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Call for Paper - December – 2022 Edition   

(SJIF Impact Factor: 5.966) (IJIFACTOR 3.8, RANKING: A+) (PIF: 3.460)

IJATCA solicits original research papers for the December – 2022 Edition.
Last date of manuscript submission is December 30, 2022.

                                                   

Labview based Electrocardiograph (ECG) Patient Monitoring System For Cardiovascular Patient Using WSNs: A Critical Review


Volume: 4 Issue: 4
Year of Publication: 2017
Authors: Vibhav Kumar Sachan, Vijay Srivastava, Krati Varshney, Syed Akhtar Imam



Abstract

Wireless Sensor Network is suitable a significant allowing technology for a wide variety of applications. Recent advances in wireless sensor networks have allowed the realization of prevalent health monitoring for both homecare and hospital environments. Current technological advances in sensors, power-efficient integrated circuits, and wireless communication have allowed the development of miniature, lightweight, low-cost, and smart physiological sensor nodes. These nodes are capable of sensing, processing, and communicating one or more vital signs. Furthermore, they can be used in wireless personal area networks or wireless body sensor networks for health monitoring. Many studies were performed and/or are under way in order to develop flexible, reliable, secure, real-time, and power-efficient wireless body sensor networks suitable for healthcare applications. To efficiently control and monitor a patients status as well as to decrease the cost of power and maintenance, IEEE 802.15.4/ZigBee, a communication standard for low-power wireless communication, is developed as a new efficient technology in health monitoring systems. This paper describes the applications of wireless sensor networks in the healthcare area and discusses the related problems and challenges. The main goal of this review paper is to evaluate the acceptance of the current wireless standard for enabling wireless sensor networks for healthcare monitoring in real environment.

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Keywords

Cardiac arrhythmias, Electrocardiogram , Discrete Wavelet Transform, P-QRS-T Segment, NI Lab VIEW Biomedical Toolkit, Biomedical workbench, ECG, Electrocardiograph parameters ECG Feature Extraction.




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