Cross-individual Recognition of Emotions by a Dynamic Entropy based on Pattern Learning with EEG features

09/26/2020
by   Xiaolong Zhong, et al.
0

Use of the electroencephalogram (EEG) and machine learning approaches to recognize emotions can facilitate affective human computer interactions. However, the type of EEG data constitutes an obstacle for cross-individual EEG feature modelling and classification. To address this issue, we propose a deep-learning framework denoted as a dynamic entropy-based pattern learning (DEPL) to abstract informative indicators pertaining to the neurophysiological features among multiple individuals. DEPL enhanced the capability of representations generated by a deep convolutional neural network by modelling the interdependencies between the cortical locations of dynamical entropy based features. The effectiveness of the DEPL has been validated with two public databases, commonly referred to as the DEAP and MAHNOB-HCI multimodal tagging databases. Specifically, the leave one subject out training and testing paradigm has been applied. Numerous experiments on EEG emotion recognition demonstrate that the proposed DEPL is superior to those traditional machine learning (ML) methods, and could learn between electrode dependencies w.r.t. different emotions, which is meaningful for developing the effective human-computer interaction systems by adapting to human emotions in the real world applications.

READ FULL TEXT

page 10

page 15

page 17

09/20/2021

Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition

Emotion recognition plays a vital role in human-machine interactions and...
07/18/2021

Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity

Machine learning methods, such as deep learning, show promising results ...
05/10/2022

Human Emotion Classification based on EEG Signals Using Recurrent Neural Network And KNN

In human contact, emotion is very crucial. Attributes like words, voice ...
07/12/2022

Self-supervised Group Meiosis Contrastive Learning for EEG-Based Emotion Recognition

The progress of EEG-based emotion recognition has received widespread at...
03/05/2021

Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games

Human emotion recognition has become a need for more realistic and inter...
11/25/2021

Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism

Current models on Explainable Artificial Intelligence (XAI) have shown a...