DocumentCode
1612804
Title
EEG-Based Mental Task Classification in Hypnotized and Normal Subjects
Author
Solhjoo, Soroosh ; Nasrabadi, Ali Motie ; Golpayegani, Mohammad Reza Hashemi
Author_Institution
Biomed. Eng. Fac., Amirkabir Univ. of Technol., Tehran
fYear
2006
Firstpage
2041
Lastpage
2043
Abstract
EEG-based mental task classification is an approach to understand the processes in our brain which lead to our thoughts and behavior. Different mental tasks have been used for this purpose and we have chosen relaxation and imagination for our study. As well as normal conscious state, we have considered mental tasks performed in hypnosis which is defined as a state of consciousness with high concentration. To assess nonlinear dynamics, we have considered fractal dimension in addition to frequency features. HMM classifiers have been used for classification. Results show the most important features in EEG signal related to mentioned mental tasks as well as differences between normal and hypnotic states of the brain
Keywords
electroencephalography; fractals; hidden Markov models; medical signal processing; signal classification; EEG-based mental task classification; HMM classifiers; brain; fractal dimension; hypnosis; hypnotized subjects; imagination; nonlinear dynamics; normal conscious state; normal subjects; relaxation; Biomedical engineering; Biomedical signal processing; Brain modeling; Electroencephalography; Feature extraction; Fractals; Frequency; Hidden Markov models; Problem-solving; Rhythm;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location
Shanghai
Print_ISBN
0-7803-8741-4
Type
conf
DOI
10.1109/IEMBS.2005.1616858
Filename
1616858
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