381
Simpson, D.M.
53674880-f381-4cc9-8505-6a97eeac3c2a

Chesnaye, M.A., Bell, S.L., Harte, James, Simonsen, L.B., Visram, A., Stone, M.A., Munro, K.J. and Simpson, D.M. (2021) Efficient detection of cortical auditory evoked potentials in adults using bootstrapped methods. Ear and Hearing, 42 (3), 574-583. (doi:10.1097/AUD.0000000000000959).

Record type: Article

Abstract

Background: Statistical detection methods are useful tools for assisting clinicians with cortical auditory evoked potential (CAEP) detection, and can help improve the overall efficiency and reliability of the test. However, many of these detection methods rely on parametric distributions when evaluating test significance, and thus make various assumptions regarding the electroencephalogram (EEG) data. When these assumptions are violated, reduced test sensitivities and/or increased or decreased false-positive rates can be expected. As an alternative to the parametric approach, test significance can be evaluated using a bootstrap, which does not require some of the aforementioned assumptions. Bootstrapping also permits a large amount of freedom when choosing or designing the statistical test for response detection, as the distributions underlying the test statistic no longer need to be known prior to the test.

Objectives: To improve the reliability and efficiency of CAEP-related applications by improving the specificity and sensitivity of objective CAEP detection methods.

Design: The methods included in the assessment were Hotelling's T test, the Fmp, four modified q-sample statistics, and various template-based detection methods (calculated between the ensemble coherent average and some predefined template), including the correlation coefficient, covariance, and dynamic time-warping (DTW). The assessment was carried out using both simulations and a CAEP threshold series collected from 23 adults with normal hearing.

Results: The most sensitive method was DTW, evaluated using the bootstrap, with maximum increases in test sensitivity (relative to the conventional Hotelling's T test) of up to 30%. An important factor underlying the performance of DTW is that the template adopted for the analysis correlates well with the subjects' CAEP.

Conclusion: When subjects' CAEP morphology is approximately known before the test, then the DTW algorithm provides a highly sensitive method for CAEP detection.

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ChesnayeEtAl_EarAndHearing - Accepted Manuscript
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More information

Accepted/In Press date: 12 August 2020
e-pub ahead of print date: 30 November 2020
Published date: 1 May 2021
Additional Information: Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

Identifiers

Local EPrints ID: 448285
URI: http://eprints.soton.ac.uk/id/eprint/448285
ISSN: 0196-0202
PURE UUID: 0211d8f0-89bd-4000-a2ed-3b259bf3da3c
ORCID for D.M. Simpson: ORCID iD orcid.org/0000-0001-9072-5088

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Date deposited: 19 Apr 2021 16:31
Last modified: 17 Mar 2024 06:44

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Contributors

Author: M.A. Chesnaye
Author: S.L. Bell
Author: James Harte
Author: L.B. Simonsen
Author: A. Visram
Author: M.A. Stone
Author: K.J. Munro
Author: D.M. Simpson ORCID iD

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