A non-invasive approach for estimation of hemoglobin analyzing blood flow in palm

Estimation of hemoglobin is important to diagnose anaemia which is a grave public health problem in developing and in other less developed countries. Hemoglobin, which normally is present within red blood cells, is the compound responsible for coloring blood red. Therefore redness of blood and consequently of skin, is a measure of hemoglobin concentration in blood. We utilize redness of palm to estimate hemoglobin non-invasively. We propose a machine vision based portable, user-friendly, non-invasive and cost effective approach to measure hemoglobin exploiting the redness measure of skin of palm. A camera captures the video of a palm of a human subject before and after the blood flow is restricted to the palm using a sphygmomanometer cuff in forearm close to the wrist. The video continues till the blood flow is released after sudden and rapid release of pressure in cuff. Measuring the redness of skin color after occlusion and after resumption of blood flow to palm, we propose a regression based classifier to predict the hemoglobin content of the blood. Through a human subject study, we show that our approach can estimate hemoglobin content up to an accuracy of 91%.