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Electroencephalography signal processing: A comprehensive review and analysis of methods and techniques
The electroencephalography (EEG) signal is a noninvasive and complex signal that has
numerous applications in biomedical fields, including sleep and the brain–computer …
numerous applications in biomedical fields, including sleep and the brain–computer …
Review of studies on emotion recognition and judgment based on physiological signals
W Lin, C Li - Applied Sciences, 2023 - mdpi.com
People's emotions play an important part in our daily life and can not only reflect
psychological and physical states, but also play a vital role in people's communication …
psychological and physical states, but also play a vital role in people's communication …
Automatic and early detection of Parkinson's disease by analyzing acoustic signals using classification algorithms based on recursive feature elimination method
Parkinson's disease (PD) is a neurodegenerative condition generated by the dysfunction of
brain cells and their 60–80% inability to produce dopamine, an organic chemical …
brain cells and their 60–80% inability to produce dopamine, an organic chemical …
Emotion recognition using spatial-temporal EEG features through convolutional graph attention network
Objective. Constructing an efficient human emotion recognition model based on
electroencephalogram (EEG) signals is significant for realizing emotional brain–computer …
electroencephalogram (EEG) signals is significant for realizing emotional brain–computer …
Adaptive neural decision tree for EEG based emotion recognition
Y Zheng, J Ding, F Liu, D Wang - Information Sciences, 2023 - Elsevier
An adaptive neural decision tree is investigated to recognize electroencephalogram (EEG)
emotion signal with ability of intelligently selecting network structure. Firstly, to overcome …
emotion signal with ability of intelligently selecting network structure. Firstly, to overcome …
Role of machine learning and deep learning techniques in EEG-based BCI emotion recognition system: a review
Emotion is a subjective psychophysiological reaction coming from external stimuli which
impacts every aspect of our daily lives. Due to the continuing development of non-invasive …
impacts every aspect of our daily lives. Due to the continuing development of non-invasive …
EEG-based cross-subject emotion recognition using multi-source domain transfer learning
J Quan, Y Li, L Wang, R He, S Yang, L Guo - Biomedical Signal Processing …, 2023 - Elsevier
Emotion recognition based on electroencephalogram (EEG) has received extensive
attention due to its advantages of being objective and not being controlled by subjective …
attention due to its advantages of being objective and not being controlled by subjective …
Deep time-frequency features and semi-supervised dimension reduction for subject-independent emotion recognition from multi-channel EEG signals
In recent years, human emotion recognition has received great attention since it plays an
essential role in human-computer interactions. Traditional methods focused on …
essential role in human-computer interactions. Traditional methods focused on …
Fourier-Bessel representation for signal processing: A review
Several applications, analysis and visualization of signal demand representation of time-
domain signal in different domains like frequency-domain representation based on Fourier …
domain signal in different domains like frequency-domain representation based on Fourier …
EEG based classification of children with learning disabilities using shallow and deep neural network
Learning disability (LD), a neurodevelopmental disorder that has severely impacted the lives
of many children all over the world. LD refers to significant deficiency in children's reading …
of many children all over the world. LD refers to significant deficiency in children's reading …