DocumentCode :
3506516
Title :
A study on relationship between personal feature of EEG and human´s characteristic for BCI based on mental state
Author :
Ito, Shin-ichi ; Mitsukura, Yasue ; Sato, Katsuya ; Fujisawa, Shoichiro ; Fukumi, Minoru
Author_Institution :
Univ. of Tokushima, Tokushima, Japan
fYear :
2009
fDate :
3-5 Nov. 2009
Firstpage :
4229
Lastpage :
4232
Abstract :
This paper discusses the relationship the result classified the electroencephalogram (EEG) patterns while listening to music and the human´s nature, which indicates the personal feature of a human, based on the egogram pattern. The EEG analysis calculates the power spectra of the frequency of the EEG signal, divides into the frequency bands based on theta, alpha, and beta rhythms, and evaluates whether the music matches mood of the user or not through EEG pattern classification. A k-nearest neighbor classifier is used to classify the EEG patterns. The egogram is used for detecting nature of the human. Finally, we discuss the relationship the result of EEG pattern classification and the human´s nature. An interesting finding was that the recognition accuracy of the EEG pattern meaning the response of them on negative stimuli became high when the subject was classified into the egogram pattern with introverted nature.
Keywords :
brain-computer interfaces; electroencephalography; feature extraction; medical signal processing; pattern classification; signal classification; BCI; EEG; brain computer interface; egogram; electroencephalogram; k-nearest neighbor classifier; pattern classification; Electroencephalography; Frequency conversion; Humans; Mood; Multiple signal classification; Pattern analysis; Pattern classification; Pattern matching; Rhythm; Signal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE
Conference_Location :
Porto
ISSN :
1553-572X
Print_ISBN :
978-1-4244-4648-3
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2009.5415062
Filename :
5415062
Link To Document :
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