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Intelligent automat...
Intelligent automated eeg artifacts handling using wavelet transform, independent component analysis and hierarchal clustering
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- Barua, Shaibal (author)
- Mälardalens högskola,Inbyggda system
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- Begum, Shahina, 1977- (author)
- Mälardalens högskola,Inbyggda system
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- Ahmed, Mobyen Uddin, 1976- (author)
- Mälardalens högskola,Inbyggda system
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(creator_code:org_t)
- 2017-06-06
- 2017
- English.
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In: Lect. Notes Inst. Comput. Sci. Soc. Informatics Telecommun. Eng.. - Cham : Springer Verlag. - 9783319588766 ; , s. 144-148
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Billions of interconnected neurons are the building block of the human brain. For each brain activity these neurons produce electrical signals or brain waves that can be obtained by the Electroencephalogram (EEG) recording. Due to the characteristics of EEG signals, recorded signals often contaminate with undesired physiological signals other than the cerebral signal that is referred to as the EEG artifacts such as the ocular or the muscle artifacts. Therefore, identification and handling of artifacts in the EEG signals in a proper way is becoming an important research area. This paper presents an automated EEG artifacts handling approach, combining Wavelet transform, Independent Component Analysis (ICA), and Hierarchical clustering. The effectiveness of the proposed approach has been examined and observed on real EEG recording. According to the result, the proposed approach identified artifacts in the EEG signals effectively and after handling artifacts EEG signals showed acceptable considering visual inspection. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Keyword
- Electroencephalogram (EEG)
- Hierarchical clustering
- Muscle artifacts
- Ocular artifacts
- Brain
- Health care
- Independent component analysis
- Mobile telecommunication systems
- Muscle
- Wavelet transforms
- Electrical signal
- Electro-encephalogram (EEG)
- Hier-archical clustering
- Independent component analysis(ICA)
- Physiological signals
- Recorded signals
- Visual inspection
- Electroencephalography
Publication and Content Type
- ref (subject category)
- kon (subject category)
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