Bosch Uses AI in Hemoglobin Monitor to Detect Anemia without Blood Test

WHO has approximated that about 1.6 billion people suffer from Anemia, a condition resulting from the reduced hemoglobin concentration in the blood. This has provoked WHO to bring up a measure to curb anemia as one of its critical sustainable development goals for 2025. Thus, Bosch has developed a portable Hemoglobin Monitor Solution (HMS) particularly for regions where routine access to medical care tends to be difficult. This HMS allows a large number of people to be screened for anemia rapidly, safely, using a non-invasive approach. The solution has been named a CES Innovation Award Honoree in the “Health and Wellness” category.

Dattatri Salagame, President and Managing Director of Robert Bosch Engineering and Business Solutions Private Limited (RBEI) states, “Bosch has developed the non-invasive Hemoglobin monitor as an innovative solution and as an alternative to traditional methods for the early detection of anemia. This should offer people better diagnosis options even in resource constrained conditions. The use of artificial intelligence is revolutionizing anemia management, specifically in point-of-care setups and closer to the patient.”

The intelligent product designed by Bosch could be used directly at the point-of-care and is completely pain-free. This doesn't require a blood test, as the value is determined by a finger scanner using multi-wavelength spectrophotometry on the surface of the skin. However, the system uses an optical sensor to precisely and reliably measure the photoplethysmogram (PPG) signals. Photoplethysmography, or PPG, is an optical technique used to detect volumetric changes in blood in peripheral circulation. The device provides a reliable result in less than 30 seconds even for people with low hemoglobin concentrations.

The algorithm has been adopted with more than 10,000 anemia data points. These clinically collected data along with the corresponding ground truth data, are the basis for the machine learning algorithm. The more validated data sets are put into the continuously learning algorithm, the more precise the results will be.

This doesn't require analysis and there is no risk of any infection from contaminated needles. Participants receive their test results quickly at the point of care. The device is battery operated, does not need subsequent calibration, and is extremely easy to use. It is intended for use in outlying and remote regions by healthcare professionals. Location-based reporting ensures easy clinical traceability. Organizations that operate multiple devices can draw conclusions through heat maps about specific regions. Patient data remains anonymous. Market release in India is expected by mid-2021.