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A Study on Algorithm of Emotion Analysis using EEG and HRV

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2010, 15(10), pp.105-112
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

전기환 1 오주영 2 Yeon-Man Jeong 3 양동일 4 박순희 5

1한림성심대학교
2경인여자대학
3강릉원주대학교
4한림성심대학
5강원대학교

Accredited

ABSTRACT

In this paper, the bio-signals, such as EEG, ECG were measured with a sensor and their characters were drawn out and analyzed. With results from the analysis, four emotion of rest, concentration, tension and depression were inferred. In order to assess one’s emotion, the characteristic vectors were drawn out by applying various ways, including the frequency analysis of the bio-signals like the measured EEG and HRV. RBFN, a neural network of the complex structure of unsupervised and supervised learning, was applied to classify and infer the deducted information. Through experiments, the system suggested in this thesis showed better capability to classify and infer than other systems using a different neural network. As follow-up research tasks, the recognizance rate of the measured bio-signals should be improved. Also, the technology which can be applied to the wired or wireless sensor measuring the bio-signals more easily and to wearable computing should be developed.

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