Improving the Classifier Performance in Motor Imagery Task Classification: What are the steps in the classification process that we should worry about?

Bibliographic Details
Title: Improving the Classifier Performance in Motor Imagery Task Classification: What are the steps in the classification process that we should worry about?
Authors: Miriam Seoane Santos, Pedro Henriques Abreu, Rodríguez-Bermúdez Germán, Pedro J. García-Laencina
Source: International Journal of Computational Intelligence Systems, Vol 11, Iss 1 (2018)
Publisher Information: Springer, 2018.
Publication Year: 2018
Collection: LCC:Electronic computers. Computer science
Subject Terms: Brain Computer Interface Systems, Motor Imagery Tasks, Pattern Recognition, Machine Learning, Electronic computers. Computer science, QA75.5-76.95
More Details: Brain-Computer Interface systems based on motor imagery are able to identify an individual’s intent to initiate control through the classification of encephalography patterns. Correctly classifying such patterns is instrumental and strongly depends in a robust machine learning block that is able to properly process the features extracted from a subject’s encephalograms. The main objective of this work is to provide an overall view on machine learning stages, aiming to answer the following question: “What are the steps in the classification process that we should worry about?”. The obtained results suggest that future research in the field should focus on two main aspects: exploring techniques for dimensionality reduction, in particular, supervised linear approaches, and evaluating adequate validation schemes to allow a more precise interpretation of results.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1875-6883
Relation: https://www.atlantis-press.com/article/25902766/view; https://doaj.org/toc/1875-6883
DOI: 10.2991/ijcis.11.1.95
Access URL: https://doaj.org/article/7036dff403d04d2f8d0de51441593332
Accession Number: edsdoj.7036dff403d04d2f8d0de51441593332
Database: Directory of Open Access Journals
More Details
ISSN:18756883
DOI:10.2991/ijcis.11.1.95
Published in:International Journal of Computational Intelligence Systems
Language:English