Electroencephalography Data Preprocessing

Abstract : Electroencephalography provides measurements of electrical potential in the form of a time signal for each electrode. Although they only partially reflect the brain's underlying electrophysiological phenomena, these measurements contain a significant amount of information, which is used in clinical diagnosis and cognitive sciences, as well brain computer interfaces. Statistical analysis is also necessary to assess the stability of the information extracted with respect to different parameters. The sampling frequency determines the temporal resolution of observable phenomena, as well as the extent of the analyzable frequency spectrum. Brain-computer interfaces (BCI) is more common for marking to be performed automatically during acquisition. A low-pass filter removes high frequencies, eliminating some sources of noise, such as electrical activity coming from muscles. Statistical representations are useful for analyzing sets of signals measured simultaneously or through several trials. It is certainly also interesting to apply them retrospectively to interpret brain activity modifications occurring before, during and after BCI use.
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Chapitre d'ouvrage
Maureen Clerc; Laurent Bougrain; Fabien Lotte. Brain-Computer Interfaces 1, Wiley-ISTE, 2016, 978-1-84821-826-0. 〈10.1002/9781119144977.ch6〉
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https://hal.inria.fr/hal-01409009
Contributeur : Maureen Clerc <>
Soumis le : lundi 5 décembre 2016 - 15:54:00
Dernière modification le : jeudi 11 janvier 2018 - 16:54:47

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Maureen Clerc. Electroencephalography Data Preprocessing. Maureen Clerc; Laurent Bougrain; Fabien Lotte. Brain-Computer Interfaces 1, Wiley-ISTE, 2016, 978-1-84821-826-0. 〈10.1002/9781119144977.ch6〉. 〈hal-01409009〉

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