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DCLL—A Deep Network for Possible Real-Time Decoding of Imagined Words

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present a novel architecture for classifying imagined words from electroencephalogram (EEG) captured during speech imagery. The proposed architecture employs a sliding window with overlap for data augmentation (DA) and common spatial pattern (CSP) in order to derive the features. The dimensionality of features is reduced using linear discriminant analysis (LDA). Long short-term memory (LSTM) along with majority voting is used as the classifier. We call the proposed architecture the DCLL (DA-CSP-LDA-LSTM) architecture. On a publicly available imagined word dataset, the DCLL architecture achieves an accuracy of 85.2% for classifying the imagined words “in” and “cooperate”. Although this is around 7% less than the best result in the literature on this dataset, the DCLL architecture is roughly 300 times faster than the latter, making it a potential candidate for imagined word-based online BCI systems where the EEG signal needs to be classified in real time.

Original languageEnglish
Title of host publicationInternational Symposium on Intelligent Informatics - Proceedings of ISI 2022
EditorsSabu M. Thampi, Jayanta Mukhopadhyay, Marcin Paprzycki, Kuan-Ching Li
PublisherSpringer Science and Business Media Deutschland GmbH
Pages3-12
Number of pages10
ISBN (Print)9789811980930
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event7th International Symposium on Intelligent Informatics, ISI 2022 - Thiruvananthapuram, India
Duration: 31 Aug 2022 → 2 Sept 2022

Publication series

NameSmart Innovation, Systems and Technologies
Volume333
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference7th International Symposium on Intelligent Informatics, ISI 2022
Country/TerritoryIndia
CityThiruvananthapuram
Period31/08/22 → 2/09/22

Keywords

  • Csp
  • Data augmentation
  • Eeg
  • Imagined speech
  • Imagined word
  • Lda
  • Lstm
  • Online bci
  • Speech imagery

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