Attention-deficit/hyperactivity disorder (ADHD), is a behaviour disorder, usually first diagnosed in childhood, that is characterized by inattention, impulsivity, and hyperactivity. ADHD is often associated with co-morbid disorders like bipolar disorder, anxiety, depression, and substance abuse. The diagnosis of ADHD is clinically established by a review of symptoms and impairment from the child’s young age. There are numerous assistive technologies that exist for people suffering from ADHD but there exists a research gap in developing self-reflective tools for people with neurodevelopmental disorders. This paper bridges this research gap for students at Malmö University. This project will focus on developing a personalized interactive AI-based system that captures contextual data, analyses it to find relevant patterns in user’s behaviour, and visualizes it effectively to provide students with ADHD with insights into the parameters influencing the nature of their disorder. The project is performed under a Double Diamond method which allows for iteration. The methods used mostly comprise co-design methods to ensure the concept caters to the user’s needs. The project is based on learnings from three key areas: Interactive AI, Personal Informatics and Systems as dialogue partners.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-55292 |
Date | January 2022 |
Creators | Ravishankar, Vandana |
Publisher | Malmö universitet, Institutionen för konst, kultur och kommunikation (K3), Malmö University |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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