Smartphones have their own merits and demerits. Apart from talking and texting, there are many surprising things that you can do with your smartphone. For instance, you can measure your heart rate, monitor your asthma, blood pressure, etc. Recently researchers have developed an algorithm in smartphones that detects anemia with more than 70% accuracy.
Anemia is caused by nutritional deficiency, poor diet, and the most common type of anemia is caused by the shortage of iron in your body. Nearly 30% of the population is affected by anemia. Anemia can cause serious health problems if untreated it can cause severe fatigue, pregnancy complications, heart problems and can even lead to death.
Ways to Detect Anemia
To diagnose anemia, your doctor will ask you to do the following test
Complete blood count (CBC) – It is the first and foremost test for diagnosing anemia. This test measures your hemoglobin and hematocrit levels.
Hemoglobin electrophoresis- This test is to determine the different types of hemoglobin in your blood.
A reticulocyte- This test measures the number of young red blood cells in your blood.
All these above-mentioned methods might not be easily accessible to many people and on other hand, all these tests are a bit costly too. By considering all this, a team of researchers has found out a simple method to detect anemia i.e by using a smartphone picture of a person’s lower eyelid. But how?
Smartphone Cameras to Detect Anemia
Recent research published in PLOS ONE disclosed a new technique to diagnose the symptoms of anemia. According to the study, the paleness of the palpebral conjunctiva that lines the eyelids is one of the severe symptoms of anemia. Researchers conducted a two-phase study to find the possibility of using a smartphone camera to detect anemia. The first phase involved the smartphone images of 142 patients in an emergency department. The researchers selected the inner lower eyelids palpebral conjunctiva for the following reasons:
- It can be easily photographed.
- The color can easily distinguish between blood vessels and the conjunctival surface.
- The distance between blood vessels and their surface is very small.
- No factors will significantly affect blood flow in this area.
By zooming in the photo the researchers developed an algorithm that maximizes color resolution and a predictive model. This helped to identify the skin and the eyes to hemoglobin levels. In the second phase, the scientists tested the algorithm on smartphone images of 202 patients of the emergency departments. The findings showed 72.6 percent accuracy in detecting anemia. It also predicted the case of severe anemia that requires a blood transfusion was higher, at between 86% and 94.4%.
Whether the mobile camera flash is on or off, this technique provides the same and instant results. The only limitation will be on the impact of the quality of the picture and even due to the person retracting their eyelid during the recording of the image.