EEGNAS: Neural Architecture Search for Electroencephalography Data Analysis and Decoding

Elad Rapaport, Oren Shriki, Rami Puzis

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

15 Scopus citations

Abstract

EEG, Electroencephalography, is the acquisition and decoding of electric brain signals. The data acquired from EEG scans can be put to use in many fields, including seizure prediction, treatment of mental illness, brain-computer interfaces (BCIs) and more. Recent advances in deep learning (DL) in fields of image classification and natural language processing have motivated researchers to apply DL for classification of EEG signals as well. One major caveat in DL is the amount of human effort and expertise required for the development of efficient and effective neural network architectures. Neural architecture search algorithms are used to automatically find good enough neural network architectures for a problem and dataset at hand. In this research, we employ genetic algorithms for optimizing neural network architectures for multiple tasks related to EEG processing while addressing two unique challenges related to EEG: (1) small amounts of labeled EEG data per subject, and (2) high diversity of EEG signal patterns across subjects. Neural network architectures produced during this study successfully compete with state of the art architectures published in the literature. Particularly successful are architectures optimized for all (human) subjects, with evolution and training performed on a mixed dataset including all subjects’ data.

Original languageEnglish
Title of host publicationHuman Brain and Artificial Intelligence - 1st International Workshop, HBAI 2019, held in Conjunction with IJCAI 2019, Revised Selected Papers
EditorsAn Zeng, Dan Pan, Tianyong Hao, Daoqiang Zhang, Yiyu Shi, Xiaowei Song
PublisherSpringer
Pages3-20
Number of pages18
ISBN (Print)9789811513978
DOIs
StatePublished - 1 Jan 2019
Event1st International Workshop on Human Brain and Artificial Intelligence, HBAI 2019, held in conjunction with the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 - Macao, China
Duration: 12 Aug 201912 Aug 2019

Publication series

NameCommunications in Computer and Information Science
Volume1072
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference1st International Workshop on Human Brain and Artificial Intelligence, HBAI 2019, held in conjunction with the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019
Country/TerritoryChina
CityMacao
Period12/08/1912/08/19

Keywords

  • EEG
  • Neural architecture search
  • Time series

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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