• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.503-508
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• 2013

This study aims to analyze using RQA(Recurrence Quantification Analysis) about difference of electroencephalogram between inattention and attention among nonlinear methods for school age children who need attention. The experiments were conducted by 21 healthy subjects(12 males and 9 females). Inattention state is 500msec before the beginning of the auditory stimuli, attention state is 500msec after the beginning of auditory stimuli. The results of RQA parameters are greater in attention state than inattention state. It showed a statistically difference(p < 0.05). According to two states, auditory evoked potentials are displayed RP and CRP in diagram form to confirm nonlinear characteristics and The brain dynamics in the attention is more complex than the inattention. It is feasible that the RQA can be useful for the analysis of complex brain dynamics associated during auditory attentional task.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.195-205
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• 2013

The analysis of electroencephalographic signal associated with the attention is essential for the understanding of human cognition. In this paper, the characteristic differences between the attention and inattention status in the brain were inspected by nonlinear analysis. The recurrence quantification analysis was applied to the relatively small number of samples of evoked potential having time varying characteristics, where the recurrence plot (RP), the color recurrence plot (CRP), and mean and time-sequential trend parameters were extracted. The dimension and the time delay in phase transformation can be determined by the paired set of extracted parameters. It is observed from RP, CRP, and parameters that the brain dynamics in attention is more complex than that in the inattention, as well as the synchronized brain response is stable in the mean sense but locally time varying. It is feasible that the non-linear analysis method can be useful for the analysis of complex brain dynamics associated during visual attentional task.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.42-48
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• 2016

Since a variety of sound occur in same place and similar sound occurs in other places, the performance of acoustic scene classification is not guaranteed in case of insufficient training data. A Bag of Words (BOW) based histogram feature is foreseen as a method to overcome the problem. However, since the histogram features is made by using a feature distribution, the ordering of sequence of features is ignored. A temporal information such as periodicity and stationarity are also important for acoustic scene classification. In this paper, temporal features about a periodicity and a stationarity are extracted by using a recurrent quantification analysis. In the experiment, performance of the proposed method is shown better than other baseline methods.