Database for an emotion recognition system based on EEG signals and various computer games–GAMEEMO
In this study, electroencephalography-based data for emotion recognition analysis are
introduced. EEG signals were collected from 28 different subjects with a wearable and …
introduced. EEG signals were collected from 28 different subjects with a wearable and …
Deep fusion feature learning network for MI-EEG classification
J Yang, S Yao, J Wang - Ieee Access, 2018 - ieeexplore.ieee.org
Brain–computer interfaces (BCIs) are used to provide a direct communication between the
human brain and the external devices, such as wheelchairs and intelligent apparatus, by …
human brain and the external devices, such as wheelchairs and intelligent apparatus, by …
Vibration‐Based Fault Diagnosis of Commutator Motor
A Glowacz, W Glowacz - Shock and Vibration, 2018 - Wiley Online Library
This paper presents a study on vibration‐based fault diagnosis techniques of a commutator
motor (CM). Proposed techniques used vibration signals and signal processing methods …
motor (CM). Proposed techniques used vibration signals and signal processing methods …
A novel approach for emotion recognition based on EEG signal using deep learning
Emotion can be defined as a voluntary or involuntary reaction to external factors. People
express their emotions through actions, such as words, sounds, facial expressions, and …
express their emotions through actions, such as words, sounds, facial expressions, and …
Emotion recognition with deep learning using GAMEEMO data set
Emotion recognition is actively used in brain–computer interface, health care, security, e‐
commerce, education and entertainment applications to increase and control human …
commerce, education and entertainment applications to increase and control human …
A study on dynamic model of steady-state visual evoked potentials
Objective. Significant progress has been made in the past two decades to considerably
improve the performance of steady-state visual evoked potential (SSVEP)-based brain …
improve the performance of steady-state visual evoked potential (SSVEP)-based brain …
Early and remote detection of possible heartbeat problems with convolutional neural networks and multipart interactive training
K Wołk, A Wołk - IEEE Access, 2019 - ieeexplore.ieee.org
In this study, the convolutional neural network (CNN) and multipart interactive training were
used to create a state-of-the-art classifier for the early detection of cardiac pathologies. The …
used to create a state-of-the-art classifier for the early detection of cardiac pathologies. The …
Novel SSVEP processing method based on correlation and feedforward neural network for embedded brain computer interface
Abstract Steady State Visually Evoked Potential (SSVEP) is a successful strategy in
electroencephalographic (EEG) processing applied to spellers, games, rehabilitation …
electroencephalographic (EEG) processing applied to spellers, games, rehabilitation …
Brain map** of low and high implusivity based P300 signals
A Turnip, EK Dwi, T Hidayat… - Journal of Physics …, 2018 - iopscience.iop.org
Impulsiveness is defined as action without good planning and with little consideration the
consequences. Impulsive actions are typically poorly conceived, prematurely expressed, or …
consequences. Impulsive actions are typically poorly conceived, prematurely expressed, or …
[HTML][HTML] Emotion recognition positively correlates with steady-state visual evoked potential amplitude and alpha entrainment
C Deng, J Tong, X Deng, Z Zhang, Y Qin - Neuroscience, 2020 - Elsevier
Emotion recognition reflects the psychological and physiological status of humans.
Numerous studies have investigated the neural mechanisms of emotion recognition based …
Numerous studies have investigated the neural mechanisms of emotion recognition based …