Related references
Note: Only part of the references are listed.Emotion detection using electroencephalography signals and a zero-time windowing-based epoch estimation and relevant electrode identification
Sofien Gannouni et al.
SCIENTIFIC REPORTS (2021)
Expression-EEG Bimodal Fusion Emotion Recognition Method Based on Deep Learning
Yu Lu et al.
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2021)
Recognition of human emotions using EEG signals: A review
Md. Mustafizur Rahman et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2021)
AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups
Juan Abdon Miranda-Correa et al.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2021)
Multimodal Emotion Recognition Using a Hierarchical Fusion Convolutional Neural Network
Yong Zhang et al.
IEEE ACCESS (2021)
Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living
Saifur Rahman et al.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020)
Emotion Recognition Related to Stock Trading Using Machine Learning Algorithms With Feature Selection
Edgar P. Torres et al.
IEEE ACCESS (2020)
Emotion Feature Analysis and Recognition Based on Reconstructed EEG Sources
Guijun Chen et al.
IEEE ACCESS (2020)
EmotionMeter: A Multimodal Framework for Recognizing Human Emotions
Wei-Long Zheng et al.
IEEE TRANSACTIONS ON CYBERNETICS (2019)
Emotion recognition from single-channel EEG signals using a two-stage correlation and instantaneous frequency-based filtering method
Sachin Taran et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2019)
Fear Level Classification Based on Emotional Dimensions and Machine Learning Techniques
Oana Balan et al.
SENSORS (2019)
Recognition of Emotional States Using Multiscale Information Analysis of High Frequency EEG Oscillations
Zhilin Gao et al.
ENTROPY (2019)
Accurate EEG-Based Emotion Recognition on Combined Features Using Deep Convolutional Neural Networks
J. X. Chen et al.
IEEE ACCESS (2019)
Interpretable Emotion Recognition Using EEG Signals
Chunmei Qing et al.
IEEE ACCESS (2019)
Real-Time Movie-Induced Discrete Emotion Recognition from EEG Signals
Yong-Jin Liu et al.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2018)
Decision Variants for the Automatic Determination of Optimal Feature Subset in RF-RFE
Qi Chen et al.
GENES (2018)
Wavelet-based emotion recognition system using EEG signal
Zeynab Mohammadi et al.
NEURAL COMPUTING & APPLICATIONS (2017)
Cloud-Supported Cyber-Physical Localization Framework for Patients Monitoring
M. Shamim Hossain
IEEE SYSTEMS JOURNAL (2017)
Real-time EEG-based emotion monitoring using stable features
Zirui Lan et al.
VISUAL COMPUTER (2016)
Application of Entropy-Based Metrics to Identify Emotional Distress from Electroencephalographic Recordings
Beatriz Garcia-Martinez et al.
ENTROPY (2016)
ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition
Jianhai Zhang et al.
SENSORS (2016)
A review of channel selection algorithms for EEG signal processing
Turky Alotaiby et al.
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING (2015)
Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients' Consciousness Level Based on Anesthesiologists Experience
George J. A. Jiang et al.
BIOMED RESEARCH INTERNATIONAL (2015)
EEG-based Emotion Recognition using Statistical measures and Auto-regressive modeling
Aravind E. Vijayan et al.
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION TECHNOLOGY CICT 2015 (2015)
Emotional state classification from EEG data using machine learning approach
Xiao-Wei Wang et al.
NEUROCOMPUTING (2014)
Feature Extraction and Selection for Emotion Recognition from EEG
Robert Jenke et al.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2014)
Emotion recognition based on the sample entropy of EEG
Xiang Jie et al.
BIO-MEDICAL MATERIALS AND ENGINEERING (2014)
Application of Multivariate Empirical Mode Decomposition and Sample Entropy in EEG Signals via Artificial Neural Networks for Interpreting Depth of Anesthesia
Jeng-Rung Huang et al.
ENTROPY (2013)
Practical considerations of permutation entropy
M. Riedl et al.
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS (2013)
DEAP: A Database for Emotion Analysis Using Physiological Signals
Sander Koelstra et al.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2012)
Combining Spatial Filtering and Wavelet Transform for Classifying Human Emotions Using EEG Signals
Murugappan Murugappan et al.
JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING (2011)
Machine learning: a review of classification and combining techniques
S. B. Kotsiantis et al.
ARTIFICIAL INTELLIGENCE REVIEW (2006)
Permutation entropy: A natural complexity measure for time series
C Bandt et al.
PHYSICAL REVIEW LETTERS (2002)
Stochastic gradient boosting
JH Friedman
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2002)
Share Paper
