Literature DB >> 26737669

Recognition and regionalization of emotions in the arousal-valence plane.

P A Bustamante, N M Lopez Celani, M E Perez, O L Quintero Montoya.   

Abstract

The emotion recognition systems have become important for the diversity of its applications. Several methodologies have been proposed based on how emotions are reflected in biological systems, such as facial expressions, the activity of the nervous system or the prosody of voice. The detection of emotions by voice processing is an approach that involves a noninvasive procedure that produces results with an acceptable rate of detection. In this work an algorithm for features extraction was developed, that efficiently classify different emotional states. Thus, emotions that have not been trained can be associated with a trained emotion both belonging to the same region of the valence-arousal plane.

Mesh:

Year:  2015        PMID: 26737669     DOI: 10.1109/EMBC.2015.7319769

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Internet-of-Things-Enabled Data Fusion Method for Sleep Healthcare Applications.

Authors:  Fan Yang; Qilu Wu; Xiping Hu; Jiancong Ye; Yuting Yang; Haocong Rao; Rong Ma; Bin Hu
Journal:  IEEE Internet Things J       Date:  2021-03-22       Impact factor: 10.238

2.  Nuclear Norm Regularized Deep Neural Network for EEG-Based Emotion Recognition.

Authors:  Shuang Liang; Mingbo Yin; Yecheng Huang; Xiubin Dai; Qiong Wang
Journal:  Front Psychol       Date:  2022-06-29

Review 3.  EEG-Based BCI Emotion Recognition: A Survey.

Authors:  Edgar P Torres P; Edgar A Torres; Myriam Hernández-Álvarez; Sang Guun Yoo
Journal:  Sensors (Basel)       Date:  2020-09-07       Impact factor: 3.576

  3 in total

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