Hafsa Ashfaque
designer, creator, maker, thinker.
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ThoroughLine - a reading interface designed with adults with ADHD
For most of my life I thought I was just bad at reading longform, especially anything academic. I'd reach the end of a page and realise nothing had gone in. I'd read the same paragraph three times. I'd lose my place, lose the thread, and get through it eventually, but it took me far longer than my peers.
During my master’s, I spent over a year researching why. It turned out the struggle wasn't me, it was built into how most reading tools work. My thesis became a three-phase participatory study: a co-design workshop with seven adults with ADHD, a full redesign based on what they told me, and a heuristic evaluation with five UX professionals.
The research told me what was needed. It couldn't show me what it would feel like to use. So for the Config Makeathon, I built it.
It's called ThoroughLine.
Live prototype: https://thoroughline.figma.site/
Figma Community file: https://www.figma.com/community/file/1649415417146487825
Socials: https://www.linkedin.com/posts/hafsaashfaqq_configmakeathon-ugcPost-7473361559449174020-P3fX/?utm_source=share&utm_medium=member_desktop&rcm=ACoAADKxDPIBlmvcYrb8oh7dkc4lsaH5ex97Afw
ThoroughLine is built around one rule: notice quietly, never overwhelm. Instead of piling on options, it watches how you actually read and offers help only when it detects you need it, one gentle nudge at a time, never stacking, always dismissible, and you can turn the whole thing down.
Every feature traces back to a specific finding:
Presets: One tap reconfigures everything, Focus to go deep, Skim to move fast.
Typography control: Font, size, spacing, and typeface are front and centre and on by default, because typographic adjustment was the single strongest finding in my study (highest rating, lowest variability across participants).
Blur focus: Reduce cognitive load and focus on one thing at a time.
The noticing system: It watches several signals and responds warmly: when your gaze or cursor drifts off the text, it brings you back to your line. When you re-read a dense passage, it offers to read it aloud. When you stall, it saves your spot. When your pace drops well below your own baseline, it gently offers help. All of it is governed, one nudge at a time, with cooldowns, so it supports without nagging.
Thought parking: When a stray thought hits mid-sentence, you park it in a note and keep reading, instead of losing your place chasing it.
Read-aloud: When reading is hard that day, it reads to you and the text follows along, so your eyes and ears stay on the same line.
Eye tracking: An honest preview. On a webcam it's rough, it's designed to run on professional eye trackers (the Tobii-class hardware my research team uses), where the same drift-recovery logic becomes precise. I built the interaction layer; the signal source is swappable.
It isn't finished, and I'm not pretending it is. On-demand summaries and gentle comprehension check-ins, for the "I read it but didn't absorb it" moment, are the next pieces. Both need a small backend I'm adding after the deadline.
I'm a designer, not a developer. I came in with the research, the user flows, and the information architecture. Figma Make turned designs I could only ever mock up into something you can actually open and use. The thinking was mine; Make gave it a pulse. The entire interface, the noticing logic, the reading mechanics, was built and iterated in Figma Make.
Built with Figma Make for #ConfigMakeathon @figma
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