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
Link To Document :
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