Covid19 tracking algorithm and conceptualization of an associated patient monitoring system

S. Varun, R. Nagaraj
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引用次数: 1

Abstract

The outburst of corona virus called SARS-COV-2 saw a sudden surge in active cases all over the world. Kalman filter with its tremendous prediction capability achieves the actual value within limited iteration so that any locality can be aware of the increase in the status of the infected patients. This paper proposes the estimation algorithm for tracking covid19 patients in locality using kalman filter. The vitals acquired from these patients through sensors can be transmitted to the doctor through internet for further monitoring thereby decreasing the fatality rate including post covid19 patients. Kalman filtering along with monitoring system can bring wonders in medical field thus decreasing the risk of sudden heart attack, variation in blood pressure, blood sugar fluctuations in patients located in remote locations.
covid - 19跟踪算法和相关患者监测系统的概念化
冠状病毒SARS-COV-2爆发后,世界各地的活跃病例突然激增。卡尔曼滤波器以其强大的预测能力,在有限的迭代中得到实际值,从而使任何一个局部都能意识到感染患者状态的增加。本文提出了一种基于卡尔曼滤波的局部跟踪covid - 19患者的估计算法。通过传感器从这些患者身上获取的生命体征可以通过互联网传输给医生进行进一步监测,从而降低包括covid - 19后患者在内的死亡率。卡尔曼滤波配合监测系统,可以降低偏远地区患者突发心脏病、血压变化、血糖波动的风险,在医疗领域创造奇迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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