Smartphone-Based Technique Helps Doctors Assess Hematological Disorders

As one of the most common clinical laboratory tests, blood hemoglobin tests are routinely ordered as an initial screening of reduced red blood cell production to examine the general health status before other specific examinations.

Blood hemoglobin tests are extensively performed for a variety of patient care needs, such as anemia detection as a cause of other underlying diseases, assessment of hematologic disorders, transfusion initiation, hemorrhage detection after traumatic injury, and acute kidney injury.


Biomedical Engineers at Purdue University (West Lafayette, IN, USA) and their colleagues have developed a way to use smartphone images of a person's eyelids to assess blood hemoglobin levels. The ability to perform one of the most common clinical laboratory tests without a blood draw could help reduce the need for in-person clinic visits, make it easier to monitor patients who are in critical condition, and improve care in low- and middle-income countries where access to testing laboratories is limited.

The scientists tested the new technique, called mHematology, with 153 volunteers who were referred for conventional blood tests at the Moi University Teaching and Referral Hospital (Eldoret, Kenya). They used data from a randomly selected group of 138 patients to train the algorithm, and then tested the mobile health app with the remaining 15 volunteers. The results showed that the mobile health test could provide measurements comparable to traditional blood tests over a wide range of blood hemoglobin values.

The team created a mobile health version of the analysis by using an approach known as spectral super-resolution spectroscopy. This technique uses software to virtually convert photos acquired with low-resolution systems such as a smartphone camera into high-resolution digital spectral signals. They selected the inner eyelid as a sensing site because microvasculature is easily visible there; it is easy to access and has relatively uniform redness. The inner eyelid is also not affected by skin color, which eliminates the need for any personal calibrations. The prediction errors for the smartphone technique were within 5% to 10% of those measured with clinical laboratory blood.

Young L. Kim, PhD, MSCI, an associate professor and senior author of the study said, “Our new mobile health approach paves the way for bedside or remote testing of blood hemoglobin levels for detecting anemia, acute kidney injury and hemorrhages, or for assessing blood disorders such as sickle cell anemia.” The study was published on May 21, 2020 issue of the journal Optica.

Related Links:
Purdue University
Moi University Teaching and Referral Hospital