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ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning

Thesis (MEng)--Stellenbosch University, 2019.

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Bibliographic Details
Main Author: Swarts, Romano
Other Authors: Fourie, Pieter Rousseau
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2019
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access_status_str Open Access
author Swarts, Romano
author2 Fourie, Pieter Rousseau
author_browse Fourie, Pieter Rousseau
Swarts, Romano
author_facet Fourie, Pieter Rousseau
Swarts, Romano
author_sort Swarts, Romano
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MEng)--Stellenbosch University, 2019.
format Thesis
id oai:scholar.sun.ac.za:10019.1/106231
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:46:33.531Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2019
publishDateRange 2019
publishDateSort 2019
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/106231 ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning Swarts, Romano Fourie, Pieter Rousseau Van den Heever, David Jacobus Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering (CRSES) ADHD (Child behavior disorder) Machine learning Attention-deficit disordered children Hyperactive children Attention-Deficit Hyperactivity Disorder ADHD -- Treatment ADHD -- Diagnosis Human-computer interaction Computer-human interaction UCTD Thesis (MEng)--Stellenbosch University, 2019. ENGLISH ABSTRACT: This study investigated the effectiveness of a tablet-based game that incorporated machine learning to screen participants between the ages of six and twelve years for ADHD inattentive subtype. Prior to the design and development of the ADHD screening tool, a thorough investigation of the literature was conducted. Additionally, existing ADHD screening tools and cognitive training tools were identified. This research project implemented lessons learned from the literature, as well as input from medical professionals and the DSM-V diagnostic criteria. The ADHD screening tool presents a patient-testing interface in the form of a tablet-based game with a cloud-based machine learning classifier. The cloud-based classifier is integrated with an algorithm, and together they can discriminate between ADHD and non-ADHD patients with a sensitivity of 100i% and specificity of 87.5i%. The device used for testing was a single, internet connected, commercially available tablet. No additional hardware is required. AFRIKAANSE OPSOMMING: Hierdie studie het ondersoek ingestel om die effektiwiteit van 'n tablet-gebaseerde speletjie om deelnemers tussen die ouderdomme van ses en twaalf jaar vir ADHD-onoplettende subtipe te evalueer. Voor die ontwerp en ontwikkeling van die ADHD keuring instrument was 'n deeglike ondersoek ingestel om die literatuur te ondersoek. Daarbenewens was die bestaande ADHD keuring instrumente en kognitiewe opleidingsinstrumente geïdentifiseer. Hierdie navorsingsprojek het lesse van uit die literatuur geïmplementeer, sowel as insette van mediese professionele en die DSM-V diagnostiese kriteria. Die ADHD evalueringsinstrument bied 'n pasiënt-toets in die vorm van 'n tablet-gebaseerde speletjie met 'n wolk-gebaseerde masjienleer klassifiseerder. Die wolk-gebaseerde klassifiseerder is geïntegreer met 'n algoritme, en saam kan hulle onderskei tussen ADHD en nie-ADHD pasiënte met 'n sensitiwiteit van 100i% en spesifisiteit van 87.5i%. Die toestel wat gebruik was vir toetsing is 'n enkele, internet-gekoppelde, kommersieel beskikbare tablet. Geen bykomende hardeware word benodig nie. 2019-02-28T10:29:40Z 2019-04-17T08:35:55Z 2019-02-28T10:29:40Z 2019-04-17T08:35:55Z 2019-04 Thesis http://hdl.handle.net/10019.1/106231 en_ZA Stellenbosch University xvii, 114 pages : illustrations application/pdf Stellenbosch : Stellenbosch University
spellingShingle ADHD (Child behavior disorder)
Machine learning
Attention-deficit disordered children
Hyperactive children
Attention-Deficit Hyperactivity Disorder
ADHD -- Treatment
ADHD -- Diagnosis
Human-computer interaction
Computer-human interaction
UCTD
Swarts, Romano
ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning
title ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning
title_full ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning
title_fullStr ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning
title_full_unstemmed ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning
title_short ADHD screening tool: investigating the effectiveness of a tablet-based game with machine learning
title_sort adhd screening tool investigating the effectiveness of a tablet based game with machine learning
topic ADHD (Child behavior disorder)
Machine learning
Attention-deficit disordered children
Hyperactive children
Attention-Deficit Hyperactivity Disorder
ADHD -- Treatment
ADHD -- Diagnosis
Human-computer interaction
Computer-human interaction
UCTD
url http://hdl.handle.net/10019.1/106231
work_keys_str_mv AT swartsromano adhdscreeningtoolinvestigatingtheeffectivenessofatabletbasedgamewithmachinelearning