Review and classification of emotion recognition based on EEG brain-computer interface system research: a systematic review
Recent developments and studies in brain-computer interface (BCI) technologies have
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
Review of affective computing in education/learning: Trends and challenges
Affect can significantly influence education/learning. Thus, understanding a learner's affect
throughout the learning process is crucial for understanding motivation. In conventional …
throughout the learning process is crucial for understanding motivation. In conventional …
Analytical mapping of opinion mining and sentiment analysis research during 2000–2015
The new transformed read-write Web has resulted in a rapid growth of user generated
content on the Web resulting into a huge volume of unstructured data. A substantial part of …
content on the Web resulting into a huge volume of unstructured data. A substantial part of …
A survey of affective brain computer interfaces: principles, state-of-the-art, and challenges
Affective states, moods and emotions, are an integral part of human nature: they shape our
thoughts, govern the behavior of the individual, and influence our interpersonal …
thoughts, govern the behavior of the individual, and influence our interpersonal …
Subject-independent EEG emotion recognition with hybrid spatio-temporal GRU-Conv architecture
G Xu, W Guo, Y Wang - Medical & Biological Engineering & Computing, 2023 - Springer
Recently, various deep learning frameworks have shown excellent performance in decoding
electroencephalogram (EEG) signals, especially in human emotion recognition. However …
electroencephalogram (EEG) signals, especially in human emotion recognition. However …
An EEG-based brain computer interface for emotion recognition and its application in patients with disorder of consciousness
Recognizing human emotions based on electroencephalogram (EEG) signals has received
a great deal of attentions. Most of the existing studies focused on offline analysis, and real …
a great deal of attentions. Most of the existing studies focused on offline analysis, and real …
Selecting feature subsets based on SVM-RFE and the overlapping ratio with applications in bioinformatics
X Lin, C Li, Y Zhang, B Su, M Fan, H Wei - Molecules, 2017 - mdpi.com
Feature selection is an important topic in bioinformatics. Defining informative features from
complex high dimensional biological data is critical in disease study, drug development, etc …
complex high dimensional biological data is critical in disease study, drug development, etc …
A review on EEG signals based emotion recognition
M Zangeneh Soroush, K Maghooli… - International …, 2017 - eprints.go2submission.com
Emotion recognition has become a very controversial issue in brain-computer interfaces
(BCIs). Moreover, numerous studies have been conducted in order to recognize emotions …
(BCIs). Moreover, numerous studies have been conducted in order to recognize emotions …
Emotion recognition by distinguishing appropriate EEG segments based on random matrix theory
P Sarma, S Barma - Biomedical Signal Processing and Control, 2021 - Elsevier
This work proposes an emotion recognition technique by distinguishing appropriate
electroencephalogram (EEG) segments from acquired signal for target emotions. Generally …
electroencephalogram (EEG) segments from acquired signal for target emotions. Generally …
ASRmiRNA: Abiotic Stress-Responsive miRNA Prediction in Plants by Using Machine Learning Algorithms with Pseudo K-Tuple Nucleotide Compositional Features
MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses.
Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop …
Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop …