A smartphone, an app and a photo: how to detect anaemia in a non-invasive way

Source: Smartphone app for non-invasive detection of anemia using only patient

The magazine Nature Communications published a research by Robert G. Mannino, David R. Myers, Erika A. Tyburski, Christina Caruso, Jeanne Boudreaux, Traci Leong, G. D. Clifford and Wilbur A. Lama about the development of an app aimed to detect anaemia.

The application estimates hemoglobin levels by analyzing color and metadata of fingernail bed smartphone photos and detects anemia (hemoglobin levels <12.5 g dL−1) with an accuracy of ±2.4 g dL−1 and a sensitivity of 97% (95% CI, 89–100%) when compared with CBC hemoglobin levels (n = 100 subjects), indicating its viability to serve as a non-invasive anemia screening tool. Moreover, with personalized calibration, this system achieves an accuracy of ±0.92 g dL−1 of CBC hemoglobin levels (n = 16), empowering chronic anemia patients to serially monitor their hemoglobin levels instantaneously and remotely.

Let’s see how this system operates. A patient simply downloads the app onto his/her smartphone, opens the app, obtains a smartphone photo of his/her fingernail beds, and without the need for any blood sampling or additional smartphone attachments or external calibration tools, quantitatively measures blood Hgb levels.

The patient first takes an image of his fingernails, then is prompted by the app to tap on the screen to select the regions of interest corresponding to the nailbeds: the result is then displayed on the smartphone screen.

As smartphone images with fingernail irregularities such as camera flash reflections or leukonychia may affect Hgb level measurements, a quality control algorithm integrated within the Hgb level measurement app detects and omits those irregularities to preserve measurement integrity and accuracy.

Source: Smartphone app for non-invasive detection of anemia using only patient

In this example, when the quality control system was implemented to exclude the fingernail bed irregularities, Hgb level was measured to be 14.7 g dL−1, comparable to the patient’s CBC Hgb level of 15.3 g dL−1. Without the quality control algorithm, Hgb level was measured at 12.8 g dL−1, indicating that the algorithm resulted in a 76% reduction in error.

Due to anemia high prevalence affecting over 2 billion people globally, especially among babies, old people and pregnants, this completely non-invasive technology represents a valid screening tool, largely accessible to populations under this risk. The capacity to detect anemia with a high level of sensitiveness and without the need of external calibration equipment, represents a strong improvement in respect to the actual anemia screening realized through Point Of Care (POC) instruments.

Although the clinical equipment for anemia diagnosis have strict requirements of accuracy (95% LOA di ± 1,0 g/dL), these requisites are less strict for POC instruments employed for the anemia screening. The results obtained by researchers (95% LOA di ±2,4 g/dL) are comparable or better than the ones obtained by the available POC diagnostic instruments (95% LOA di 2,3 – 3,7 g/dL). Moreover, the application results, if individually measured, suggest that the technology can be ameliorated with additional studies, to reach the right accuracy in the haemoglobin measuring, as required for the anemia diagnosis.

If you want to examine in depth this argument, I suggest read the research, a very detailed study. The detection of biologic and hematic parameters in a non-invasive way is a very interesting area and is attiring great investments, engaging many experts either from the academia and hi-tech companies.

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