[HTML][HTML] A systematic review on emotion recognition system using physiological signals: data acquisition and methodology
Emotion recognition systems (ERS) have become a popular research field to contribute to
human-machine interaction in different areas. Different kinds of applications on ERS can …
human-machine interaction in different areas. Different kinds of applications on ERS can …
Multi-task EEG signal classification using correlation-based IMF selection and multi-class CSP
N Alizadeh, S Afrakhteh, MR Mosavi - IEEE Access, 2023 - ieeexplore.ieee.org
In the context of motor imagery (MI)-based brain-computer interface (BCI) systems, a great
amount of research has been studied for attaining higher classification performance by …
amount of research has been studied for attaining higher classification performance by …
On the use of pairwise distance learning for brain signal classification with limited observations
The increasing access to brain signal data using electroencephalography creates new
opportunities to study electrophysiological brain activity and perform ambulatory diagnoses …
opportunities to study electrophysiological brain activity and perform ambulatory diagnoses …
Detecting online child grooming conversation
FE Gunawan, L Ashianti, S Candra… - … and Creativity Support …, 2016 - ieeexplore.ieee.org
Massive proliferation of social media has opened possibilities for perpetrator to conduct the
crime of online child grooming. Because the pervasiveness of the problem scale, it may only …
crime of online child grooming. Because the pervasiveness of the problem scale, it may only …
Principal components analysis of eeg signals for epileptic patient identification
MC Guerrero, JS Parada, HE Espitia - Computation, 2021 - mdpi.com
According to the behavior of its neuronal connections, it is possible to determine if the brain
suffers from abnormalities such as epilepsy. This disease produces seizures and alters the …
suffers from abnormalities such as epilepsy. This disease produces seizures and alters the …
Performance analysis of EEG based emotion recognition using deep learning models
M Jehosheba Margaret… - Brain-Computer …, 2023 - Taylor & Francis
Emotion is an important factor that decides the the state of the mind of an individual.
However, there are many people who cannot express their emotions explicitly due to various …
However, there are many people who cannot express their emotions explicitly due to various …
[PDF][PDF] Novel solution to improve mental health by ntegrating music and IoT with neural feedback
BM Khrisna, VC Jhansi, PS Shama… - J of Computl Inform …, 2019 - researchgate.net
Health care is one of the services that is given for highest importance. With advances in
medicine and technology, physical health is well maintained. Whereas mental health is one …
medicine and technology, physical health is well maintained. Whereas mental health is one …
Mild Cognitive Impairment detection based on EEG and HRV data
A Boudaya, S Chaabene, B Bouaziz… - Digital Signal …, 2024 - Elsevier
Brain volume decrease is usually connected to neurodegeneration and aging. In this
environment, an important percentage of elderly persons suffer from mild cognitive …
environment, an important percentage of elderly persons suffer from mild cognitive …
Feature Extraction ElectroEncephaloGram (EEG) using wavelet transform for cursor movement
This study aims to extract features related to human brain signals associated with
ElectroEncephaloGraph (EEG) signal measurements and EEG signal classification …
ElectroEncephaloGraph (EEG) signal measurements and EEG signal classification …
Classification of epileptic seizure using machine learning and deep learning based on electroencephalography (EEG)
Epilepsy is a type of neurological brain disorder due to a temporary change in the brain's
electrical function. If diagnosed and treated, there can be no seizures …
electrical function. If diagnosed and treated, there can be no seizures …