[HTML][HTML] Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
Mental health is a basic need for a sustainable and developing society. The prevalence and
financial burden of mental illness have increased globally, and especially in response to …
financial burden of mental illness have increased globally, and especially in response to …
A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent
impairments in social interaction, speech and nonverbal communication, and restricted or …
impairments in social interaction, speech and nonverbal communication, and restricted or …
EEG signal analysis for diagnosing neurological disorders using discrete wavelet transform and intelligent techniques
Analysis of electroencephalogram (EEG) signals is essential because it is an efficient
method to diagnose neurological brain disorders. In this work, a single system is developed …
method to diagnose neurological brain disorders. In this work, a single system is developed …
EEG‐based computer aided diagnosis of autism spectrum disorder using wavelet, entropy, and ANN
Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core
impairments in the social relationships, communication, imagination, or flexibility of thought …
impairments in the social relationships, communication, imagination, or flexibility of thought …
A robust method for early diagnosis of autism spectrum disorder from EEG signals based on feature selection and DBSCAN method
D Abdolzadegan, MH Moattar, M Ghoshuni - … and Biomedical Engineering, 2020 - Elsevier
Electroencephalogram (EEG) is one of the most important signals for diagnosis of Autism
Spectrum Disorder (ASD). There are different challenges such as feature selection and the …
Spectrum Disorder (ASD). There are different challenges such as feature selection and the …
Diagnosis of autism spectrum disorder from EEG using a time–frequency spectrogram image‐based approach
Autism is a type of neurodevelopment disorder in which individuals often have difficulties in
social relationship, communication, expressing and controlling emotions and poor eye …
social relationship, communication, expressing and controlling emotions and poor eye …
Brain functional network topology in autism spectrum disorder: a novel weighted hierarchical complexity metric for electroencephalogram
Recent complex network analysis reflected the brain network as a modular network with
small-world architecture in Autism Spectrum Disorder (ASD). Network hierarchy, which can …
small-world architecture in Autism Spectrum Disorder (ASD). Network hierarchy, which can …
Common spatial pattern technique with EEG signals for diagnosis of autism and epilepsy disorders
Electroencephalogram (EEG) signals reflect the activities or electrical disturbances in
neurons in the human brain. Therefore, these signals are vital for diagnosing certain brain …
neurons in the human brain. Therefore, these signals are vital for diagnosing certain brain …
A dynamic filtering DF-RNN deep-learning-based approach for EEG-based neurological disorders diagnosis
G Bouallegue, R Djemal, SA Alshebeili… - IEEE …, 2020 - ieeexplore.ieee.org
Filtering of unwanted signals has a great impact on the performance of EEG signal
processing applied to neurological disorders diagnosis. It is so difficult to remove …
processing applied to neurological disorders diagnosis. It is so difficult to remove …
Automated identification for autism severity level: EEG analysis using empirical mode decomposition and second order difference plot
Background Previous automated EEG-based diagnosis of autism spectrum disorders (ASD)
using various nonlinear EEG analysis methods were limited to distinguish only children with …
using various nonlinear EEG analysis methods were limited to distinguish only children with …