TY - GEN

T1 - The Study of Correlation Dimension of the EEG Signals in a State of Meditation by means of Empirical Mode Decomposition

AU - Dmitrieva, L.A.

AU - Kanunikov, I.E.

AU - Krivoshapova, M.N.

AU - KuperinY.A., Юрий Александрович

AU - Smetanin1, N.M.

AU - Shaptiley, M.A.

PY - 2014

Y1 - 2014

N2 - Abstract. The aim of this work was to develop an indicator for finding differences in the multichannel EEG of experienced and inexperienced subjects in the states of meditation and rest. As such an indicator, we have chosen the difference between the correlation dimensions of the EEG channels reconstructed attractors and the corresponding EMD-filtered correlation dimensions (we denote this difference as DifD2). Under the EMD- filtered EEG correlation dimension here we understand the correlation dimension calculated from EEG signal, in which the first two modes of empirical decomposition (EMD) are dropped. The authors previously showed that the sum of the first two EMD-modes of EEG are stochastic components (both physical and physiological noise). Thus, the smaller the difference DifD2, the less noise in the EEG signals. Calculations were performed for 5 experienced and 5 inexperienced subjects in the states of meditation and rest. Unfiltered correlation dimensions were calculated in the embedding dimension eq

AB - Abstract. The aim of this work was to develop an indicator for finding differences in the multichannel EEG of experienced and inexperienced subjects in the states of meditation and rest. As such an indicator, we have chosen the difference between the correlation dimensions of the EEG channels reconstructed attractors and the corresponding EMD-filtered correlation dimensions (we denote this difference as DifD2). Under the EMD- filtered EEG correlation dimension here we understand the correlation dimension calculated from EEG signal, in which the first two modes of empirical decomposition (EMD) are dropped. The authors previously showed that the sum of the first two EMD-modes of EEG are stochastic components (both physical and physiological noise). Thus, the smaller the difference DifD2, the less noise in the EEG signals. Calculations were performed for 5 experienced and 5 inexperienced subjects in the states of meditation and rest. Unfiltered correlation dimensions were calculated in the embedding dimension eq

KW - correlation dimension

KW - empirical mode decomposition (EMD)

KW - EMD- filtered correlation dimensions

KW - meditation

KW - indicator DifD2.

M3 - Conference contribution

SN - 978-618-81257-5-9

SP - 179

EP - 191

BT - 3rd SMTDA International Conference Proceedings, 11-14 June 2014, Lisbon, C. H. Skiadas (Ed), Lisbon Portugal, ISAST 2014, p.179-191

PB - ISAST

ER -