Technological Intervention and Diagnosis System for Individuals with Attention Deficit Hyperactivity Disorder ADHD
| dc.contributor.guide | Sharma, Anurag and Khullar, Vikas | |
| dc.coverage.spatial | ||
| dc.creator.researcher | Mishra, Santosh Kumar | |
| dc.date.accessioned | 2025-11-11T07:15:58Z | |
| dc.date.available | 2025-11-11T07:15:58Z | |
| dc.date.awarded | 2025 | |
| dc.date.completed | 2025 | |
| dc.date.registered | 2019 | |
| dc.description.abstract | This thesis presents the development and evaluation of two innovative technological solutions for the diagnosis and treatment of attention deficit hyperactivity disorder (ADHD): an AI-assisted diagnostic system and a virtual reality (VR) intervention platform. The AI diagnostic tool integrates multimodal data, including clinical phenotypes, cognitive assessments, neuroimaging, genomics, and digital behavioral signals, to classify ADHD cases with enhanced accuracy and objectivity. The best-performing ensemble model achieved an accuracy of 88%, sensitivity of 90%, specificity of 86%, and an AUC-ROC of 0.94, outperforming clinician-based methods in diagnostic reliability and consistency. newlineThe VR-based therapeutic system was designed to address attention, inhibition, emotional regulation, and social skills through immersive, gamified modules. In a randomized controlled trial, individuals receiving VR therapy demonstrated significantly greater reductions in ADHD symptom severity and functional impairments compared to standard treatments. Symptom improvements were maintained at 6- and 12-month follow-ups, indicating strong durability of treatment effects. Notably, emotional regulation and attention gains were major mediators of these improvements. User engagement was high, with over 89% completion of therapeutic modules and favorable satisfaction ratings. newlineTogether, the diagnostic and intervention systems showed strong feasibility for integration into clinical workflows. Clinicians reported increased diagnostic confidence, and the solutions performed reliably across diverse demographic subgroups. This thesis underscores the promise of AI and VR technologies in delivering personalized, scalable, and effective care for ADHD. newline newline | |
| dc.description.note | ||
| dc.format.accompanyingmaterial | CD | |
| dc.format.dimensions | ||
| dc.format.extent | i-xii,159 | |
| dc.identifier.researcherid | 0000-0001-6484-6353 | |
| dc.identifier.uri | http://hdl.handle.net/10603/672823 | |
| dc.language | English | |
| dc.publisher.institution | Department of Computer Science | |
| dc.publisher.place | Hoshiarpur | |
| dc.publisher.university | GNA University | |
| dc.relation | ||
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Attention Deficit Hyperactivity Disorder (ADHD), AI-assisted diagnostic system, Virtual Reality (VR) intervention, machine learning, multimodal data integration, cognitive and behavioral assessment, personalized therapy, biofeedback, neuroimaging, genomic markers, technological innovation in mental health | |
| dc.subject.keyword | Computer Science | |
| dc.subject.keyword | Computer Science Artificial Intelligence | |
| dc.subject.keyword | Engineering and Technology | |
| dc.title | Technological Intervention and Diagnosis System for Individuals with Attention Deficit Hyperactivity Disorder ADHD | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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