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Blood leakage detection during dialysis therapy based on fog computing with array photocell sensors and heteroassociative memory model

机译:基于阵列光电管传感器雾计算和异缔合记忆模型的透析治疗中血液泄漏检测

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摘要

Blood leakage and blood loss are serious life-threatening complications occurring during dialysis therapy. These events have been of concerns to both healthcare givers and patients. More than 40% of adult blood volume can be lost in just a few minutes, resulting in morbidities and mortality. The authors intend to propose the design of a warning tool for the detection of blood leakage/blood loss during dialysis therapy based on fog computing with an array of photocell sensors and heteroassociative memory (HAM) model. Photocell sensors are arranged in an array on a flexible substrate to detect blood leakage via the resistance changes with illumination in the visible spectrum of 500–700 nm. The HAM model is implemented to design a virtual alarm unit using electricity changes in an embedded system. The proposed warning tool can indicate the risk level in both end-sensing units and remote monitor devices via a wireless network and fog/cloud computing. The animal experimental results (pig blood) will demonstrate the feasibility.
机译:血液渗漏和失血是透析治疗期间严重的威胁生命的并发症。这些事件已引起医疗保健提供者和患者的关注。在短短几分钟内,超过40%的成人血量就会流失,从而导致发病率和死亡率。作者打算提出一种预警工具的设计,该工具可用于基于烟雾计算的光疗传感器和异质联想记忆(HAM)模型,用于检测透析治疗过程中的漏血/失血。光电池传感器以阵列形式布置在柔性基板上,以通过在500-700 nm可见光谱中的照明强度变化来检测血液泄漏。实施HAM模型以利用嵌入式系统中的电力变化设计虚拟警报单元。所提出的警告工具可以通过无线网络和雾/云计算来指示终端感测单元和远程监控设备中的风险级别。动物实验结果(猪血)将证明其可行性。

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