Survey on brain-computer interface: An emerging computational intelligence paradigm
A brain-computer interface (BCI) provides a way to develop interaction between a brain and
a computer. The communication is developed as a result of neural responses generated in …
a computer. The communication is developed as a result of neural responses generated in …
Brain computer interface: A comprehensive survey
The contemporary era demands a progress with respect to manual work or even semi-
machine dependence and the desired procession can be provided by Brain Computer …
machine dependence and the desired procession can be provided by Brain Computer …
Early detection of Alzheimer's disease from EEG signals using Hjorth parameters
Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the
brain that ultimately results in the death of neurons and dementia. The prevalence of the …
brain that ultimately results in the death of neurons and dementia. The prevalence of the …
Mind your mind: EEG-based brain-computer interfaces and their security in cyber space
A brain-computer interface (BCI) system is a system that leverages brainwave information
acquired by a designated brain monitoring device to interact with a computerized system …
acquired by a designated brain monitoring device to interact with a computerized system …
EEG data classification for mental state analysis using wavelet packet transform and Gaussian process classifier
R Desai, P Porob, P Rebelo, DR Edla… - Wireless Personal …, 2020 - Springer
Stress is one of the most common problems that is faced by a majority of the students. Long-
term stress can lead to serious health problems, for example, depression, heart disease …
term stress can lead to serious health problems, for example, depression, heart disease …
Analysis of weight-directed functional brain networks in the deception state based on EEG signal
S Wei, J Gao, Y Yang, N Xiong, J Zhang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Although analyzing the brain's functional and structural network has revealed that numerous
brain networks are necessary to collaborate during deception, the directionality of these …
brain networks are necessary to collaborate during deception, the directionality of these …
Classification of brain mr images using modified version of simplified pulse-coupled neural network and linear programming twin support vector machines
R Shanker, M Bhattacharya - The Journal of Supercomputing, 2022 - Springer
The automated and accurate detection of brain tumors is challenging for classifying brain
Magnetic Resonance (MR) images. The conventional techniques for diagnosing the images …
Magnetic Resonance (MR) images. The conventional techniques for diagnosing the images …
EEG-based deception detection using weighted dual perspective visibility graph analysis
Deception detection is a critical aspect across various domains. Integrating advanced signal
processing techniques, particularly in neuroscientific studies, has opened new avenues for …
processing techniques, particularly in neuroscientific studies, has opened new avenues for …
A systematic literature review on machine learning algorithms for human status detection
Human status detection (HSD) is important to understand the status of users when
interacting with various systems under different conditions. Recently, although various …
interacting with various systems under different conditions. Recently, although various …
RETRACTED ARTICLE: A novel multi-layer multi-spiking neural network for EEG signal classification using Mini Batch SGD
A novel multi-layer multi-spiking neural network (MMSNN) model sends information from
one neuron to the next through multiple synapses in different spikes. When a suitable …
one neuron to the next through multiple synapses in different spikes. When a suitable …