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

机译:评估血红蛋白的非侵入性方法,用于分析手掌中的血流

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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%.
机译:血红蛋白的估计对于诊断贫血是重要的,这是在发展中国家和其他发达国家的严重公共卫生问题。通常存在于红细胞内的血红蛋白是负责着色血红色的化合物。因此血液和皮肤的发红,是血液中血红蛋白浓度的量度。我们利用棕榈的发红来估计血红蛋白的非侵入性。我们提出了一种基于机器视觉的便携式,用户友好,非侵入性和具有成本效益的方法来测量血红蛋白利用棕榈皮肤的发红量度。在使用前臂靠近手腕的前臂靠近手掌,在血流限制在手掌之前和之后,相机捕获人类主体的掌握的视频。视频持续到腹部压力突然和快速释放后血流释放。测量梳理后的肤色的发红和血流恢复掌握后,我们提出了一种基于回归的分类器来预测血液的血红蛋白含量。通过人类学科研究,我们表明我们的方法可以估算血红蛋白内容的准确性为91 \%。

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