Search
Now showing items 1-5 of 5
Emotional State Sensing by Using Hybrid Multivariate Empirical Mode Decomposition and Synchrosqueezing Transform
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2018)
In recent years, utilizing Hilbert-based time frequency methods in emotional state sensing research attracted attention in the brain computer interfaces. Primarily, Hilbert Transform-based empirical mode decomposition (EMD) ...
Emotion Elicitation Analysis in Multi-Channel EEG Signals Using Multivariate Empirical Mode Decomposition and Discrete Wavelet Transform
(IEEE345 E 47TH ST, NEW YORK, NY 10017 USA, 2017)
In recent years, wavelet-based, Fourier-based and Hilbert-based time-frequency methods attracted attention in emotion state classification studies in human machine interaction. In particular, the Hilbert-based Empirical ...
Emotion Recognition Classification in EEG Signals Using Multivariate Synchrosqueezing Transform
(IEEE345 E 47TH ST, NEW YORK, NY 10017 USA, 2017)
Electrophysiological data processing can take place both in time and in frequency domains as well as in the joint time-frequency domain. Short Time Fourier Transform and Wavelet Transform are commonly used time-frequency ...
Multivariate Pseudo Wigner Ville Distribution based Emotion Detection from Electrical Activity of Brain
(IEEE 345 E 47TH ST, NEW YORK, NY 10017 USA, 2017)
Recently, there has been a rapid development in multivariate signal analysis to determine joint oscillations for multiple data channels. The emotion elicitation in an electroencephalogram (EEG) is a novel area to evaluate ...
Emotional State Analysis from EEG signals via Noise-Assisted Multivariate Empirical Mode Decomposition Method
(IEEE345 E 47TH ST, NEW YORK, NY 10017 USA, 2017)
Emotional state analysis is an interdisciplinary arena because of the many parameters that encompass the complex neural structure and electrical signals of the brain and in terms of emotional state differences. In recent ...