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In this paper, we investigate stable patterns of electroencephalogram (EEG) over time for emotion recognition using a machine learning approach. Up to now, various findings of activated patterns associated with different emotions have been…

Human-Computer Interaction · Computer Science 2016-01-12 Wei-Long Zheng , Jia-Yi Zhu , Bao-Liang Lu

Detrend fluctuation analysis (DFA) has become a choice method for effective analysis of a broad variety of nonstationary signals. We show in the present article that, provided the nonstationary fluctuations occur at a large enough time…

Quantitative Methods · Quantitative Biology 2007-05-23 Luciano da Fontoura Costa , Ruth Caldeira de Melo , Ester da Silva , Audrey Borghi-Silva , Aparecida Maria Catai

Emotion is an inherently subjective psychophysiological human-state and to produce an agreed-upon representation (gold standard) for continuous emotion requires a time-consuming and costly training procedure of multiple human annotators.…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Alice Baird , Lukas Stappen , Lukas Christ , Lea Schumann , Eva-Maria Meßner , Björn W. Schuller

Affective brain-computer interfaces (aBCIs) are increasingly recognized for their potential in monitoring and interpreting emotional states through electroencephalography (EEG) signals. Current EEG-based emotion recognition methods perform…

Human-Computer Interaction · Computer Science 2024-07-31 Yue Pan , Qile Liu , Qing Liu , Li Zhang , Gan Huang , Xin Chen , Fali Li , Peng Xu , Zhen Liang

Motivated behaviour relies on the brain's capacity to evaluate effort and reward. Dysregulation within these processes contributes to a spectrum of conditions, from hyperactivity in attention-deficit/hyperactivity disorder (ADHD) to…

Neurons and Cognition · Quantitative Biology 2026-04-20 Nam Trinh

Emotion recognition is an important research direction in artificial intelligence, helping machines understand and adapt to human emotional states. Multimodal electrophysiological(ME) signals, such as EEG, GSR, respiration(Resp), and…

Multimedia · Computer Science 2023-08-07 Yunfei Guo , Tao Zhang , Wu Huang

This paper introduces variational representational similarity analysis RSA (vRSA) for electromagnetic recordings of neural responses (e.g., EEG, MEG, ECoG or LFP). Variational RSA is a Bayesian approach for testing whether the similarity of…

Neurons and Cognition · Quantitative Biology 2025-11-04 Alex Lepauvre , Lucia Melloni , Karl Friston , Peter Zeidman

Simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) is an emerging neuromodulation approach, that enables simultaneous volitional regulation of both hemodynamic (BOLD fMRI) and electrophysiological (EEG) brain activities. Here…

Neurons and Cognition · Quantitative Biology 2020-07-06 Vadim Zotev , Ahmad Mayeli , Masaya Misaki , Jerzy Bodurka

Emotional recognition through exploring the electroencephalography (EEG) characteristics has been widely performed in recent studies. Nonlinear analysis and feature extraction methods for understanding the complex dynamical phenomena are…

Signal Processing · Electrical Eng. & Systems 2022-05-10 Yan Yan , Xuankun Wu , Chengdong Li , Yini He , Zhicheng Zhang , Huihui Li , Ang Li , Lei Wang

Hindustani classical music is entirely based on the "Raga" structures. In Hindustani music, a "Gharana" or school refers to the adherence of a group of musicians to a particular musical style. Gharanas have their basis in the traditional…

Sound · Computer Science 2021-05-27 Archi Banerjee , Shankha Sanyal , Ranjan Sengupta , Dipak Ghosh

Ragas form the foundation for Indian Classical Music. The task of Raga Recognition has gained traction in the Music Information Retrieval community in the recent past, which can be attributed to the nuances of Indian Classical Music that…

Sound · Computer Science 2022-12-13 Devayani Hebbar , Vandana Jagtap

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noisy signals. Many noisy signals in real systems display trends, so that the scaling results obtained from the…

Data Analysis, Statistics and Probability · Physics 2009-11-07 Kun Hu , Plamen Ch. Ivanov , Zhi Chen , Pedro Carpena , H. Eugene Stanley

Electroencephalography (EEG) is a powerful non-invasive brain imaging technique with a high temporal resolution that has seen extensive use across multiple areas of cognitive science research. This thesis adapts representational similarity…

Neurons and Cognition · Quantitative Biology 2021-10-08 Feng Cheng

Electroencephalography (EEG) is a popular and effective tool for emotion recognition. However, the propagation mechanisms of EEG in the human brain and its intrinsic correlation with emotions are still obscure to researchers. This work…

Robotics · Computer Science 2022-09-26 Jiyao Liu , Hao Wu , Li Zhang , Yanxi Zhao

Electroencephalography (EEG) monitors ---by either intrusive or noninvasive electrodes--- time and frequency variations and spectral content of voltage fluctuations or waves, known as brain rhythms, which in some way uncover activity during…

Neurons and Cognition · Quantitative Biology 2019-03-13 Javier A. Galadí , Joaquín J. Torres , J. Marro

For several decades, electroencephalography (EEG) has featured as one of the most commonly used tools in emotional state recognition via monitoring of distinctive brain activities. An array of datasets have been generated with the use of…

Pain remains one of the most pressing health challenges, yet its measurement still relies heavily on self-report, limiting monitoring in non-communicative patients and hindering translational research. Neural oscillations recorded with…

Neurons and Cognition · Quantitative Biology 2025-09-16 D. A. Blanco-Mora , A. Dierolf , J. Gonçalves , M. van Der Meulen

Accurate recognition of human emotional states is critical for effective human-machine interaction. Electroencephalography (EEG) offers a reliable source for emotion recognition due to its high temporal resolution and its direct reflection…

Machine Learning · Computer Science 2026-01-30 Maryam Mirzaei , Farzaneh Shayegh , Hamed Narimani

Emotions are crucial in human life, influencing perceptions, relationships, behaviour, and choices. Emotion recognition using Electroencephalography (EEG) in the Brain-Computer Interface (BCI) domain presents significant challenges,…

Human-Computer Interaction · Computer Science 2025-12-12 Gourav Siddhad , Masakazu Iwamura , Partha Pratim Roy

Raga is the central melodic concept in Hindustani Classical Music. It has a complex structure, often characterized by pathos. In this paper, we describe a technique for Automatic Raga Recognition, based on pitch distributions. We are able…

Sound · Computer Science 2017-08-09 Sanchit Alekh