A basic method for classifying humans based on an EEG analysis

Shin ichi Ito, Yasue Mitsukura, Minoru Fukumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008
Pages1783-1786
Number of pages4
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008 - Hanoi, Viet Nam
Duration: 2008 Dec 172008 Dec 20

Other

Other2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008
CountryViet Nam
CityHanoi
Period08/12/1708/12/20

Fingerprint

Electroencephalography
Power spectrum
Frequency bands
Monitoring

Keywords

  • Electroencephalogram
  • Human feature
  • Matching mood
  • Music

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Ito, S. I., Mitsukura, Y., & Fukumi, M. (2008). A basic method for classifying humans based on an EEG analysis. In 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008 (pp. 1783-1786). [4795798] https://doi.org/10.1109/ICARCV.2008.4795798

A basic method for classifying humans based on an EEG analysis. / Ito, Shin ichi; Mitsukura, Yasue; Fukumi, Minoru.

2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008. 2008. p. 1783-1786 4795798.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ito, SI, Mitsukura, Y & Fukumi, M 2008, A basic method for classifying humans based on an EEG analysis. in 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008., 4795798, pp. 1783-1786, 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008, Hanoi, Viet Nam, 08/12/17. https://doi.org/10.1109/ICARCV.2008.4795798
Ito SI, Mitsukura Y, Fukumi M. A basic method for classifying humans based on an EEG analysis. In 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008. 2008. p. 1783-1786. 4795798 https://doi.org/10.1109/ICARCV.2008.4795798
Ito, Shin ichi ; Mitsukura, Yasue ; Fukumi, Minoru. / A basic method for classifying humans based on an EEG analysis. 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008. 2008. pp. 1783-1786
@inproceedings{1ba712bda2a84b5bb19967dd8c2d51b6,
title = "A basic method for classifying humans based on an EEG analysis",
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 = "Electroencephalogram, Human feature, Matching mood, Music",
author = "Ito, {Shin ichi} and Yasue Mitsukura and Minoru Fukumi",
year = "2008",
doi = "10.1109/ICARCV.2008.4795798",
language = "English",
isbn = "9781424422876",
pages = "1783--1786",
booktitle = "2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008",

}

TY - GEN

T1 - A basic method for classifying humans based on an EEG analysis

AU - Ito, Shin ichi

AU - Mitsukura, Yasue

AU - Fukumi, Minoru

PY - 2008

Y1 - 2008

N2 - 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.

AB - 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.

KW - Electroencephalogram

KW - Human feature

KW - Matching mood

KW - Music

UR - http://www.scopus.com/inward/record.url?scp=64549157946&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=64549157946&partnerID=8YFLogxK

U2 - 10.1109/ICARCV.2008.4795798

DO - 10.1109/ICARCV.2008.4795798

M3 - Conference contribution

SN - 9781424422876

SP - 1783

EP - 1786

BT - 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008

ER -