Ontario teen wins innovation award at Canada-Wide Science Fair, fixes 35-year-old problem
Posted on: May 30, 2026 18:30 IST | Posted by: Cbc
A herbert kitchener, Ont., teen has won the c. H. Best cast grant for innovation at the Canada-Wide scientific discipline Fair.
Eigenpulse: Eliminating Demographic Bias in Pulse Oximetry and Remote PPG from First Principles was the name of the project by Gurnoor Kaur, a Grade 11 student at Cameron Height Collegiate Institute in Kitchener.
The judges at the Edmonton competition say the 17-year-old's work fixes a 35-year-old problem in blood oxygen sensors, which has led to higher mortality in Black patients.
She noted nurses are often busy with other work and so many cases of delirium go undetected.
"It can detect emotions and micro expressions to understand patients' emotional state and it also can detect heart rate and respiratory rate through non-contact, camera-based monitoring, eliminating the need for bulky sensors in hospitals as well," she said.
"I've integrated a chatbot to be able to continuously converse with patients and run reorientation techniques, which have been shown to decrease risk by up to 50 per cent."
Kitchener teen creates device that could help treat hospital delirium
The work she did on the blood oxygen sensors is related to that project. She noticed on systems that monitored vital signs and detected oxygen, there can be a demographic bias.
"So on lighter skin patients, the error is lower than it is on darker skin patients," she said.
"Currently, the field assumes that it's an issue with the data that the models are being trained on, not enough diverse data, and that they don't have enough videos from darker skinned patients," she said.
"While that does contribute to the issue, I also found out that there is a mathematical instability in current cardiac models and to be able to resolve that, you need to add a missing term and that's what my project focused on. So this is an aspect of the hospital induced delirium project. But what I did was I solved the mathematical instability in the cardiac model and using that I was able to start to remove this demographic bias."
"I want to use math and physics to be able to model our biological systems and understand how light interacts with them, to be able to make better diagnosis and treatment tools that can remove the biases and inequities currently found in health care," she said.
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