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.
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Authors are grateful to “BIT Mesra, Ranchi, India” for providing the logistical support to conduct this research activity. Special thanks to all the volunteers participated in this research.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the “Ethical Committee, BIT Mesra” and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.
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Mukherjee, R., Ghorai, S.K., Gupta, B. et al. Development of a Wearable Remote Cardiac Health Monitoring with Alerting System. Instrum Exp Tech 63, 273–283 (2020). https://doi.org/10.1134/S002044122002013X
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DOI: https://doi.org/10.1134/S002044122002013X