Identification of Auditory Object-Specific Attention from Single-Trial Electroencephalogram Signals via Entropy Measures and Machine Learning

Identification of Auditory Object-Specific Attention from Single-Trial Electroencephalogram Signals via Entropy Measures and Machine Learning

Existing research has revealed that auditory attention can be tracked from ongoing electroencephalography (EEG) signals. The aim of this novel study was to investigate the identification of peoples’ attention to a specific auditory object from single-trial EEG signals via entropy measures...

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Bibliographic Details
Main Authors: Yun Lu, Mingjiang Wang, Qiquan Zhang, Yufei Han
Format: Article
Language:English
Published: MDPI AG 2018-05-01
Series:Entropy
Subjects:
auditory attention
entropy measure
linear discriminant analysis (LDA)
support vector machine (SVM)
auditory attention classifier
electroencephalography (EEG)
Online Access:http://www.mdpi.com/1099-4300/20/5/386

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http://www.mdpi.com/1099-4300/20/5/386

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