HemoSmart: A Non-invasive, Machine Learning Based Device and Mobile App for Anemia Detection

J. Jayakody, E. Edirisinghe
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引用次数: 6

Abstract

This paper presents a non-invasive method to detect Anemia (a low level of Hemoglobin) easily. The Hemoglobin concentration in human blood is an important substance to health condition determination. With the results which are obtained from Hemoglobin test, a condition which is called as Anemia can be revealed. Traditionally the Hemoglobin test is done using blood samples which are taken using needles. The non-invasive Hemoglobin measurement system, discussed in this paper, describes a better idea about the hemoglobin concentration in the human blood. The images of the finger- tip of the different hemoglobin level patients which are taken using a camera is used to develop the neural network-based algorithm. The pre-mentioned algorithm is used in the developed noninvasive device to display the Hemoglobin level. Before doing the above procedure, an account is created in the mobile app and a questionnaire is given to answer by the patient. Finally, both the results which are obtained from the mobile app and the device are run through a machine learning algorithm to get the final output. According to the result patient would be able to detect anemia at an early stage.
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HemoSmart:一种无创、基于机器学习的贫血检测设备和移动应用程序
本文介绍了一种无创检测贫血(低水平血红蛋白)的方法。人体血液中血红蛋白浓度是测定健康状况的重要指标。根据血红蛋白试验的结果,可以发现一种叫做贫血的情况。传统上,血红蛋白检测是用针头采集血液样本来完成的。本文讨论的无创血红蛋白测量系统,对人体血液中的血红蛋白浓度有了更好的了解。利用相机拍摄的不同血红蛋白水平患者的指尖图像,开发了基于神经网络的算法。上述算法被用于开发的非侵入性设备显示血红蛋白水平。在进行上述程序之前,在移动应用程序中创建一个帐户,并给出一份调查问卷供患者回答。最后,从移动应用程序和设备中获得的结果都通过机器学习算法进行运行,以获得最终输出。根据检测结果,患者可以在早期发现贫血。
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