AI-Based Technopreneurship for Speech Disorder Therapyin ADHD Children

While existing literature explores AI in healthcare, this study uniquely high-lights technopreneurial approaches to address accessibility and affordability ofAI-based therapies. Focusing on Indonesia as a case study, the paper exam-ines how AI can support children with ADHD who often face delays in speechdevelopment and communication. ADHD affects attention, language process-ing, and social interaction, creating challenges for effective therapy. AI inte-grates machine learning to analyze speech patterns, detect phonological errors,and provide adaptive therapy exercises tailored to children’s developmental lev-els. Findings indicate that AI improves diagnostic accuracy and delivers engag-ing interventions through interactive and gamified tools, enhancing motivationand participation for children who struggle with conventional therapy. AI sys-tems can track progress and adjust feedback in real time, offering personalizedsupport. However, barriers remain regarding affordability, infrastructure, andthe need for human oversight to manage complex emotional and behavioral re-sponses. In this context, technopreneurship is essential to scale affordable AI-based therapies for schools, clinics, and homes. By bridging gaps in healthcaredelivery, this study contributes to SDG 3 (Good Health), SDG 4 (Quality Ed-ucation), and SDG 10 (Reduced Inequalities). It emphasizes the importance ofinterdisciplinary collaboration among AI developers, speech-language patholo-gists, medical professionals, and educators. Overall, AI-driven technopreneur-ship demonstrates strong potential to improve early detection, therapy person-alization, and language development for children with ADHD, while ensuringbroader accessibility and sustainability.

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Publication Details

Journal
Journal of Computer Science and Technology Application
Published
2025-08-31
DOI
https://doi.org/10.33050/corisinta.v2i2.135
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Based Technopreneurship for Speech Disorder Therapyin ADHD Children

Subyantoro Subyantoro, Yusro Edy Nugroho, Ida Zulaeha, Uki Hares Yulianti et al.
Journal of Computer Science and Technology Application
EEG and Brain-Computer Interfaces
article

AI-Based Technopreneurship for Speech Disorder Therapyin ADHD Children

Subyantoro Subyantoro, Yusro Edy Nugroho, Ida Zulaeha, Uki Hares Yulianti, Kgomotso Moyo
article en

Abstract

While existing literature explores AI in healthcare, this study uniquely high-lights technopreneurial approaches to address accessibility and affordability ofAI-based therapies. Focusing on Indonesia as a case study, the paper exam-ines how AI can support children with ADHD who often face delays in speechdevelopment and communication. ADHD affects attention, language process-ing, and social interaction, creating challenges for effective therapy. AI inte-grates machine learning to analyze speech patterns, detect phonological errors,and provide adaptive therapy exercises tailored to children’s developmental lev-els. Findings indicate that AI improves diagnostic accuracy and delivers engag-ing interventions through interactive and gamified tools, enhancing motivationand participation for children who struggle with conventional therapy. AI sys-tems can track progress and adjust feedback in real time, offering personalizedsupport. However, barriers remain regarding affordability, infrastructure, andthe need for human oversight to manage complex emotional and behavioral re-sponses. In this context, technopreneurship is essential to scale affordable AI-based therapies for schools, clinics, and homes. By bridging gaps in healthcaredelivery, this study contributes to SDG 3 (Good Health), SDG 4 (Quality Ed-ucation), and SDG 10 (Reduced Inequalities). It emphasizes the importance ofinterdisciplinary collaboration among AI developers, speech-language patholo-gists, medical professionals, and educators. Overall, AI-driven technopreneur-ship demonstrates strong potential to improve early detection, therapy person-alization, and language development for children with ADHD, while ensuringbroader accessibility and sustainability.

Journal of Computer Science and Technology ApplicationVol. 2(2)
State University of Semarang (ID)
Openalex Percentile: Top 71%
EEG and Brain-Computer Interfaces
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