Optimising weighted averaging for auditory brainstem response detection
Optimising weighted averaging for auditory brainstem response detection
The auditory brainstem response (ABR) is a clinical test used to evaluate hearing objectively. The aim of this study was to optimise weighted averaging for both residual noise reduction and also for objective ABR detection using the Fmp statistical test. Analyses were performed using no-stimulus EEG background activity recorded from 15 participants and simulated “response present” data (4,602 ensembles in total). Different approaches for estimating the variance of the noise within each block were compared, as was the effect of the number of recording epochs in each block when calculating and applying the weights. The “VAR Whole Block” method was found to be more effective than the “VAR MP” method at estimating the noise level, especially for smaller block sizes (2–10 epochs). Caution should be exerted when selecting recording parameters for use with weighted averaging as an inflation in the “response absent” Fmp statistic was observed using small block sizes (relative to unweighted averaging); this may be due to a bias in the Fmp statistic observed as a result of the combined effects of the finite Fmp analysis window length and the high-pass filter setting. Optimised weighted averaging was effective in reducing the mean residual noise level in the averaged waveform, leading to improved ABR detection. Further work is required to optimise the Fmp analysis window length, recording settings, and weighted averaging parameters in combination, using a large clinical dataset.
Auditory brainstem response, Weighted averaging, Evoked potentials, EEG, Signal processing
McKearney, Richard Michael
279c26fc-e03a-48c2-9b43-8d3d6d877407
Bell, Steven
91de0801-d2b7-44ba-8e8e-523e672aed8a
Chesnaye, Michael
5f337509-3255-4322-b1bf-d4d3836b36ec
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
May 2023
McKearney, Richard Michael
279c26fc-e03a-48c2-9b43-8d3d6d877407
Bell, Steven
91de0801-d2b7-44ba-8e8e-523e672aed8a
Chesnaye, Michael
5f337509-3255-4322-b1bf-d4d3836b36ec
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
McKearney, Richard Michael, Bell, Steven, Chesnaye, Michael and Simpson, David
(2023)
Optimising weighted averaging for auditory brainstem response detection.
Biomedical Signal Processing and Control, 83, [104676].
(doi:10.1016/j.bspc.2023.104676).
Abstract
The auditory brainstem response (ABR) is a clinical test used to evaluate hearing objectively. The aim of this study was to optimise weighted averaging for both residual noise reduction and also for objective ABR detection using the Fmp statistical test. Analyses were performed using no-stimulus EEG background activity recorded from 15 participants and simulated “response present” data (4,602 ensembles in total). Different approaches for estimating the variance of the noise within each block were compared, as was the effect of the number of recording epochs in each block when calculating and applying the weights. The “VAR Whole Block” method was found to be more effective than the “VAR MP” method at estimating the noise level, especially for smaller block sizes (2–10 epochs). Caution should be exerted when selecting recording parameters for use with weighted averaging as an inflation in the “response absent” Fmp statistic was observed using small block sizes (relative to unweighted averaging); this may be due to a bias in the Fmp statistic observed as a result of the combined effects of the finite Fmp analysis window length and the high-pass filter setting. Optimised weighted averaging was effective in reducing the mean residual noise level in the averaged waveform, leading to improved ABR detection. Further work is required to optimise the Fmp analysis window length, recording settings, and weighted averaging parameters in combination, using a large clinical dataset.
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Accepted/In Press date: 4 February 2023
e-pub ahead of print date: 13 February 2023
Published date: May 2023
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Funding Information:
This work was supported by a studentship from the University of Southampton. For the purpose of open access, the authors have applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. The authors are thankful to Sara M.K. Madsen and James M. Harte for allowing use of the no-stimulus EEG data and to Debbie Cane for collecting the ABR data. Thank you to Dr Jaime Undurraga for the advice regarding the Fmp analysis window length. The authors gratefully acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton. The authors would like to thank the anonymous reviewers for their helpful feedback on the original manuscript.
Publisher Copyright:
© 2023 The Author(s)
Keywords:
Auditory brainstem response, Weighted averaging, Evoked potentials, EEG, Signal processing
Identifiers
Local EPrints ID: 475258
URI: http://eprints.soton.ac.uk/id/eprint/475258
ISSN: 1746-8094
PURE UUID: 1d8d5b32-1aaf-497f-a172-3ddc3225480b
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Date deposited: 14 Mar 2023 17:53
Last modified: 17 Mar 2024 02:56
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Author:
Richard Michael McKearney
Author:
Michael Chesnaye
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