[HTML][HTML] Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade

SK Khare, S March, PD Barua, VM Gadre, UR Acharya - Information Fusion, 2023 - Elsevier
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 …

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 …

Automated detection of ADHD: Current trends and future perspective

HW Loh, CP Ooi, PD Barua, EE Palmer… - Computers in Biology …, 2022 - Elsevier
Attention deficit hyperactivity disorder (ADHD) is a heterogenous disorder that has a
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 …

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 …

Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations

ZJ Lau, T Pham, SHA Chen… - European Journal of …, 2022 - Wiley Online Library
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 …

[HTML][HTML] Deep neural network technique for automated detection of ADHD and CD using ECG signal

HW Loh, CP Ooi, SL Oh, PD Barua, YR Tan… - Computer methods and …, 2023 - Elsevier
Abstract Background and objective Attention Deficit Hyperactivity problem (ADHD) is a
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

JEW Koh, CP Ooi, NSJ Lim-Ashworth, J Vicnesh… - Computers in biology …, 2022 - Elsevier
Background The most prevalent neuropsychiatric disorder among children is attention deficit
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

M Cao, E Martin, X Li - Translational Psychiatry, 2023 - nature.com
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous
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

MO Ribas, M Micai, A Caruso, F Fulceri, M Fazio… - Neuroscience & …, 2023 - Elsevier
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 …