Methods for Explaining CNN-Based BCI: A Survey of Recent Applications

Maksims Ivanovs, Beate Banga, Valters Āboliņš, Krisjanis Nesenbergs

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Convolutional neural networks (CNN) have achieved state-of-the-art results in many Brain-Computer Interface (BCI) tasks, yet their applications in real-world scenarios and attempts at further optimizing them may be hindered by their non-transparent, black box-like nature. While there has been ex-tensive research on the intersection of the fields of explainable artificial intelligence (AI) and computer vision on explaining CNN for image classification, it is an open question how commonly the methods for explaining CNNs are used when CNNs are a part of a BCI setup. In the present study, we survey BCI studies from 2020 to 2022 that deploy CNNs to find out how many of them use explainable AI methods for better understanding of CNNs and which such methods are used in particular. Our findings are that explainable AI methods were used in 13.7 percent of the surveyed publications, and the majority of the studies in which these methods were used employed the t-distributed stochastic neighbour embedding (t-SNE) method.

Original languageEnglish
Title of host publication2022 IEEE 16th International Scientific Conference on Informatics
Subtitle of host publicationProceedings
EditorsWilliam Steingartner, Stefan Korecko, Aniko Szakal
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages137-141
Number of pages5
ISBN (Electronic)9798350310344
ISBN (Print)979-8-3503-1035-1
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event16th IEEE International Scientific Conference on Informatics, Informatics 2022 - Poprad, Slovakia
Duration: 23 Nov 202225 Nov 2022
Conference number: 16
https://ieeexplore.ieee.org/xpl/conhome/10083311/proceeding

Publication series

NameIEEE International Scientific Conference on Informatics (IEEE Proceedings)
PublisherInstitute of Electrical and Electronics Engineers Inc.

Conference

Conference16th IEEE International Scientific Conference on Informatics, Informatics 2022
Country/TerritorySlovakia
CityPoprad
Period23/11/2225/11/22
Internet address

Keywords*

  • Brain-Computer Interface (BCI)
  • Convolutional Neural Networks (CNN)
  • Deep Learning
  • Deep Neural Networks (DNN)
  • Electroen-cephalography (EEG)
  • Explainable AI

Field of Science*

  • 1.2 Computer and information sciences

Publication Type*

  • 3.1. Articles or chapters in proceedings/scientific books indexed in Web of Science and/or Scopus database

Fingerprint

Dive into the research topics of 'Methods for Explaining CNN-Based BCI: A Survey of Recent Applications'. Together they form a unique fingerprint.

Cite this