Automatic eyeblink and muscular artifact detection and removal from EEG signals using k-nearest neighbor classifier and long short-term memory networks
Electroencephalogram (EEG) is often corrupted with artifacts originating from sources such
as eyes and muscles. Hybrid artifact removal methods often require human intervention for …
as eyes and muscles. Hybrid artifact removal methods often require human intervention for …
Non-Invasive Biosensing for Healthcare Using Artificial Intelligence: A Semi-Systematic Review
T Islam, P Washington - Biosensors, 2024 - mdpi.com
The rapid development of biosensing technologies together with the advent of deep learning
has marked an era in healthcare and biomedical research where widespread devices like …
has marked an era in healthcare and biomedical research where widespread devices like …
Automatic muscle artifacts identification and removal from single-channel eeg using wavelet transform with meta-heuristically optimized non-local means filter
Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts,
which may lead to wrong interpretation in the brain–computer interface (BCI) system as well …
which may lead to wrong interpretation in the brain–computer interface (BCI) system as well …
DSCNN-CAU: deep-learning-based mental activity classification for IoT implementation toward portable BCI
Mental activity classification (MAC) based on electroencephalogram (EEG) is used in the
brain–computer interface (BCI) and neurofeedback applications. For this purpose, machine …
brain–computer interface (BCI) and neurofeedback applications. For this purpose, machine …
BCI wheelchair control using expert system classifying EEG signals based on power spectrum estimation and nervous tics detection
D Pawuś, S Paszkiel - Applied Sciences, 2022 - mdpi.com
The constantly developing biomedical engineering field and newer and more advanced BCI
(brain–computer interface) systems require their designers to constantly develop and search …
(brain–computer interface) systems require their designers to constantly develop and search …
Investigating the relationship between noise exposure and human cognitive performance: attention, stress, and mental workload based on EEG signals using power …
A pervasive environmental stressor is one that damages mental and physical health as well
as cognitive abilities by producing noise at a specific frequency and level. Current noise …
as cognitive abilities by producing noise at a specific frequency and level. Current noise …
The effect of stress on a personal identification system based on electroencephalographic signals
EA Abdel-Ghaffar, M Salama - Sensors, 2024 - mdpi.com
Personal identification systems based on electroencephalographic (EEG) signals have their
own strengths and limitations. The stability of EEG signals strongly affects such systems. The …
own strengths and limitations. The stability of EEG signals strongly affects such systems. The …
Greening and safety: the influence of road greenness on driver's attention and emergency reaction time
Road traffic accidents are among the top 10 causes of death globally. With regard to
potential accidents, if driver reaction time (RT) can be reduced, drivers would have more …
potential accidents, if driver reaction time (RT) can be reduced, drivers would have more …
AnEEG: leveraging deep learning for effective artifact removal in EEG data
In neuroscience and clinical diagnostics, electroencephalography (EEG) is a crucial
instrument for capturing neural activity. However, this signal is polluted by different artifacts …
instrument for capturing neural activity. However, this signal is polluted by different artifacts …
[HTML][HTML] EEG stress classification based on Doppler spectral features for ensemble 1D-CNN with LCL activation function
J Naren, AR Babu - Journal of King Saud University-Computer and …, 2024 - Elsevier
The paper proposes an induced stress classification algorithm that uses features from the
Doppler spectrum. In this approach, a reference signal source is used to obtain the …
Doppler spectrum. In this approach, a reference signal source is used to obtain the …