Emotion recognition in EEG signals using deep learning methods: A review

M Jafari, A Shoeibi, M Khodatars… - Computers in Biology …, 2023‏ - Elsevier
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …

Application of artificial intelligence in wearable devices: Opportunities and challenges

D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022‏ - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …

Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Information …, 2023‏ - Elsevier
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …

[HTML][HTML] Epileptic seizures detection using deep learning techniques: a review

A Shoeibi, M Khodatars, N Ghassemi, M Jafari… - International journal of …, 2021‏ - mdpi.com
A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …

Artificial intelligence enabled personalised assistive tools to enhance education of children with neurodevelopmental disorders—a review

PD Barua, J Vicnesh, R Gururajan, SL Oh… - International Journal of …, 2022‏ - mdpi.com
Mental disorders (MDs) with onset in childhood or adolescence include
neurodevelopmental disorders (NDDs)(intellectual disability and specific learning …

Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review

A Shoeibi, M Khodatars, M Jafari, P Moridian… - Computers in Biology …, 2021‏ - Elsevier
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …

D Sadeghi, A Shoeibi, N Ghassemi, P Moridian… - Computers in Biology …, 2022‏ - Elsevier
Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …

Automatic diagnosis of schizophrenia in EEG signals using CNN-LSTM models

A Shoeibi, D Sadeghi, P Moridian… - Frontiers in …, 2021‏ - frontiersin.org
Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals
in the brain, the function of some brain regions is out of balance, leading to the lack of …

Autism spectrum disorder detection framework for children based on federated learning integrated CNN-LSTM

A Lakhan, MA Mohammed, KH Abdulkareem… - Computers in Biology …, 2023‏ - Elsevier
Abstract The incidence of Autism Spectrum Disorder (ASD) among children, attributed to
genetics and environmental factors, has been increasing daily. ASD is a non-curable …

Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies

A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022‏ - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …