EEG decoding for musical emotion with functional connectivity features

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Cite
Xu, Jiayang, et al. “EEG Decoding for Musical Emotion With Functional Connectivity Features”. Biomedical Signal Processing and Control, vol. 89, 2024, p. 105744, https://doi.org/10.1016/j.bspc.2023.105744.
Xu, J., Qian, W., Hu, L., Liao, G., & Tian, Y. (2024). EEG decoding for musical emotion with functional connectivity features. Biomedical Signal Processing and Control, 89, 105744. https://doi.org/10.1016/j.bspc.2023.105744
Xu, Jiayang, Wenxia Qian, Liangliang Hu, Guangyuan Liao, and Yin Tian. “EEG Decoding for Musical Emotion With Functional Connectivity Features”. Biomedical Signal Processing and Control 89 (2024): 105744. https://doi.org/10.1016/j.bspc.2023.105744.
Xu J, Qian W, Hu L, Liao G, Tian Y. EEG decoding for musical emotion with functional connectivity features. Biomedical Signal Processing and Control. 2024;89:105744.
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Medicine
Medicine (General)
Medical technology
Technology
Engineering (General)
Civil engineering (General)
Refrences
Title Journal Journal Categories Citations Publication Date
Fusion Graph Representation of EEG for Emotion Recognition

 Sensors
  • Technology: Chemical technology
  • Science: Chemistry: Analytical chemistry
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Science: Mathematics: Instruments and machines
  • Science: Chemistry: Analytical chemistry
  • Science: Chemistry
 11 2023
3DCANN: A spatio-temporal convolution attention neural network for EEG emotion recognition 2022
A review on nonlinear methods using electroencephalographic recordings for emotion recognition IEEE Transactions on Affective Computing 2021
Employing PCA and t-statistical approach for feature extraction and classification of emotion from multichannel EEG signal Egyptian Informatics Journal
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Science (General): Cybernetics: Information theory
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 71 2020
An Innovative Multi-Model Neural Network Approach for Feature Selection in Emotion Recognition Using Deep Feature Clustering

 Sensors
  • Technology: Chemical technology
  • Science: Chemistry: Analytical chemistry
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Science: Mathematics: Instruments and machines
  • Science: Chemistry: Analytical chemistry
  • Science: Chemistry
 22 2020
Refrences Analysis
Category Category Repetition
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry20
Science: Mathematics: Instruments and machines: Electronic computers. Computer science12
Science: Chemistry: Analytical chemistry10
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks8
Philosophy. Psychology. Religion: Psychology6
Technology: Chemical technology5
Science: Mathematics: Instruments and machines5
Science: Chemistry5
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics4
Medicine: Medicine (General): Medical technology4
Technology: Engineering (General). Civil engineering (General)3
Medicine: Medicine (General): Computer applications to medicine. Medical informatics3
Science: Biology (General)3
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software3
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware3
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system: Psychiatry3
Technology: Mechanical engineering and machinery2
Science: Science (General)2
Science: Science (General): Cybernetics: Information theory2
Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication2
Medicine: Medicine (General)1
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system: Psychiatry: Therapeutics. Psychotherapy1
Medicine1
Science1
Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine1
Technology: Electrical engineering. Electronics. Nuclear engineering1
The category Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry 20 is the most frequently represented among the references in this article. It primarily includes studies from IEEE Transactions on Affective Computing and Sensors. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year