Handling EEG artifacts and searching individually optimal experimental parameter in real time: a system development and demonstration.
Publication Date
2022-02-02Journal Title
J Neural Eng
ISSN
1741-2560
Publisher
IOP Publishing
Volume
19
Issue
1
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Ouyang, G., Dien, J., & Lorenz, R. (2022). Handling EEG artifacts and searching individually optimal experimental parameter in real time: a system development and demonstration.. J Neural Eng, 19 (1) https://doi.org/10.1088/1741-2552/ac42b6
Abstract
Objective.Neuroadaptive paradigms that systematically assess event-related potential (ERP) features across many different experimental parameters have the potential to improve the generalizability of ERP findings and may help to accelerate ERP-based biomarker discovery by identifying the exact experimental conditions for which ERPs differ most for a certain clinical population. Obtaining robust and reliable ERPs online is a prerequisite for ERP-based neuroadaptive research. One of the key steps involved is to correctly isolate electroencephalography artifacts in real time because they contribute a large amount of variance that, if not removed, will greatly distort the ERP obtained. Another key factor of concern is the computational cost of the online artifact handling method. This work aims to develop and validate a cost-efficient system to support ERP-based neuroadaptive research.Approach.We developed a simple online artifact handling method, single trial PCA-based artifact removal (SPA), based on variance distribution dichotomies to distinguish between artifacts and neural activity. We then applied this method in an ERP-based neuroadaptive paradigm in which Bayesian optimization was used to search individually optimal inter-stimulus-interval (ISI) that generates ERP with the highest signal-to-noise ratio.Main results.SPA was compared to other offline and online algorithms. The results showed that SPA exhibited good performance in both computational efficiency and preservation of ERP pattern. Based on SPA, the Bayesian optimization procedure was able to quickly find individually optimal ISI.Significance.The current work presents a simple yet highly cost-efficient method that has been validated in its ability to extract ERP, preserve ERP effects, and better support ERP-based neuroadaptive paradigm.
Keywords
Paper, bayesian optimization, neuroadaptive research, EEG artifacts, event-related potentials
Sponsorship
Wellcome Trust (209139/Z/17/Z)
Identifiers
jneac42b6, ac42b6, jne-104732.r2
External DOI: https://doi.org/10.1088/1741-2552/ac42b6
This record's URL: https://www.repository.cam.ac.uk/handle/1810/335083
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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