Emotion recognition from EEG signals by using multivariate empirical mode decomposition
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition
Link
http://link.springer.com/article/10.1007/s10044-016-0567-6/fulltext.html
Reference29 articles.
1. Alam SMS, Bhuiyan MI (2013) Detection of seizure and epilepsy using higher order statistics in the EMD domain. IEEE J Biomed Health Inf 17(2):312–318. doi: 10.1109/JBHI.2012.2237409
2. Bos DO (2006) EEG-based emotion recognition: the influence of visual and auditory stimuli. Available: http://hmi.ewi.utwente.nl/verslagen/capita-selecta/CS-Oude_Bos-Danny.pdf
3. Daimi SN, Saha G (2014) Classification of emotions induced by music videos and correlation with participants rating. Expert Syst Appl 41:6057–6065. doi: 10.1016/j.eswa.2014.03.050
4. Eftekhar A, Toumazou C, Drakakis EM (2013) Empirical mode decomposition: real-time implementation and applications. J Signal Process Syst 73(1):43–58. doi: 10.1007/s11265-012-0726-y
5. Flandrin P, Goncalves P (2004) Emprical mode decompositions as data-driven wavelet-like expansions. Int J Wavel Multiresolut Inf Process 02:477–496. doi: 10.1142/S0219691304000561
Cited by 180 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Emotion recognition of EEG signals based on contrastive learning graph convolutional model;Journal of Neural Engineering;2024-08-01
2. CATM: A Multi-Feature-Based Cross-Scale Attentional Convolutional EEG Emotion Recognition Model;Sensors;2024-07-25
3. Enhanced photoacoustic signal processing using empirical mode decomposition and machine learning;Nondestructive Testing and Evaluation;2024-06-30
4. An improved empirical mode decomposition method with ensemble classifiers for analysis of multichannel EEG in BCI emotion recognition;Computer Methods in Biomechanics and Biomedical Engineering;2024-06-26
5. Subject-Specific Feature Identification of Arousal and Valence Based on EEG;2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA);2024-06-26
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3