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Fuzzy Artmap classification of mental tasks using segmented and overlapped EEG signals

Palaniappan, Ramaswamy, Raveendran, P., Nishida, Shogo, Saiwaki, Naoki (2000) Fuzzy Artmap classification of mental tasks using segmented and overlapped EEG signals. In: 2000 TENCON Proceedings. 2. II 388-II 391. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Abstract

Visual inspection of EEG signals in their unprocessed form is still the predominant way of discriminating EEG patterns in the medical community and requires highly trained medical professionals. To overcome this problem, automatic EEG analysis using Fourier Transform methods are popular since most EEG signals consist of spectral power in the range of δ, θ, α and β i.e from 0 to 30 Hz. But this method suffers from high noise sensitivity and is not suitable for short and variable length of signal segments. In this paper, we analyze EEG signals with time series analysis using autoregression techniques. We classify these extracted features for different mental tasks using a Fuzzy ARTMAP classifier. We study the effects of different EEG segment or window lengths and different overlapping lengths on the overall performance of the classifier. Our results show that the segment length affects the performance and that overlapping the segments improves the performance greatly.

Item Type: Conference or workshop item (Proceeding)
Additional information: Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - IEEE Reg 10 Annu Int Conf Proc TENCON [Field not mapped to EPrints] AD - Univ of Malaya, Kuala Lumpur, Malaysia [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] A4 - IEEE [Field not mapped to EPrints] C3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON [Field not mapped to EPrints]
Uncontrolled keywords: Algorithms, Electrophysiology, Fourier transforms, Fuzzy control, Neurophysiology, Spectrum analyzers, Autoregressive spectral analysis, Electroencephalography
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 16:37 UTC
Last Modified: 30 May 2019 08:30 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70771 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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