Identification of ERD using Fuzzy Inference Systems for Brain-Computer Interface | Zendy

Ioan Dziţac | Zendy; Tiberiu Vesselényi | Zendy; Radu Ţarcă | Zendy

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Identification of ERD using Fuzzy Inference Systems for Brain-Computer Interface

Author(s) -

Ioan Dziţac,

Tiberiu Vesselényi,

Radu Ţarcă

Publication year - 2011

Publication title -

international journal of computers communications and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.422

H-Index - 33

eISSN - 1841-9844

pISSN - 1841-9836

DOI - 10.15837/ijccc.2011.3.2126

Subject(s) - computer science , electroencephalography , brain–computer interface , interface (matter) , identification (biology) , human–computer interaction , inference , artificial intelligence , inference system , brain activity and meditation , fuzzy logic , fuzzy control system , adaptive neuro fuzzy inference system , machine learning , neuroscience , botany , bubble , maximum bubble pressure method , parallel computing , biology

A Brain-Computer Interface uses measurements of scalp electric potential (electroencephalography - EEG) reflecting brain activity, to communicate with external devices. Recent developments in electronics and computer sciences have enabled applications that may help users with disabilities and also to develop new types of Human Machine Interfaces. By producing modifications in their brain potential activity, the users can perform control of different devices. In order to perform actions, this EEG signals must be processed with proper algorithms. Our approach is based on a fuzzy inference system used to produce sharp control states from noisy EEG data.

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