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  • Open Access


    An Exploratory Investigation of Difficulties in Applying Functional Behavior Assessment and Implementing Behavioral Intervention Plans in ADHD Programs in Saudi Arabia

    Abdulrahman Abdullah Abaoud*

    International Journal of Mental Health Promotion, Vol.24, No.4, pp. 595-601, 2022, DOI:10.32604/ijmhp.2022.021286

    Abstract Functional behavior assessment (FBA) and behavioral intervention plans (BIPs) can be effective for students with attention deficit hyperactivity disorder (ADHD); however, teachers may face difficulties when implementing FBA procedures and, in turn, BIPs because of lack of time, insufficient training, and multiplicity of beliefs. Thus, it is important to identify the difficulties teachers may face and the obstacles that can deter them from implementing intervention plans. This is a worthwhile endeavor because nearly all classrooms will have students with behavioral problems who will benefit from specifically designed educational interventions. This study aimed to identify the… More >

  • Open Access


    Efficient Feature Selection and Machine Learning Based ADHD Detection Using EEG Signal

    Md. Maniruzzaman1, Jungpil Shin1,*, Md. Al Mehedi Hasan1, Akira Yasumura2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5179-5195, 2022, DOI:10.32604/cmc.2022.028339

    Abstract Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric and neurobehavioral disorders in children, affecting 11% of children worldwide. This study aimed to propose a machine learning (ML)-based algorithm for discriminating ADHD from healthy children using their electroencephalography (EEG) signals. The study included 61 children with ADHD and 60 healthy children aged 7–12 years. Different morphological and time-domain features were extracted from EEG signals. The t-test (p-value < 0.05) and least absolute shrinkage and selection operator (LASSO) were used to select potential features of children with ADHD and enhance the classification accuracy. The… More >

  • Open Access


    Machine Learning Based Framework for Classification of Children with ADHD and Healthy Controls

    Anshu Parashar*, Nidhi Kalra, Jaskirat Singh, Raman Kumar Goyal

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 669-682, 2021, DOI:10.32604/iasc.2021.017478

    Abstract Electrophysiological (EEG) signals provide good temporal resolution and can be effectively used to assess and diagnose children with Attention Deficit Hyperactivity Disorder (ADHD). This study aims to develop a machine learning model to classify children with ADHD and Healthy Controls. In this study, EEG signals captured under cognitive tasks were obtained from an open-access database of 60 children with ADHD and 60 Healthy Controls children of similar age. The regional contributions towards attaining higher accuracy are identified and further tested using three classifiers: AdaBoost, Random Forest and Support Vector Machine. The EEG data from 19 More >

  • Open Access


    Cognitive Skill Enhancement System Using Neuro-Feedback for ADHD Patients

    Muhammad Usman Ghani Khan1,2, Zubaira Naz1, Javeria Khan1, Tanzila Saba3, Ibrahim Abunadi3, Amjad Rehman3, Usman Tariq4,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2363-2376, 2021, DOI:10.32604/cmc.2021.014550

    Abstract The National Health Interview Survey (NHIS) shows that there are 13.2% of children at the age of 11 to 17 who are suffering from Attention Deficit Hyperactivity Disorder (ADHD), globally. The treatment methods for ADHD are either psycho-stimulant medications or cognitive therapy. These traditional methods, namely therapy, need a large number of visits to hospitals and include medication. Neurogames could be used for the effective treatment of ADHD. It could be a helpful tool in improving children and ADHD patients’ cognitive skills by using Brain–Computer Interfaces (BCI). BCI enables the user to interact with the… More >

  • Open Access


    Mind-Body Exercises (Yoga/Tai Chi) for Attention-Deficit/Hyperactivity Disorder: A Quantitative Evidence of Experimental Studies

    Erfei Zuo1, Yanjie Zhang2, Qian Yu2, Tianyou Guo2, Can Jiao2, Ye Yu3, Patrick Müller4, Xinli Chi2, Md Mahhub Hossain5, Albert S. Yeung6, Notger G. Müller4, Liye Zou2,*

    International Journal of Mental Health Promotion, Vol.22, No.4, pp. 221-231, 2020, DOI:10.32604/IJMHP.2020.014552

    Abstract Background: Attention-deficit/hyperactivity disorder (ADHD) is a common pediatric psychiatric disorder. Although mindful exercises (Yoga and Tai Chi) have been increasingly accepted as alternative medicine for ADHD, no meta-analytic review has been conducted on this topic. Objective: We systematically and critically evaluated the existing literature regarding the effects of the two most widely practiced mindful exercises on ADHD symptoms and social problems in children and adolescents with ADHD. Methods: Searching literature databases included PubMed, Web of Science, Scope, China National Knowledge Infrastructure and Wanfang. Only randomized controlled trials (RCT) and nonrandomized controlled studies (NRS) that investigated the beneficial… More >

  • Open Access


    Statistical Analysis and Multimodal Classification on Noisy Eye Tracker and Application Log Data of Children with Autism and ADHD

    Mahiye Uluyagmur Ozturka, Ayse Rodopman Armanb, Gresa Carkaxhiu Bulutc, Onur Tugce Poyraz Findikb, Sultan Seval Yilmazd, Herdem Aslan Gencb, M. Yanki Yazgane,f, Umut Tekera, Zehra Cataltepea

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 891-905, 2018, DOI:10.31209/2018.100000058

    Abstract Emotion recognition behavior and performance may vary between people with major neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and control groups. It is crucial to identify these differences for early diagnosis and individual treatment purposes. This study represents a methodology by using statistical data analysis and machine learning to provide help to psychiatrists and therapists on the diagnosis and individualized treatment of participants with ASD and ADHD. In this paper we propose an emotion recognition experiment environment and collect eye tracker fixation data together with the application log data More >

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