Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
Eeg signal processing for medical diagnosis, healthcare, and monitoring: A comprehensive review
EEG is a common and safe test that uses small electrodes to record electrical signals from
the brain. It has a broad range of applications in medical diagnosis, including diagnosis of …
the brain. It has a broad range of applications in medical diagnosis, including diagnosis of …
A new framework for automatic detection of patients with mild cognitive impairment using resting-state EEG signals
Mild cognitive impairment (MCI) can be an indicator representing the early stage of
Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major …
Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major …
A comparative analysis of machine learning methods for emotion recognition using EEG and peripheral physiological signals
V Doma, M Pirouz - Journal of Big Data, 2020 - Springer
Emotion recognition using brain signals has the potential to change the way we identify and
treat some health conditions. Difficulties and limitations may arise in general emotion …
treat some health conditions. Difficulties and limitations may arise in general emotion …
A dataset for emotion recognition using virtual reality and EEG (DER-VREEG): Emotional state classification using low-cost wearable VR-EEG headsets
Emotions are viewed as an important aspect of human interactions and conversations, and
allow effective and logical decision making. Emotion recognition uses low-cost wearable …
allow effective and logical decision making. Emotion recognition uses low-cost wearable …
Automatic seizure detection by convolutional neural networks with computational complexity analysis
Abstract Background and Objectives Nowadays, an automated computer-aided diagnosis
(CAD) is an approach that plays an important role in the detection of health issues. The main …
(CAD) is an approach that plays an important role in the detection of health issues. The main …
Bearing remaining useful life prediction under starved lubricating condition using time domain acoustic emission signal processing
In this paper, the estimation of the remaining useful life (RUL) of angular contact ball bearing
using time-domain signal processing method is discussed. An experimental setup based on …
using time-domain signal processing method is discussed. An experimental setup based on …
Alzheimer's diseases diagnosis using fusion of high informative BiLSTM and CNN features of EEG signal
M Imani - Biomedical Signal Processing and Control, 2023 - Elsevier
Electroencephalography (EEG) signals are low cost and available data for diagnosis of
mental disorders such as Alzheimer's diseases (AD). Each EEG signal contains information …
mental disorders such as Alzheimer's diseases (AD). Each EEG signal contains information …
EEG-based optimization of eye state classification using modified-BER metaheuristic algorithm
This article introduces the Modified Al-Biruni Earth Radius (MBER) algorithm, which seeks to
improve the precision of categorizing eye states as either open (0) or closed (1). The …
improve the precision of categorizing eye states as either open (0) or closed (1). The …
Multiclass EEG motor-imagery classification with sub-band common spatial patterns
Electroencephalogram (EEG) signal classification plays an important role to facilitate
physically impaired patients by providing brain-computer interface (BCI)-controlled devices …
physically impaired patients by providing brain-computer interface (BCI)-controlled devices …