EEG on-line analysis for autonomous adaptive interface

Ishiwaka, Yuko; Yokoi, Hiroshi; Kakazu, Yukinori

doi:10.1016/s0531-5131(01)00721-x

Cited by 1 publication

(1 citation statement)

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“…Although bio-electrical signal was known since late 1840s, forms of BCI (Brain Computer Interface), which facilitates human-system interaction using various biosignals, were introduced only in 1970s. Later on, through various researches (Hesham, 2003;Yuko, 2002;Pfurtscheller et al, 1996), basic interface functions such as controlling mouse cursors by EEG signal are being reported. On the other hand, there were substantial researches attempting to discriminate emotional state of human beings in real life situation such as fatigue, drowsiness, and general stress level using bio-physiological signals (Eoh et.…”

Section: Introductionmentioning

confidence: 99%

Classification of Bluffing Behavior and Affective Attitude from Prefrontal Surface Encephalogram During On-Line Game

Yun

Lee

et al. 2005

Advances in Biometrics

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The purpose of this research was to detect the pattern of player's emotional change during on-line game. By defining data processing technique and analysis method for bio-physiological activity and player's bluffing behavior, the classification of affective attitudes during on-line game was attempted. Bluffing behavior displayed during the game was classified into two dimensions of emotional axis based on prefrontal surface electroencephalographic data. Classified bluffing attitudes were: (1) pleasantness/unpleasantness; and (2) honesty/bluffing. A multilayer-perception neural network was used to classify the player state into four attitude categories. Resulting classifier showed moderate performance with 67.03% pleasantness/unpleasantness classification, and 77.51% for honesty/bluffing. The classifier model developed in this study was integrated to on-line game as a form of 'emoticon' which displays facial expression of opposing player's emotional state.

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Section: Introductionmentioning

confidence: 99%