Detail publikace

A comprehensive survey of evolutionary algorithms and metaheuristics in brain EEG-based applications

ARIF, M. REHMAN, F. SEKANINA, L. MALIK, A.

Originální název

A comprehensive survey of evolutionary algorithms and metaheuristics in brain EEG-based applications

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

Electroencephalography (EEG) has emerged as a primary non-invasive and mobile modality for understanding the complex workings of the human brain, providing invaluable insights into cognitive processes, neurological disorders, and brain-computer interfaces (BCI). Nevertheless, the volume of EEG data, the presence of artifacts, the selection of optimal channels, and the need for feature extraction from EEG data present considerable challenges in achieving meaningful and distinguishing outcomes for machine learning algorithms utilized to process EEG data. Consequently, the demand for sophisticated optimization techniques has become imperative to overcome these hurdles effectively. Evolutionary algorithms (EAs) and other nature-inspired metaheuristics have been applied as powerful design and optimization tools in recent years, showcasing their significance in addressing various design and optimization problems relevant to brain EEG based applications. This paper presents a comprehensive survey highlighting the importance of EAs and other metaheuristics in EEG-based applications. The survey is organized according to the main areas where EAs have been applied, namely artifact mitigation, channel selection, feature extraction, feature selection, and signal classification. Finally, the current challenges and future aspects of EAs in the context of EEG-based applications are discussed.

Klíčová slova

Evolutionary algorithms, Electroencephalography, EEG, optimization, nature-inspired metaheuristics

Autoři

ARIF, M.; REHMAN, F.; SEKANINA, L.; MALIK, A.

Vydáno

25. 9. 2024

ISSN

1741-2552

Periodikum

Journal of Neural Engineering

Ročník

21

Číslo

5

Stát

Spojené království Velké Británie a Severního Irska

Strany od

1

Strany do

25

Strany počet

25

URL

https://iopscience.iop.org/article/10.1088/1741-2552/ad7f8e

BibTex

@article{BUT189698,
  author="ARIF, M. and REHMAN, F. and SEKANINA, L. and MALIK, A.",
  title="A comprehensive survey of evolutionary algorithms and metaheuristics in brain EEG-based applications",
  journal="Journal of Neural Engineering",
  year="2024",
  volume="21",
  number="5",
  pages="1--25",
  doi="10.1088/1741-2552/ad7f8e",
  issn="1741-2552",
  url="https://iopscience.iop.org/article/10.1088/1741-2552/ad7f8e"
}