mHealth spectroscopy for noninvasive blood hemoglobin assessments

Sang Mok Park; Michelle A. Visbal-Onufrak; Md Munirul Haque; Martin C. Were; Violet Naanyu; Md Kamrul Hasan; Young L. Kim

doi:10.1117/12.2578640

5 March 2021 mHealth spectroscopy for noninvasive blood hemoglobin assessments

Sang Mok Park, Michelle A. Visbal-Onufrak, Md Munirul Haque, Martin C. Were, Violet Naanyu, Md Kamrul Hasan, Young L. Kim

Author Affiliations +

Proceedings Volume 11632, Optics and Biophotonics in Low-Resource Settings VII; 116320L (2021) https://doi.org/10.1117/12.2578640
Event: SPIE BiOS, 2021, Online Only

Abstract

In developing countries, anemia is a major public health problem; anemia affects 24.8% of the global population, corresponding to 1.62 billion people. As anemia is defined as a low hemoglobin level in the blood, it is important to measure exact hemoglobin content in grams per deciliter of the blood. Recent advances in mobile health (mHealth) technologies for blood hemoglobin levels are promising, but often rely on additional complex components to the smartphone and require blood sampling. As a result, noninvasive quantification of hemoglobin content in the blood is still limited. We have recently developed intravital mHealth spectroscopy to extract spectrally encoded microvascular and blood information from peripheral tissue. Spectral learning virtually transforms the built-in camera of a smartphone into a hyperspectral imager for spectroscopic analyses. Owing to the easy accessibility and relatively uniform microvasculature, the inner eyelid is used as a sensing site. Spectroscopic analyses of spectra acquired from the inner eyelid further result in key parameters about the blood and the microvasculature that are used for predicting blood hemoglobin levels in a noninvasive and real-time manner. Our clinical study conducted in sub-Saharan Africa supports reliable performance of blood hemoglobin quantification and anemia prediction. As our mHealth technology requires no additional attachment (our data-centric approach minimizes hardware complexity), the key features include mobility, simplicity, and affordability for rapid and scalable adaptation. Successful implementation with local governments and community healthcare workers can potentially provide unreached and underserved remote populations with accessible and affordable healthcare services in low-resource settings.

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Sang Mok Park, Michelle A. Visbal-Onufrak, Md Munirul Haque, Martin C. Were, Violet Naanyu, Md Kamrul Hasan, and Young L. Kim "mHealth spectroscopy for noninvasive blood hemoglobin assessments", Proc. SPIE 11632, Optics and Biophotonics in Low-Resource Settings VII, 116320L (5 March 2021); https://doi.org/10.1117/12.2578640

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