Transfer Learning of Spectrogram Image for Automatic Sleep Stage Classification

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most of the existing methods for automatic sleep stage classification are relying on hand-crafted features. In this paper, the goal is to develop a deep learning-based method that automatically exploits time-frequency spectrum of Electroencephalogram (EEG) signal, removing the need for manual feature extraction. Using Continuous Wavelet Transform (CWT), we extracted the time-frequency spectrogram for EEG signal of 10 healthy subjects and converted to RGB images. The images were classified using transfer learning of a pre-trained Convolutional Neural Network (CNN), AlexNet. The proposed method was evaluated using a publicly available dataset. Evaluation results show that our method can achieve state of the art accuracy, while having higher overall sensitivity.

Original languageEnglish
Title of host publicationImage Analysis and Recognition - 15th International Conference, ICIAR 2018, Proceedings
EditorsB. ter Haar Romeny, F. Karray, A. Campilho
Place of PublicationCham
PublisherSpringer Verlag
Pages522-528
Number of pages7
ISBN (Electronic)978-3-319-93000-8
ISBN (Print)978-3-319-92999-6
DOIs
Publication statusPublished - 1 Jan 2018
Event15th International Conference on Image Analysis and Recognition, ICIAR 2018 - Povoa de Varzim, Portugal
Duration: 27 Jun 201829 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Volume10882 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Image Analysis and Recognition, ICIAR 2018
CountryPortugal
CityPovoa de Varzim
Period27/06/1829/06/18

Keywords

  • Convolutional Neural Network
  • Deep learning
  • Discrete Wavelet Transform
  • Sleep stage classification
  • Spectrogram
  • Transfer learning

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  • Cite this

    Gharbali, A. A., Najdi, S., & Fonseca, J. M. (2018). Transfer Learning of Spectrogram Image for Automatic Sleep Stage Classification. In B. ter Haar Romeny, F. Karray, & A. Campilho (Eds.), Image Analysis and Recognition - 15th International Conference, ICIAR 2018, Proceedings (pp. 522-528). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10882 LNCS). Cham: Springer Verlag. https://doi.org/10.1007/978-3-319-93000-8_59