Graphia

Graphia is an essay writing aid tool for children that encourages visual thinking and improves visual and auditory processing, whilst simultaneously democratizing the diagnosis process for Dysgraphia in middle school aged kids. It offers an AI driven graphic tablet based diagnostic tool at a fraction of the price of traditional diagnostic methods.

In Collaboration with: National Alliance on Mental Illness + Luisa Charles, Marco Da Re, Serra Umut from Royal College of Art, UK

Advisor

Dr. Alexander Schweder

Role

Design Research

Code Development

Video Production

Year

2021

Outcome

Presented at RCA WIP '22

Product proposals for tech companies

Recognition

Start-up Power Award, Pratt ROH '22

Research

Dysgraphia is estimated to affect approximately 20% of children, and is a neurological disorder that is considered a symptom of ASD, ADD ,etc. It manifests in illegible handwriting, poor visual, auditory, and phonological processing, pain throughout the nervous system, poor thought organization, and an inability to use writing as a communication tool. Children with Dysgraphia tend to perform poorly in school, and have a higher rate of depression and anxiety. Diagnosis is done by a child behavioral psychologist through tests like TOWL is:

  • Time consuming

  • Expensive

  • Delayed

Conceptualization

Through a research based iterative design process and identifying current trends, it was decided that a digital tool would be optimal to aid in the pre-diagnosis for dysgraphia as it might be useful in the school setting. The act of writing is something children do everyday and integrating the product with existing systems helps create a more holistic approach to the issue of under diagnosis. 

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Outcome

Graphia aims to solve the issues of under diagnosis, and to provide coping strategies for those experiencing Dysgraphia with three tools;

  • Coping tools that provide strategies for children with or without Dysgraphia to learn how to write essays more easily and effectively.

  • Diagnostic tools that use a Machine Learning algorithm to provide a pre-diagnosis of Dysgraphia. Pre-diagnosis is made by analyzing handwriting, and looking into pen pressure, pen angle and altitude, punctuation, grammar, and spelling data. 

  • Post-Diagnostic physical tools that enable children to continue utilizing the visual essay writing skills they have learnt even after they might lose access to a tablet

Prototype

With a focus on diagnosis for children, but keeping in mind the socio-mental impact of diagnosis, especially in the school setting, Graphia is discreetly packaged as an essay writing toolkit to help children visual what their thoughts. The tool helps all children map out their essays visually, gives progress reviews, provides an audio-processing solution for class notes, and helps grammar and spelling.

Details

 Graphia uses a machine learning algorithm to analyze pen pressure, altitude, azimuth angle and handwriting to provide data on potential dysgraphia. Using existing techniques, the data is visually represented and translated into a pre-diagnosis. This can be then shared with the educator and immediate actions can be taken, to help the student reach their fullest potential.

Alongside this, the digital coping tool helps all students organize their thoughts through visual methods

Graphia also comes with a post-diagnostic toolkit which enhances remediation through employing visual and tactile solutions.

Click here to check out the code (best viewed on iPad)