Abstract Emotion recognition is attracting considerable interest among the research community. In this work, Empirical Mode Decomposition has been implemented to derive both statistical and nonlinear features from Wrist Pulse Signal classifying emotions namely anxiety boredom. signals were extracted 24 subjects using TETRIS game as a stimulus Fission Fusion approach. The acquired pre-processed ...

Empirical mode decomposition (EMD) is a signal processing method that produces data-driven time-frequency representation suited to characterize time-varying and nonlinear phenomena. In EMD, intrinsic functions (IMF) are sequentially estimated from the of interest represent different oscilation modes produce an orthogonal original information. Different algorithms have been proposed for EMD esti...

Abstract In view of the nonlinear characteristics of chaotic signal, a threshold denoising method of noisy chaotic signal based on empirical mode decomposition (EMD) is presented. Firstly, noisy chaotic signal is decomposed into several intrinsic mode function (IMF) by empirical mode decomposition. Secondly, the intrinsic mode functions of high frequency are respectively processed using thresho...