Title :
A basic method for classifying humans based on an EEG analysis
Author :
Ito, Shin-ichi ; Mitsukura, Yasue ; Fukumi, Minoru
Author_Institution :
Factory of Eng., Tokyo Univ. of Agric. & Technol., Koganei
Abstract :
This paper introduces a method for classifying humans by analyzing prefrontal cortex electroencephalogram (EEG) activity to extract and confirm distinct response features on listening to music that the user feels matches his/her mood, does not match his/her mood, or otherwise. The proposed method constitutes analyzing EEG signals obtained from monitoring human response features and classifying the human subjects according to the different frequency bands of the power spectrum of the EEG signal. The performance of the proposed method is evaluated using real EEG data. We confirm that we can classify humans into at least three groups.
Keywords :
electroencephalography; feature extraction; medical signal processing; EEG signals; distinct response feature extraction; human classification; human response features; prefrontal cortex electroencephalogram activity; Agriculture; Electroencephalography; Electronic mail; Humans; Independent component analysis; Indium tin oxide; Mood; Paper technology; Principal component analysis; Robotics and automation; electroencephalogram; human feature; matching mood; music;
Conference_Titel :
Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
Conference_Location :
Hanoi
Print_ISBN :
978-1-4244-2286-9
Electronic_ISBN :
978-1-4244-2287-6
DOI :
10.1109/ICARCV.2008.4795798