Journal ArticleDOI
Influence of music liking on EEG based emotion recognition
Daimi Syed Naser,Goutam Saha +1 more
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TLDR
The study indicates that liking influences classification performance and also the temporal dynamics of emotional experience across these scales, and observes an inverted U relationship between the level of liking and arousal and dominance classification performance.About:
This article is published in Biomedical Signal Processing and Control.The article was published on 2021-02-01. It has received 38 citations till now. The article focuses on the topics: Valence (psychology).read more
Citations
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Journal ArticleDOI
EEG Based Emotion Recognition: A Tutorial and Review
Xiang Li,Yazhou Zhang,Prayag Tiwari,D. Song,Bin Hu,Meihong Yang,Zhigang Zhao,Neeraj Kumar,Pekka Marttinen +8 more
TL;DR: The recent representative works in the EEG-based emotion recognition research are reviewed and a tutorial is provided to guide the researchers to start from the beginning and the scientific basis of EEG- based emotion recognition in the psychological and physiological levels is introduced.
Journal ArticleDOI
Review on Emotion Recognition Based on Electroencephalography
TL;DR: In this article, the authors describe the common steps of an emotion recognition algorithm based on EEG from data acquisition, preprocessing, feature extraction, feature selection to classifier, and assess their classification effect.
Journal ArticleDOI
Three-dimensional feature maps and convolutional neural network-based emotion recognition
TL;DR: An emotion recognition method based on three‐dimensional feature maps and CNNs is proposed and the experimental results demonstrate that the proposed method has better classification accuracy than the state‐of‐the‐art methods.
Journal ArticleDOI
Revealing Preference in Popular Music Through Familiarity and Brain Response
Soravitt Sangnark,Phairot Autthasan,Puntawat Ponglertnapakorn,Phudit Chalekarn,Thapanun Sudhawiyangkul,Manatsanan Trakulruangroj,Sarita Songsermsawad,Rawin Assabumrungrat,Supalak Amplod,Kajornvut Ounjai,Theerawit Wilaiprasitporn +10 more
TL;DR: Wang et al. as mentioned in this paper investigated the distinction of music preference through familiarity scores, response times (response rates), and brain response (EEG) and found that the brain's right side outperformed its left side in classification performance.
Journal ArticleDOI
A new approach to recognition of human emotions using brain signals and music stimuli
TL;DR: An EEG-based emotion recognition model is developed, and a new emotion recognition method based on deep learning is proposed that performed well in a noiseless environment.
References
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Journal ArticleDOI
Collective dynamics of small-world networks
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
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A wavelet tour of signal processing
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
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An introduction to variable and feature selection
Isabelle Guyon,André Elisseeff +1 more
TL;DR: The contributions of this special issue cover a wide range of aspects of variable selection: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
Proceedings Article
A study of cross-validation and bootstrap for accuracy estimation and model selection
TL;DR: The results indicate that for real-word datasets similar to the authors', the best method to use for model selection is ten fold stratified cross validation even if computation power allows using more folds.
Journal ArticleDOI
The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms
TL;DR: In this article, the use of the fast Fourier transform in power spectrum analysis is described, and the method involves sectioning the record and averaging modified periodograms of the sections.