Automatic sleep staging of EEG signals: recent development, challenges, and future directions
H Phan, K Mikkelsen - Physiological Measurement, 2022 - iopscience.iop.org
Modern deep learning holds a great potential to transform clinical studies of human sleep.
Teaching a machine to carry out routine tasks would be a tremendous reduction in workload …
Teaching a machine to carry out routine tasks would be a tremendous reduction in workload …
A survey on brain biometrics
Brainwaves, which reflect brain electrical activity and have been studied for a long time in
the domain of cognitive neuroscience, have recently been proposed as a promising …
the domain of cognitive neuroscience, have recently been proposed as a promising …
Affective EEG-based person identification using the deep learning approach
T Wilaiprasitporn, A Ditthapron… - … on Cognitive and …, 2019 - ieeexplore.ieee.org
Electroencephalography (EEG) is another method for performing person identification (PI).
Due to the nature of the EEG signals, EEG-based PI is typically done while a person is …
Due to the nature of the EEG signals, EEG-based PI is typically done while a person is …
EEG-based user identification system using 1D-convolutional long short-term memory neural networks
Electroencephalographic (EEG) signals have been widely used in medical applications, yet
the use of EEG signals as user identification systems for healthcare and Internet of Things …
the use of EEG signals as user identification systems for healthcare and Internet of Things …
Brain waves for automatic biometric-based user recognition
P Campisi, D La Rocca - IEEE transactions on information …, 2014 - ieeexplore.ieee.org
Brain signals have been investigated within the medical field for more than a century to
study brain diseases like epilepsy, spinal cord injuries, Alzheimer's, Parkinson's …
study brain diseases like epilepsy, spinal cord injuries, Alzheimer's, Parkinson's …
Human brain distinctiveness based on EEG spectral coherence connectivity
D La Rocca, P Campisi, B Vegso… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
The use of EEG biometrics, for the purpose of automatic people recognition, has received
increasing attention in the recent years. Most of the current analyses rely on the extraction of …
increasing attention in the recent years. Most of the current analyses rely on the extraction of …
Brainprint: Assessing the uniqueness, collectability, and permanence of a novel method for ERP biometrics
The human brain continually generates electrical potentials representing neural
communication. These potentials can be measured at the scalp, and constitute the …
communication. These potentials can be measured at the scalp, and constitute the …
CEREBRE: A novel method for very high accuracy event-related potential biometric identification
The vast majority of existing work on brain biometrics has been conducted on the ongoing
electroencephalogram. Here, we argue that the averaged event-related potential (ERP) may …
electroencephalogram. Here, we argue that the averaged event-related potential (ERP) may …
Convolutional neural networks using dynamic functional connectivity for EEG-based person identification in diverse human states
Highly secure access control requires Swiss-cheese-type multi-layer security protocols. The
use of electroencephalogram (EEG) to provide cognitive indicators for human workload and …
use of electroencephalogram (EEG) to provide cognitive indicators for human workload and …
A high-security EEG-based login system with RSVP stimuli and dry electrodes
Lately, electroencephalography (EEG)-based auth-entication has received considerable
attention from the scientific community. However, the limited usability of wet EEG electrodes …
attention from the scientific community. However, the limited usability of wet EEG electrodes …