The Riemannian Potato: an automatic and adaptive artifact detection method for online experiments using Riemannian geometry - Archive ouverte HAL Access content directly
Conference Papers Year : 2013

The Riemannian Potato: an automatic and adaptive artifact detection method for online experiments using Riemannian geometry

Anton Andreev
Marco Congedo

Abstract

Artifacts management is a critical problem in any applications involving on-line processing of EEG signals. This paper presents a multivariate automatic and adaptive method for identifying artifacts in continuous EEG data.
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Dates and versions

hal-00781701 , version 1 (28-01-2013)

Identifiers

  • HAL Id : hal-00781701 , version 1

Cite

Alexandre Barachant, Anton Andreev, Marco Congedo. The Riemannian Potato: an automatic and adaptive artifact detection method for online experiments using Riemannian geometry. TOBI Workshop lV, Jan 2013, Sion, Switzerland. pp.19-20. ⟨hal-00781701⟩
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