Driving fatigue prediction with pre-event electroencephalography (EEG) via a recurrent fuzzy neural network

Yu Ting Liu, Shang Lin Wu, Kuang Pen Chou, Yang Yin Lin, Jie Lu, Guangquan Zhang, Wen-Chieh Lin, Chin Teng Lin

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

15 Scopus citations

Abstract

We propose an electroencephalography (EEG) prediction system based on a recurrent fuzzy neural network (RFNN) architecture to assess drivers' fatigue degrees during a virtual-reality (VR) dynamic driving environment. Prediction of fatigue degrees is a crucial and arduous biomedical issue for driving safety, which has attracted growing attention of the research community in the recent past. Meanwhile, combined with the benefits of measuring EEG signals facilitates, many EEG-based brain-computer interfaces (BCIs) have been developed for use in real-Time mental assessment. In the literature, EEG signals are severely blended with stochastic noise; therefore, the performance of BCIs is constrained by low resolution in recognition tasks. For this rationale, independent component analysis (ICA) is usually used to find a source mapping from original data that has been blended with unrelated artificial noise. However, the mechanism of ICA cannot be used in real-Time BCI design. To overcome this bottleneck, the proposed system in this paper utilizes a recurrent self-evolving fuzzy neural work (RSEFNN) to increase memory capability for adaptive noise cancellation when assessing drivers' mental states during a car driving task. The experimental results without the use of ICA procedure indicate that the proposed RSEFNN model remains superior performance compared with the state-of-Thearts models.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2488-2494
Number of pages7
ISBN (Electronic)9781509006250
DOIs
StatePublished - 7 Nov 2016
Event2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016 - Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016

Publication series

Name2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

Conference

Conference2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
Country/TerritoryCanada
CityVancouver
Period24/07/1629/07/16

Keywords

  • Brain-computer interface (BCI)
  • Driving safety
  • Electroencephalography (EEG)
  • Fatigue prediction
  • Recurrent fuzzy neural network (rfnn)

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