Per Bækgaard, Associate Professor, Department of Applied Mathematics and Computer Science, Technical University of Denmark, has been awarded a grant of nearly DKK 8 million for developing a solution that can improve the reading ability of people with impaired vision and their educational opportunities. The grant is one of three collaborative projects within data science to which the Novo Nordisk Foundation awarded grants at the end of 2022. A new application round opened recently.

Millions of people have impaired vision, which negatively affects their daily life in various ways. Many of them have central vision loss, in which the centre of their field of vision is blurred so much that they have difficulty reading and carrying out other activities.

A new research project will address this problem.

Based on a grant of nearly DKK 8 million from the Data Science Collaborative Research Programme of the Novo Nordisk Foundation, Per Bækgaard will lead the development of an artificial intelligence model for determining the reading patterns of people with central vision loss with the aim of adapting reading material to each person’s needs.

The research is being carried out in collaboration with the Royal Danish Academy – Architecture, Design, Conservation and includes computer scientists, psychologists, experts in reading patterns and ophthalmologists.

“The project involves developing a model that enables us to rapidly decode a person’s reading patterns and simultaneously set, for example, the font size, contrast or spacing between letters on a mobile phone, a tablet or other screen, so that the material is optimally adapted to the person’s reading pattern, thereby providing the optimal reading experience and improving reading speed,” explains Per Bækgaard.

People with impaired vision can have difficulty in education
Reading can be a challenge for people with central vision loss. Many have to move their heads from side to side and forward and back to read the text. If the text is displayed on a tablet, a mobile phone or a computer, they also often adjust the contrast, increase or decrease the brightness or change the font size.

The many adjustments required to read a text often makes taking an educational programme more difficult for people with central vision loss and can also result in social problems. This research project is taking a completely new approach to this problem.

“Much is already being done to help people to improve their reading, but the reading material is still predominantly static. We would like to determine whether we can use modern technology to categorise the reading patterns of people with central vision loss and then use this knowledge to alter the reading material to automatically improve the reading process,” says Per Bækgaard.

Tracking eye movements
The main aim of the project is to develop a computer model that can interpret the reading pattern of people with central vision loss. The model primarily uses eye-tracking to follow a person’s eyes while they read and can thereby identify when they start skipping lines, how they move their heads to enable them to read and how their pupils expand and contract during different reading experiences.

The model should then be able to decode the reading experience of each person and thus dynamically adjust parameters, including screen contrast, font size, brightness, spacing between letters or lines and other parameters, to optimise reading.

This will all be driven by artificial intelligence, which will find the relevant data points in the reading patterns and determine how to adjust the reading material to accommodate each person’s reading challenges.

The project also aims to use the model to improve the determination of why some people have difficulty reading.

“The research involves identifying which signals are most relevant to the reading experience and how we can use those signals to change it. We want to use data systems to be able to decode a person’s reading patterns and automatically suggest which screen settings are best for them so that they can get the most out of reading,” concludes Per Bækgaard.

DKK 40 million awarded
The grant for Per Bækgaard’s project is one of three grants awarded through the Foundation’s Data Science Collaborative Research Programme. The grants are awarded annually for research projects that attempt to tackle some of the world’s major problems through interdisciplinary research and collaboration between research groups within data science, medicine, biology, plant science, biotechnology, physics and chemistry.

Projects and grant recipients

• Reading the Reader, led by Per Bækgaard, Associate Professor, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby: DKK 7,893,19
• CAZAI: CAZyme Specificity Prediction Using AI, led by Bernard Henrissat, Professor, Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby: DKK 14,995,489
• MOPITAS: Multi-omics Profiling in Time and Space, led by Richard Röttger, Associate Professor, Department of Mathematics and Computer Science, University of Southern Denmark, Odense: DKK 18,039,509

New application round for collaborative projects focusing on data science
The Foundation’s Data Science Collaborative Research Programme supports collaborative projects driven by data science that fall within the Foundation’s scientific focus areas: health, sustainability and the life science ecosystem.

The Data Science Collaborative Research Programme has changed from previous years. For example, the framework for the Programme has been expanded so that research projects dealing more broadly with computer-driven science can now also obtain grants. These projects may include simulations or mathematical modelling, for example. All interested applicants are encouraged to read the updated guidelines.

The annual grant budget for the programme is now DKK 75 million with up to DKK 30 million per grant. The next application deadline is 16 March 2023.