BibTeX_22E

@InProceedings{10.1007/978-3-030-91308-3_3,

  author    = {Rosero-Rodr{\'i}guez, Christian Camilo and Alfonso-Morales, Wilfredo},

  booktitle = {Applications of Computational Intelligence},

  title     = {Automated preprocessing pipeline in visual imagery tasks},

  year      = {2022},

  address   = {Cham},

  editor    = {Orjuela-Ca{\~{n}}{\'o}n, Alvaro David and Lopez, Jesus A. and Arias-Londo{\~{n}}o, Juli{\'a}n David and Figueroa-Garc{\'i}a, Juan Carlos},

  pages     = {31--52},

  publisher = {Springer International Publishing},

  abstract  = {The EEG recordings contain complex and high-resolution temporal information, representing great challenges from the point of view of data processing: high contamination of artifacts, large sample sizes, reproducibility of the procedure, and the number of EEG channels. However, traditional approaches still use manual rejection, which is unsustainable. This article proposes an automatic preprocessing procedure for shared neural representations between imagery and visual perception over four frequency bands (theta, alpha, low beta, high beta). The idea is to improve the feature extraction procedure by identifying and interpolating faulty channels and rejecting bad epochs due to significantly noisy signals. Here, we include multiple filtering steps, robust common reference with PREP, artifact rejection, noisily channel identification and interpolation, and faulty epoch reconstruction and rejection to improve multivariate pattern analysis - MVPA. This latter represents the data decoding accuracy on the time-frequency domain.},

  isbn      = {978-3-030-91308-3},

}