[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 …
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 …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
Automated detection of ADHD: Current trends and future perspective
Attention deficit hyperactivity disorder (ADHD) is a heterogenous disorder that has a
detrimental impact on the neurodevelopment of the brain. ADHD patients exhibit …
detrimental impact on the neurodevelopment of the brain. ADHD patients exhibit …
[HTML][HTML] An explainable and interpretable model for attention deficit hyperactivity disorder in children using EEG signals
SK Khare, UR Acharya - Computers in biology and medicine, 2023 - Elsevier
Background: Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental
disorder that affects a person's sleep, mood, anxiety, and learning. Early diagnosis and …
disorder that affects a person's sleep, mood, anxiety, and learning. Early diagnosis and …
Artificial intelligence enabled personalised assistive tools to enhance education of children with neurodevelopmental disorders—a review
Mental disorders (MDs) with onset in childhood or adolescence include
neurodevelopmental disorders (NDDs)(intellectual disability and specific learning …
neurodevelopmental disorders (NDDs)(intellectual disability and specific learning …
Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations
There has been an increasing trend towards the use of complexity analysis in quantifying
neural activity measured by electroencephalography (EEG) signals. On top of revealing …
neural activity measured by electroencephalography (EEG) signals. On top of revealing …
[HTML][HTML] Deep neural network technique for automated detection of ADHD and CD using ECG signal
Abstract Background and objective Attention Deficit Hyperactivity problem (ADHD) is a
common neurodevelopment problem in children and adolescents that can lead to long-term …
common neurodevelopment problem in children and adolescents that can lead to long-term …
Automated classification of attention deficit hyperactivity disorder and conduct disorder using entropy features with ECG signals
Background The most prevalent neuropsychiatric disorder among children is attention deficit
hyperactivity disorder (ADHD). ADHD presents with a high prevalence of comorbid disorders …
hyperactivity disorder (ADHD). ADHD presents with a high prevalence of comorbid disorders …
Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous
neurodevelopmental disorder in children and has a high chance of persisting in adulthood …
neurodevelopmental disorder in children and has a high chance of persisting in adulthood …
[HTML][HTML] Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review
In recent years, there has been a great interest in utilizing technology in mental health
research. The rapid technological development has encouraged researchers to apply …
research. The rapid technological development has encouraged researchers to apply …