An unsupervised multichannel artifact detection method for sleep EEG based on Riemannian geometry

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023752%3A_____%2F19%3A43919712" target="_blank" >RIV/00023752:_____/19:43919712 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/19:00328194 RIV/68407700:21460/19:00328194 RIV/68407700:21730/19:00328194 RIV/00216208:11120/19:43917610
Result on the web
<a href="https://www.mdpi.com/1424-8220/19/3/602" target="_blank" >https://www.mdpi.com/1424-8220/19/3/602</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/s19030602" target="_blank" >10.3390/s19030602</a>

Result language
angličtina
Original language name
An unsupervised multichannel artifact detection method for sleep EEG based on Riemannian geometry
Original language description
In biomedical signal processing, we often face the problem of artifacts that distort the original signals. This concerns also sleep recordings, such as EEG. Artifacts may severely affect or even make impossible visual inspection, as well as automatic processing. Many proposed methods concentrate on certain artifact types. Therefore, artifact-free data are often obtained after sequential application of different methods. Moreover, single-channel approaches must be applied to all channels alternately. The aim of this study is to develop a multichannel artifact detection method for multichannel sleep EEG capable of rejecting different artifact types at once. The inspiration for the study is gained from recent advances in the field of Riemannian geometry. The method we propose is tested on real datasets. The performance of the proposed method is measured by comparing detection results with the expert labeling as a reference and evaluated against a simpler method based on Riemannian geometry that has previously been proposed, as well as against the state-of-the-art method FASTER. The obtained results prove the effectiveness of the proposed method.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30404 - Biomaterials (as related to medical implants, devices, sensors)

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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