Research article summary (published 30 Aug 2002):

A new brain-computer interface design using fuzzy ARTMAP.

Full Abstract

This paper proposes a new brain-computer interface (BCI) design using fuzzy ARTMAP (FA) neural network, as well as an application of the design. The objective of this BCI-FA design is to classify the best three of the five available mental tasks for each subject using power spectral density (PSD) values of electroencephalogram (EEG) signals. These PSD values are extracted using the Wiener-Khinchine and autoregressive methods. Ten experiments employing different triplets of mental tasks are studied for each subject. The findings show that the average BCI-FA outputs for four subjects gave less than 6% of error using the best triplets of mental tasks identified from the classification performances of FA. This implies that the BCI-FA can be successfully used with a tri-state switching device. As an application, a proposed tri-state Morse code scheme could be utilized to translate the outputs of this BCI-FA design into English letters. In this scheme, the three BCI-FA outputs correspond to a dot and a dash, which are the two basic Morse code alphabets and a space to denote the end (or beginning) of a dot or a dash. The construction of English letters using this tri-state Morse code scheme is determined only by the sequence of mental tasks and is independent of the time duration of each mental task. This is especially useful for constructing letters that are represented as multiple dots or dashes. This combination of BCI-FA design and the tri-state Morse code scheme could be developed as a communication system for paralyzed patients.

Author information

Author/s: Palaniappan, Ramaswamy (R); Paramesran, Raveendran (R); Nishida, Shogo (S); Saiwaki, Naoki (N);

Affiliation: Faculty of Information Science and Technology, Multimedia University, 75450, Melaka, Malaysia.

Journal and publication information

Publication Type: Evaluation Studies; Journal Article

Journal: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society (IEEE Trans Neural Syst Rehabil Eng), published in United States. (Language: eng)

Reference: 2002-Sep; vol 10 (issue 3) : pp 140-8

Dates: Created 2002/12/30; Completed 2003/04/23; Revised 2004/11/17;

PMID: 12503778, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: 18 Feb 2009 00:00:00)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Brain - physiology Brain Mapping - methods Communication Aids for Disabled Electroencephalography - methods Fuzzy Logic Humans

Humans Mental Processes - classification; physiology Neural Networks (Computer) Pattern Recognition, Automated Signal Processing, Computer-Assisted User-Computer Interface

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