Faculty of Computing

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Has files: YesSubject: search.filters.subject.ADHD

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    Therapy Tool for Adolescents with ADHD
    (IEEE, 2019-12-05) Nugawela, R. C. W. M. R. H. E; Fonseka, W. G. S; Perera, G. U. C; Mihirangi, S. K. S; Kahandawaarachchi, K. A. D. C. P
    Attention deficit hyperactivity disorder (ADHD) is one of the most common disorders widespread among children and adolescents. Adolescence is the transitional phase between childhood and adulthood. The main three symptoms of ADHD are hyperactivity, impulsivity and inattention. Prevalence of ADHD among adolescents is approximately 5% in Sri Lanka. Treatment is a vital factor in any ADHD patient's lifestyle which involves a combination of pharmaceutical medications as well as therapeutic treatments with the help of the patient's family and friends. With no proper treatment, children and adolescents with ADHD are faced with the risk of carrying on the symptoms of the disorder into adulthood. Hence, the importance of treatments for patients diagnosed with ADHD is clearly evident. The solution derived at is an Android Application to provide a therapeutic treatment acceptable to the three groups of symptoms in ADHD and to track and maintain a log of records of the patient's performance and progression. For this research, one participant each was dedicated for each testing module in order to eliminate subjectivity and ensure accuracy. The Android Application developed consists of activities targeted at treating all main groups of ADHD symptoms and offers a feasible solution for patients, parents and specially for doctors to monitor the patient's progress.
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    Individualized Edutainment and Parent Supportive Tool for ADHD Children
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Thennakoon, A.; Perera, D.; Sugathapala, S.; Weerasingha, S.; Samarasinghe, P.; Dahanayake, D.; Piyawardan, V.S.
    Attention-Deficit/Hyperactivity Disorder (ADHD) is a comorbid disorder that can impact a child and his/her family. ADHD children have considerable obstacles in managing time, understanding instructions, and paying attention to the activities. To address these perplexities, this research has designed a mobile application to help parents to have better interaction with the children and for the children to enjoy their learning activities. The specialty of this application is the models are trained on individual child skills and needs. Issues with time management are handled by the Scheduler component while the Instruction Predictor module supports the parent in recognizing the child's understandability level. Furthermore, the children are provided with edutainment activities based on their attention and ability levels. Different models have been used in predicting the results through these modules and the prediction result accuracy exceeds 90% in most of the cases. Out of the many models, The Random Forest model resulted in the best overall performance. The application was tried by many parents and health professionals and received satisfactory and commendable reviews.