Abstract

Remote monitoring with alerting systems becomes unavoidable in the field of remote healthcare. The efficiency of such a system depends on accuracy, easy-to-use, versatility, and cost-effectiveness. In this study, a remote cardiac health monitoring along with the alert raising facility is presented. Special design techniques have been adopted to craft the photoplethysmography (PPG) sensor to overcome the congenital limitations like pressure disturbance, the influence of ambient light and motion artifacts. Three key components like pulse rate (PR), blood pressure (BP) and heart rate variability (HRV) are considered to monitor the cardiac health status. A novel algorithm has been developed to detect the cardiac health status of any subject from the above-mentioned physiological parameters. Also, the variation of human skin tone across demography is considered to minimize the impact of skin structure variability in PPG-based cardiac parameter measurement. Decentralized remote monitoring architecture is implemented using the virtual network computing (VNC) platform. We conducted a trial where the training dataset consisted of data from 70 volunteers and the trial dataset considered 20 new volunteers. The overall accuracy of cardiac health monitoring achieved is 98.5%. The experimental results demonstrate the good promise of reliable and efficient system architecture.

中文翻译：

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带有警报系统的可穿戴式远程心脏健康监测系统的开发

摘要

在远程医疗领域中，不可避免地需要使用警报系统进行远程监视。这种系统的效率取决于准确性，易用性，多功能性和成本效益。在这项研究中，提出了一种远程心脏健康监测以及预警设备。已采用特殊的设计技术来制作光电容积描记（PPG）传感器，以克服先天性局限性，例如压力干扰，环境光和运动伪影的影响。脉搏率（PR），血压（BP）和心率变异性（HRV）这三个关键成分被认为可以监测心脏健康状况。已经开发出一种新颖的算法来根据上述生理参数检测任何受试者的心脏健康状况。也，在基于PPG的心脏参数测量中，整个人口统计学中人类肤色的变化被认为可最大程度地减少皮肤结构变异性的影响。分散式远程监控架构是使用虚拟网络计算（VNC）平台实现的。我们进行了一项试验，其中训练数据集包含来自70名志愿者的数据，并且试验数据集考虑了20名新志愿者。心脏健康监测的总体准确性为98.5％。实验结果证明了可靠和高效的系统架构的良好前景。我们进行了一项试验，其中训练数据集包含来自70名志愿者的数据，并且试验数据集考虑了20名新志愿者。心脏健康监测的总体准确性为98.5％。实验结果证明了可靠和高效的系统架构的良好前景。我们进行了一项试验，其中训练数据集包含来自70名志愿者的数据，并且试验数据集考虑了20名新志愿者。心脏健康监测的总体准确性为98.5％。实验结果证明了可靠和高效的系统架构的良好前景。