A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application

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

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

2 Scopus citations

Abstract

A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2495-2500
Number of pages6
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
CountryCanada
CityVancouver
Period24/07/1629/07/16

Keywords

  • Brain-computer interface (bci)
  • Electroencephalography (EEG)
  • Fuzzy integral
  • Motor imagery (mi)
  • Particle swarm optimization (pso)

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