Indian-origin girl fixes flaw in oximeter:17-year-old eliminates pulse oximeter’s racial bias in oxygen readings

A 53-year-old flaw in pulse oximeter devices widely used in hospitals to measure blood oxygen levels may finally have a solution, because of a 17-year-old student of Punjab origin in Canada. Studies have shown that conventional pulse oximeters can be less accurate for people with darker skin tones, sometimes overestimating oxygen levels compared to readings in lighter-skinned individuals. Seeking to address this issue, Gurnoor Kaur developed ‘EigenPulse’, an improved mathematical model designed to enhance the device’s accuracy across different skin tones. According to Gurnoor, the innovation enables pulse oximeters to provide far more reliable oxygen readings regardless of a person’s skin colour, helping reduce disparities in patient care. For this breakthrough, Gurnoor was awarded the Best Project Award for Innovation at Canada’s largest National Science Fair, earning recognition for her contribution to improving a critical medical device used worldwide. How did the oximeter do color discrimination, know… Know in 4 points, what Gurnoor did… How the pulse oximeter story began for Gurnoor Gurnoor explained that when she was testing this delirium platform, she noticed something very strange and concerning. She observed that when her AI system measured the heart rate and oxygen levels of patients with light-colored (fair) skin, the data was completely accurate, but as soon as a dark-skinned or deeply complexioned patient came forward, the graph of errors in the system’s readings suddenly shot up very high. This question settled in Gurnoor’s mind: why exactly was a machine giving different results based on human skin color? He took this as a challenge and, pausing his old research for a while, began an in-depth study of the entire functioning of the pulse oximeter. He started scouring through college and university-level physics and mathematics books. After months of hard work and research, he finally caught that mathematical error which had been blinding the medical world for decades. Thus, research that began with a noble purpose ended up solving a very big problem of the world. Calculations based on Beer-Lambert Law principle When Gurnoor gave the presentation of his model, he explained that the traditional pulse oximeter works on a very simple principle, which in scientific language is called the ‘Beer-Lambert Law’. When you place the oximeter on your finger, two types of lights emerge from one side. One is red light, and the other is infrared light. This light passes through our skin, flesh, and blood vessels and falls on a sensor placed on the other side. The hemoglobin in our blood that is carrying oxygen absorbs more infrared light. On the other hand, hemoglobin that does not contain oxygen absorbs more red light. The machine calculates the ratio of absorption of these two lights using a traditional equation or formula called the ‘Ratio of Ratios’. This old formula assumed that skin color (melanin pigment) is a constant component that affects light the same way in every person, but in reality, the ‘melanin’ present in darker skin scatters light much more. The old mathematical model completely ignored this scattering, which caused oxygen levels in dark-skinned people to appear 2% to 5% higher than reality. How will the calculation be done with Gurnoor’s new mathematical formula Gurnoor explained that in his research, he found that when the oximeter’s light hits the skin, the scattering of light and skin thickness together create an unstable term. He added a new correction factor to the formula used for its reading that automatically adjusts the light scattering based on skin color. In simple words, Gurnoor’s formula tells the machine that if the skin color is darker and light is scattering more, then subtract the effect of that scattering from the mathematical calculation. After this new mathematical correction, as soon as the light passes through the finger, the sensor will only count the oxygen present in the blood; no matter how dark the skin color is, it will not affect the reading even slightly. This mathematical model makes the calculation completely unbiased and accurate for people of every color. Right Treatment at the right time and reduction in deaths The biggest challenge in hospitals is to detect the deterioration of a patient’s condition before it worsens. Due to incorrect readings from pulse oximeters, millions of dark-skinned and Black patients have not been able to receive oxygen or ICU beds on time, which has led to their condition worsening further. In many cases, patients have even lost their lives. Data from American hospitals shows that due to this deficiency, the mortality rate among Black patients was significantly higher. With Gurnoor’s discovery, doctors will now receive accurate information, which will stop incorrect treatment and save the lives of thousands and millions of innocent people.
Gurnoor receives National Award at ‘Canada-Wide Science Fair’ Gurnoor Kaur was honored at the 64th ‘Canada-Wide Science Fair’ organized by Youth Science Canada following this historic amendment. This is Canada’s most prestigious and largest youth science competition. The 2026 Science Fair was held in Edmonton city of Alberta province. In the final round of this competition, 390 of the most promising students selected from across Canada participated, who presented 344 excellent projects related to science and technology. A large judging panel of more than 250 renowned scientists, professors, and doctors was formed to examine all these projects and select the winners. Gurnoor Kaur was awarded the fair’s biggest prize, the ‘Best Project Award for Innovation’ for her project Eigenpulse. Youth Science Canada’s Executive Director, Renee Barlow, praised Gurnoor, saying, “When an 11th-grade student identifies and fixes a gap in medical technology that has claimed many lives for over three decades, it proves what young people can achieve when their curiosity is given the right direction and support. Gurnoor has made our country proud.”