EEG-based epileptic seizure detection using binary dragonfly algorithm and deep neural network

G Yogarajan, N Alsubaie, G Rajasekaran, T Revathi… - Scientific Reports, 2023 - nature.com
Electroencephalogram (EEG) is one of the most common methods used for seizure
detection as it records the electrical activity of the brain. Symmetry and asymmetry of EEG …

Uninterrupted real‐time cerebral stress level monitoring using wearable biosensors: A review

A Mishra, M Agrawal, A Ali… - Biotechnology and Applied …, 2023 - Wiley Online Library
Stress is the major unseen bug for the health of humans with the increasing workaholic era.
Long periods of avoidance are the main precursor for chronic disorders that are quite tough …

A Multi Representation Deep Learning Approach for Epileptic Seizure Detection

AT Hermawan, IAE Zaeni, AP Wibawa… - Journal of Robotics …, 2024 - journal.umy.ac.id
Epileptic seizures, unpredictable in nature and potentially dangerous during activities like
driving, pose significant risks to individual and public safety. Traditional diagnostic methods …

Multi-center assessment of CNN-transformer with belief matching loss for patient-independent seizure detection in scalp and intracranial EEG

WY Peh, P Thangavel, Y Yao, J Thomas, YL Tan… - 2022 - researchsquare.com
Neurologists typically identify epileptic seizures from electroencephalograms (EEGs) by
visual inspection. This process is often time-consuming, especially for EEG recordings that …

[HTML][HTML] Time-series generative adversarial network approach of deep learning improves seizure detection from the human thalamic SEEG

B Ganti, G Chaitanya, RS Balamurugan… - Frontiers in …, 2022 - frontiersin.org
Seizure detection algorithms are often optimized to detect seizures from the epileptogenic
cortex. However, in non-localizable epilepsies, the thalamus is frequently targeted for …

Automated human mind reading using EEG signals for seizure detection

V Ranga, S Gupta, J Meena… - Journal of medical …, 2020 - Taylor & Francis
Epilepsy is one of the most occurring neurological disease globally emerged back in 4000
BC. It is affecting around 50 million people of all ages these days. The trait of this disease is …

A Recent AppraisalOver EEG Signals Measurement Actions and Its Challenges

P Kumar, VK Sharma, A Rathi - 2022 8th International …, 2022 - ieeexplore.ieee.org
Electroencephalogram (EEG) is widely exploited practice to measure the level of electrical
motion rising from brain of humans. With modest procedure this mechanism globally exploits …

Memória em processos cognitivos: percepção e organização da estrutura musical no repertório do século XXI

RT Silva - 2024 - repositorio.unesp.br
Durante o ato de escuta de uma música, os processos cognitivos ligados à memória são
estimulados de diversas maneiras, com o ouvinte podendo atribuir significados e contextos …

[图书][B] Deep learning for electrophysiological investigation and estimation of anesthetic-induced unconsciousness

K Patlatzoglou - 2022 - search.proquest.com
Neuroscience has made a number of advances in the search for the neural correlates of
consciousness, but our understanding of the neurophysiological markers remains …

Aplicación de técnicas de aprendizaje de máquina para facilitar la comunicación en pacientes con neuropatía periférica utilizando señales eeg y visión …

EE Gallardo Ortiz - 2022 - bibdigital.epn.edu.ec
Gracias a mis padres por la confianza depositada a lo largo de este camino, en el cual crecí
y aprendí, y me dieron la fuerza para superarme, a mis hermanos por siempre estar para mí …