[HTML][HTML] SAE+ LSTM: A new framework for emotion recognition from multi-channel EEG
EEG-based automatic emotion recognition can help brain-inspired robots in improving their
interactions with humans. This paper presents a novel framework for emotion recognition …
interactions with humans. This paper presents a novel framework for emotion recognition …
[HTML][HTML] Hybrid EEG–fNIRS-based eight-command decoding for BCI: application to quadcopter control
In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–
fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain …
fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain …
Bagging ensemble-based novel data generation method for univariate time series forecasting
The most critical issue in time series data is predicting future data values. Recently, an
ensemble model combining multiple models with superior predictive performance has …
ensemble model combining multiple models with superior predictive performance has …
Learning DenseNet features from EEG based spectrograms for subject independent emotion recognition
Subject-independent emotion recognition (SIER) using electroencephalogram (EEG)
signals has always been a challenge among the biomedical research community. One of the …
signals has always been a challenge among the biomedical research community. One of the …
Performance evaluation of multi-channel electroencephalogram signal (EEG) based time frequency analysis for human emotion recognition
KP Wagh, K Vasanth - Biomedical Signal Processing and Control, 2022 - Elsevier
The automated detection of a human's emotional state by acquiring physiological or non-
physiological cues is referred to as Emotion Recognition. The EEG-based approach is an …
physiological cues is referred to as Emotion Recognition. The EEG-based approach is an …
Probing brain dynamics correlates of motor expertise with mobile recordings.
Mobile electroencephalography and magnetoencephalography technology have the
potential to revolutionize the study of motor expertise by providing real-time brain activity …
potential to revolutionize the study of motor expertise by providing real-time brain activity …
Similarity constraint style transfer mapping for emotion recognition
L Chen, Q She, M Meng, Q Zhang, J Zhang - Biomedical Signal Processing …, 2023 - Elsevier
Transfer learning plays a vital role in emotion recognition based on electroencephalogram
(EEG). In practical application, only little labeled data from the target subject can be …
(EEG). In practical application, only little labeled data from the target subject can be …
Spatio-temporal analysis of EEG signal during consciousness using convolutional neural network
Electroencephalogram (EEG) measurement could help to distinguish the level of
consciousness in an individual without requiring a behavioral response, which could be …
consciousness in an individual without requiring a behavioral response, which could be …
Ensemble algorithms for EEG based emotion recognition
Emotion recognition using Electroencephalogram (EEG) signal has grabbed the attention of
researchers recently due to its widespread applications. This study employed empirical …
researchers recently due to its widespread applications. This study employed empirical …
Electroencephalogram-Based Emotion Recognition Using Random Forest
In recent years, emotion recognition based on electroencephalogram (EEG) has gained
prominence due to its wide applications in the area of healthcare, affective computing, brain …
prominence due to its wide applications in the area of healthcare, affective computing, brain …