Optimal channels and features selection based ADHD detection from EEG signal using statistical and machine learning techniques
Attention deficit hyperactivity disorder (ADHD) is one of the major psychiatric and
neurodevelopment disorders worldwide. Electroencephalography (EEG) signal-based …
neurodevelopment disorders worldwide. Electroencephalography (EEG) signal-based …
[PDF][PDF] Efficient Feature Selection and Machine Learning Based ADHD Detection Using EEG Signal.
Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric and
neurobehavioral disorders in children, affecting 11% of children worldwide. This study …
neurobehavioral disorders in children, affecting 11% of children worldwide. This study …
Prediction of Attention Deficit Hyperactivity Disorder (ADHD) using machine learning Techniques based on classification of EEG signal
The paper shows a comprehensive study of prediction of Attention Deficit Hyperactivity
Disorder (ADHD) using machine learning in adults and children's and symptoms' of ADHD …
Disorder (ADHD) using machine learning in adults and children's and symptoms' of ADHD …
Design of a Collaborative Knowledge Framework for Personalised Attention Deficit Hyperactivity Disorder (ADHD) Treatments
P Chatpreecha, S Usanavasin - Children, 2023 - mdpi.com
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder. From the
data collected by the Ministry of Public Health, Thailand, it has been reported that more than …
data collected by the Ministry of Public Health, Thailand, it has been reported that more than …
A review on efficient EEG pattern recognition using machine learning and deep learning methods and its application
A Antony, A Bhattacharjee, S Thakur… - AIP Conference …, 2022 - pubs.aip.org
With the good development of robotic technology, good communication of robots regarded
as the most sought after achievement by researchers these days. If the robot can identify the …
as the most sought after achievement by researchers these days. If the robot can identify the …
ADHD-AID: Aiding Tool for Detecting Children's Attention Deficit Hyperactivity Disorder via EEG-Based Multi-Resolution Analysis and Feature Selection
O Attallah - Biomimetics, 2024 - mdpi.com
The severe effects of attention deficit hyperactivity disorder (ADHD) among adolescents can
be prevented by timely identification and prompt therapeutic intervention. Traditional …
be prevented by timely identification and prompt therapeutic intervention. Traditional …
A novel approach to identify the brain regions that best classify ADHD by means of EEG and deep learning
J Sanchis, S García-Ponsoda, MA Teruel, J Trujillo… - Heliyon, 2024 - cell.com
Abstract Objective Attention-Deficit Hyperactivity Disorder (ADHD) is one of the most
widespread neurodevelopmental disorders diagnosed in childhood. ADHD is diagnosed by …
widespread neurodevelopmental disorders diagnosed in childhood. ADHD is diagnosed by …
Early detection of ADHD and Dyslexia from EEG Signals
N Gupte, M Patel, T Pen… - 2023 IEEE 8th …, 2023 - ieeexplore.ieee.org
A learning impairment is a dysfunction in one or more fundamental psychological functions
that might show up as a lack of proficiency in some areas of learning, such reading, writing …
that might show up as a lack of proficiency in some areas of learning, such reading, writing …
Gabor filter-based statistical features for ADHD detection
Attention deficit/hyperactivity disorder (ADHD) is a neuropsychological disorder that occurs
in children and is characterized by inattention, impulsivity, and hyperactivity. Early and …
in children and is characterized by inattention, impulsivity, and hyperactivity. Early and …
Developing System-Based Artificial Intelligence Models for Detecting the Attention Deficit Hyperactivity Disorder
This study presents a novel methodology for automating the classification of pediatric ADHD
using electroencephalogram (EEG) biomarkers through machine learning and deep …
using electroencephalogram (EEG) biomarkers through machine learning and deep …