Painful blood tests may be over after scientists develop a new tool to measure hemoglobin – using a smartphone.
The breakthrough new method uses pictures of a person’s eyelids to assess hemoglobin levels in their blood.
Being able to perform one of the most common clinical laboratory tests without drawing blood can help reduce the need for in-person clinic visits, making it easier to remotely monitor critical patients and improve care in countries with limited access to testing laboratories.
Purdue University study leader Professor Young Kim said, “Our new mobile health approach paves the way for testing bedside or remote blood hemoglobin levels to detect anemia, acute kidney injury and bleeding, or to assess blood conditions such as sickle cell anemia.
“The Covid-19 pandemic has increased awareness of the need for comprehensive mobile health and telemedicine services.”
Professor Kim and colleagues from the University of Indianapolis, Vanderbilt University School of Medicine in the US and Moi University School of Medicine in Kenya used software to transform a smartphone camera into a hyperspectral imager that reliably measures hemoglobin levels – a measure of the oxygen transport blood capacity – without the need for hardware adjustments or accessories.
A pilot clinical trial with volunteers at Moi University Teaching and Referral Hospital found that the prediction errors for the smartphone technique were within 5 to 10% of those measured with clinical laboratory blood.
Professor Kim said, “This new technology can be very helpful in detecting anemia, which is characterized by low hemoglobin levels in the blood.
“This is a major public health problem in developing countries, but it can also be caused by cancer and cancer treatments.”
Spectroscopic analysis is regularly used to measure hemoglobin levels because it has a clear light absorption spectrum or fingerprint in the visible wavelength range. However, this type of analysis usually requires bulky and expensive optical components.
The researchers created a mobile health version of this analysis using an approach known as super spectral resolution spectroscopy.
This technique uses software to virtually convert photos taken with low-resolution systems, such as a smartphone camera, into high-resolution digital spectral signals.
They chose the inner eyelid as a sensor location because it is easily accessible and relatively uniformly red, nor is it affected by skin color.
To take the measurement, the patient pulls the inner eyelid down to expose the small blood vessels underneath. A healthcare professional then uses the smartphone app developed by the researchers to take pictures of the eyelids.
A spectral super-resolution algorithm is applied to extract the detailed spectral information from the camera images and then another algorithm quantifies the hemoglobin level by detecting its unique spectral characteristics.
After tests with more than 150 volunteers, the results showed that the mobile health test could provide measurements comparable to traditional blood tests.
Professor Kim added, “Our work demonstrates that data-driven and data-centric light-based research can offer new ways to minimize hardware complexity and facilitate mobile health.
“Combining the built-in sensors available in today’s smartphones with data-centric approaches can accelerate the pace of innovation and research translation in this field.”