In this project, Dr Liam Barrett at University College London will create a method for digitally interpreting analogue, older hearing test results, securing this data for future research.
Project start date: April 2025
Project end date: April 2026
About the project
When you have a hearing test, the results are drawn as a graph called an audiogram, showing how well you can hear sounds at different frequencies (or pitches). Since 2005, these tests have been recorded digitally on computers, but older tests were drawn on paper.
These older tests contain valuable information about how hearing changes over time, which is helpful in developing better treatments. The researchers aim to digitalise these earlier, hand drawn test results to ensure their information isn’t lost.
How it works
The researchers will develop a new computer system that can automatically convert these hand-drawn hearing tests into digital information. They’ll use artificial intelligence to teach computers how to “read” the graphs and convert them into numbers that researchers can analyse. They’ll test their new system on over 600,000 hearing tests to ensure it works accurately and reliably.
Once they’ve developed it, the tool will be made freely available online so that hospitals and researchers worldwide can digitise their historical hearing tests, including older records in modern research and improving their understanding of hearing loss over time.
How will this research benefit people at risk to losing their hearing?
This research will help doctors and researchers better understand how hearing changes over time, leading to more accurate predictions about hearing loss progression. It will ensure that research includes data from people of all ages and backgrounds, not just those who had digital tests, and give researchers access to much more information about hearing loss, helping them develop and test new treatments.
About the researcher
Dr Liam Barrett is a research fellow at the UCL Ear Institute in the EvidENT team at University College London.
I hope my research will make quality hearing healthcare more widely available. By applying AI to digitise and analyse audiograms, we can unlock valuable clinical data from paper records that would otherwise remain unused. This could help us better understand different patterns of hearing loss and how they change over time.”
