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Automatic identification of artifacts and unwanted physiologic signals in EEG and EOG during wakefulness

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00303256" target="_blank" >RIV/68407700:21230/17:00303256 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21730/17:00303256

  • Result on the web

    <a href="http://www.sciencedirect.com/science/article/pii/S174680941630132X" target="_blank" >http://www.sciencedirect.com/science/article/pii/S174680941630132X</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.bspc.2016.09.006" target="_blank" >10.1016/j.bspc.2016.09.006</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automatic identification of artifacts and unwanted physiologic signals in EEG and EOG during wakefulness

  • Original language description

    A set of computationally inexpensive methods for reliable and robust detection of undesired signals in the EEG and EOG was designed, implemented, and tested. This strategy includes detection of eye blinking, eye movements, muscle activity, and flat lines in multichannel EEG and EOG data. The proposed methodology was verified on real awake data acquired in controlled conditions (44 recordings of total length 26.38 h) during Maintenance of Wakefulness Tests (MWT). The algorithms worked reliably (average precision was 0.992 ± 0.006, accuracy 0.988 ± 0.006, sensitivity 0.985 ± 0.009, and F1 score 0.988 ± 0.006) and fast (1 h of recording processed in 46.2 ± 5.3 s). We suggest testing this versatile and fast methodology on other type of EEG recordings with modification of threshold parameters if needed. This article reports data from a clinical trials no. NCT01433315 and NCT01580761.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20301 - Mechanical engineering

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Biomedical Signal Processing and Control

  • ISSN

    1746-8094

  • e-ISSN

    1746-8108

  • Volume of the periodical

    31

  • Issue of the periodical within the volume

    January

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    10

  • Pages from-to

    381-390

  • UT code for WoS article

    000386984300042

  • EID of the result in the Scopus database

    2-s2.0-84987903150