Automated epilepsy detection techniques from electroencephalogram signals: a review study

S Supriya, S Siuly, H Wang, Y Zhang - Health information science and …, 2020 - Springer
Epilepsy is a serious neurological condition which contemplates as top 5 reasons for
avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy …

Deep learning-based multi-head self-attention model for human epilepsy identification from EEG signal for biomedical traits

AK Dutta, M Raparthi, M Alsaadi, MW Bhatt… - Multimedia Tools and …, 2024 - Springer
The neurological condition epilepsy is demanding and even fatal. Electroencephalogram
(EEG)-based epilepsy detection still faces various difficulties. EEG readings fluctuate, and …

[HTML][HTML] COVID-19 detection using chest X-ray images based on a developed deep neural network

Z Mousavi, N Shahini, S Sheykhivand, S Mojtahedi… - SLAS technology, 2022 - Elsevier
Aim Currently, a new coronavirus called COVID-19 is the biggest challenge of the human at
21st century. Now, the spread of this virus is such that mortality has risen strongly in all cities …

Developing a deep neural network for driver fatigue detection using EEG signals based on compressed sensing

S Sheykhivand, TY Rezaii, S Meshgini, S Makoui… - Sustainability, 2022 - mdpi.com
In recent years, driver fatigue has become one of the main causes of road accidents. As a
result, fatigue detection systems have been developed to warn drivers, and, among the …

Automatic detection of driver fatigue based on EEG signals using a developed deep neural network

S Sheykhivand, TY Rezaii, Z Mousavi, S Meshgini… - Electronics, 2022 - mdpi.com
In recent years, detecting driver fatigue has been a significant practical necessity and issue.
Even though several investigations have been undertaken to examine driver fatigue, there …

Dictionary learning-based damage detection under varying environmental conditions using only vibration responses of numerical model and real intact State …

Z Mousavi, S Varahram, MM Ettefagh… - Mechanical Systems and …, 2023 - Elsevier
Monitoring structural damage is critical for preserving the service life of engineering systems.
In varying operational environments, the working loads are changing all the time and they …

Epileptic classification with deep-transfer-learning-based feature fusion algorithm

J Cao, D Hu, Y Wang, J Wang… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Epilepsy ictal detection based on scalp electroencephalograms (EEGs) has been
comprehensively studied in the past decades. But few attentions have been paid to the …

[HTML][HTML] Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images

S Sheykhivand, Z Mousavi, S Mojtahedi… - Alexandria Engineering …, 2021 - Elsevier
Abstract The novel coronavirus (COVID-19) could be described as the greatest human
challenge of the 21st century. The development and transmission of the disease have …

Automatic seizure detection and classification using super-resolution superlet transform and deep neural network-A preprocessing-less method

PM Tripathi, A Kumar, M Kumar… - Computer Methods and …, 2023 - Elsevier
Context Epilepsy, characterized by recurrent seizures, is a chronic brain disease that affects
approximately 50 million. Recurrent seizures characterize it. A seizure, a burst of …

A review of the classification of neuroscience problems with the help of Deep Learning Framework

D Pathak, R Kashyap - 2021 5th International Conference on …, 2021 - ieeexplore.ieee.org
Electroencephalographic signals (EEG signals) processing has become very popular
nowadays due to its effectiveness in dealing with and treating various disorders associated …