A review of the role of machine learning techniques towards brain–computer interface applications
S Rasheed - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
This review article provides a deep insight into the Brain–Computer Interface (BCI) and the
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …
Security in brain-computer interfaces: state-of-the-art, opportunities, and future challenges
Brain-Computer Interfaces (BCIs) have significantly improved the patients' quality of life by
restoring damaged hearing, sight, and movement capabilities. After evolving their …
restoring damaged hearing, sight, and movement capabilities. After evolving their …
An automated brain tumor classification in MR images using an enhanced convolutional neural network
R Singh, BB Agarwal - International Journal of Information Technology, 2023 - Springer
MRI is a non-invasive imaging tool, accurate classification of brain tumours from MRI images
is a highly specialized area of a medical study. Classification of brain tumours is a method …
is a highly specialized area of a medical study. Classification of brain tumours is a method …
Digital transformation of cyber crime for chip-enabled hacking
The heterogeneous digital arena emerged as the open depiction for malicious activities, and
cyber criminals and terrorists are targeting the cyber depiction for controlling its operation. In …
cyber criminals and terrorists are targeting the cyber depiction for controlling its operation. In …
A novel EEG-based major depressive disorder detection framework with two-stage feature selection
Background Major depressive disorder (MDD) is a common mental illness, characterized by
persistent depression, sadness, despair, etc., troubling people's daily life and work seriously …
persistent depression, sadness, despair, etc., troubling people's daily life and work seriously …
EEG-based brain-computer interface methods with the aim of rehabilitating advanced stage ALS patients
A Pirasteh, M Shamseini Ghiyasvand… - Disability and …, 2024 - Taylor & Francis
Abstract Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that leads to
progressive muscle weakness and paralysis, ultimately resulting in the loss of ability to …
progressive muscle weakness and paralysis, ultimately resulting in the loss of ability to …
CluSem: Accurate clustering-based ensemble method to predict motor imagery tasks from multi-channel EEG data
Background The classification of motor imagery electroencephalogram (MI-EEG) is a pivotal
task in the biosignal classification process in the brain-computer i nterface (BCI) …
task in the biosignal classification process in the brain-computer i nterface (BCI) …
A novel two‐band equilateral wavelet filter bank method for an automated detection of seizure from EEG signals
SR Ashokkumar, G MohanBabu… - International Journal of …, 2020 - Wiley Online Library
One can determinate the occurrence of epileptic seizure from the electroencephalogram
(EEG) signal. Nonautomatic epilepsy detection is onerous and may be prone to error. They …
(EEG) signal. Nonautomatic epilepsy detection is onerous and may be prone to error. They …
Automated detection of seizure and nonseizure EEG signals using two band biorthogonal wavelet filter banks
The automated feature identification and classification of nonseizure and seizure
electroencephalogram (EEG) is very useful for the diagnosis of epilepsy. In this chapter two …
electroencephalogram (EEG) is very useful for the diagnosis of epilepsy. In this chapter two …
[PDF][PDF] Cybersecurity in brain-computer interfaces: State-of-the-art, opportunities, and future challenges
Brain-Computer Interfaces (BCIs) have significantly improved the patients' quality of life by
restoring damaged hearing, sight and movement capabilities. After evolving their application …
restoring damaged hearing, sight and movement capabilities. After evolving their application …