Emotion recognition from multichannel EEG signals using K-nearest neighbor classification

M Li, H Xu, X Liu, S Lu - Technology and health care, 2018 - content.iospress.com
BACKGROUND: Many studies have been done on the emotion recognition based on multi-
channel electroencephalogram (EEG) signals. OBJECTIVE: This paper explores the …

SparseDGCNN: Recognizing emotion from multichannel EEG signals

G Zhang, M Yu, YJ Liu, G Zhao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Emotion recognition from EEG signals has attracted much attention in affective computing.
Recently, a novel dynamic graph convolutional neural network (DGCNN) model was …

EEG-based emotion charting for Parkinson's disease patients using Convolutional Recurrent Neural Networks and cross dataset learning

MN Dar, MU Akram, R Yuvaraj, SG Khawaja… - Computers in biology …, 2022 - Elsevier
Electroencephalogram (EEG) based emotion classification reflects the actual and intrinsic
emotional state, resulting in more reliable, natural, and meaningful human-computer …

Investigation of window size in classification of EEG-emotion signal with wavelet entropy and support vector machine

H Candra, M Yuwono, R Chai… - 2015 37th Annual …, 2015 - ieeexplore.ieee.org
When dealing with patients with psychological or emotional symptoms, medical practitioners
are often faced with the problem of objectively recognizing their patients' emotional state. In …

Support matrix machines

L Luo, Y Xie, Z Zhang, WJ Li - International conference on …, 2015 - proceedings.mlr.press
In many classification problems such as electroencephalogram (EEG) classification and
image classification, the input features are naturally represented as matrices rather than …

Core-brain-network-based multilayer convolutional neural network for emotion recognition

Z Gao, R Li, C Ma, L Rui, X Sun - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this article, we propose a method for emotion classification based on multilayer
convolutional neural network (MCNN) and combining differential entropy (DE) and brain …

[HTML][HTML] A comparison of emotion recognition system using electrocardiogram (ECG) and photoplethysmogram (PPG)

SNMS Ismail, NAA Aziz, SZ Ibrahim - Journal of King Saud University …, 2022 - Elsevier
Abstract Electrocardiogram (ECG) and Photoplethysmogram (PPG) are derived from
electrical signals of the heart activities and frequently used to diagnose and monitor …

Broad learning system for semi-supervised learning

Z Liu, S Huang, W Jin, Y Mu - Neurocomputing, 2021 - Elsevier
As an emerging technique for supervised learning, broad learning system (BLS) has been
proved to have many advantages such as fast learning speed, good generalization, etc …

Classification of EEG-based emotion for BCI applications

M Mohammadpour, SMR Hashemi… - 2017 Artificial …, 2017 - ieeexplore.ieee.org
Emotion plays an important role in human daily life and is a significant feature for interaction
among people. Due to having adaptive role, it motivate human to respond stimuli in their …

Cross-subject and cross-gender emotion classification from EEG

JY Zhu, WL Zheng, BL Lu - World Congress on Medical Physics and …, 2015 - Springer
This paper aims to explore whether different persons share similar patterns for EEG
changing with emotions and examine the performance of cross-subject and crossgender …