Developing a Low Cost Non-invasive Smartphone App for Detecting Anemia and Providing Diet Suggestions to Fight Anemia

Shams Nafisa Ali indicated 28.06.2019

About one quarter of the world’s population suffers from anemia, a disease that results from a concentration deficiency of hemoglobin in red blood cells. A few things that increase your risk of developing iron deficiency anemia include:

  •   being female
  •   being a vegetarian
  •   donating blood frequently
  •   being 65 or older

To reduce the burden of anemia, health officials need a better picture of the disease’s global impact, an understanding made viable by a portable and affordable way to analyze blood condition.

Hemoglobin is a protein found in red blood cells that transports oxygen throughout the body. As the concentration of hemoglobin decreases, the body becomes starved of oxygen, often resulting in dizziness, fatigue, shortness of breath, and abnormal heart rate.

Blood analyzers currently on the market measure hemoglobin by chemically rupturing the red blood cells in a sample. This technique requires hands-on expertise to prepare and run a sample, limiting the ability to monitor anemia in many parts of the world.

The most exciting aspect to this analyzer is that it does not need whole blood! The device only requires some pictures for analysis.

  1. eye blood and eye skin picture
  2. tongue picture
  3. hand nails picture

Then it will measure Hb level through image scanning and machine learning.

Features will be :

  • Non-invasive
  • Smartphone Based
  • Does not require additional equipment (aside from smartphone)
  • Low cost (<$25)
  • Accurate

Then after analyzing, the result will be used to make a nutrition based chart for anemia treatment. The app will use seasonal and region based available food, and will make height weight age and gender based nutrition chart for a week according to the severity of anemia.

The app will prompt to check anemia level in interval of 7 days, so it will be a kind of preventive method as anemia will be detected before going in severe stage.

Clinical need
Remote or self-diagnosis
Mobile-based technology
Anemia, Female Health, Machine Learning, Low Cost, Blood Analyzer, Image Processing