A Fog Assisted Cyber-Physical Framework for Identifying and Preventing Coronary Heart Disease

A Fog Assisted Cyber-Physical Framework for Identifying and Preventing Coronary Heart Disease Coronary Heart Disease (CHD) is the most common cardiovascular disease which has the highest mortality rate in developing countries. To predict and prevent the risk of CHD in its early stages from remote sites, real time monitoring and analysis of an individual’s health statistics is required. Cloud based cyber-physical systems facilitate the alliance of devices in the physical world i.e. cameras, sensors and Geographical Positioning System devices with cyber world to generate the required information. Then it uses cyber world to analyze and share medical information along with localization data with healthcare service providers. Moreover, with the ability to transmit intensive information anytime and anywhere, this technological revolution has raised the level of effective healthcare deliverance. With these aspects, cloud based cyber-physical localization system is proposed to identify the risk level of CHD using adaptive neuro fuzzy inference system at an early stage. The users who are in the middle or high risk category will be monitored continuously to keep track of their electrocardiogram (ECG) readings. In case of any abnormality in ECG readings, an alert will be immediately sent to the user’s mobile phone as well as to the healthcare service providers or professionals to take immediate or necessary action on time for patient’s wellness. It also provides preventive measures and medication according to the risk category of the user. The experimental results reveal that the proposed system efficiently and effectively classifies the risk of CHD as well as utilizes minimum response time in generation of alerts on the basis of ECG readings. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

A Fog Assisted Cyber-Physical Framework for Identifying and Preventing Coronary Heart Disease

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks
ISSN
0929-6212
eISSN
1572-834X
D.O.I.
10.1007/s11277-018-5680-y
Publisher site
See Article on Publisher Site

Abstract

Coronary Heart Disease (CHD) is the most common cardiovascular disease which has the highest mortality rate in developing countries. To predict and prevent the risk of CHD in its early stages from remote sites, real time monitoring and analysis of an individual’s health statistics is required. Cloud based cyber-physical systems facilitate the alliance of devices in the physical world i.e. cameras, sensors and Geographical Positioning System devices with cyber world to generate the required information. Then it uses cyber world to analyze and share medical information along with localization data with healthcare service providers. Moreover, with the ability to transmit intensive information anytime and anywhere, this technological revolution has raised the level of effective healthcare deliverance. With these aspects, cloud based cyber-physical localization system is proposed to identify the risk level of CHD using adaptive neuro fuzzy inference system at an early stage. The users who are in the middle or high risk category will be monitored continuously to keep track of their electrocardiogram (ECG) readings. In case of any abnormality in ECG readings, an alert will be immediately sent to the user’s mobile phone as well as to the healthcare service providers or professionals to take immediate or necessary action on time for patient’s wellness. It also provides preventive measures and medication according to the risk category of the user. The experimental results reveal that the proposed system efficiently and effectively classifies the risk of CHD as well as utilizes minimum response time in generation of alerts on the basis of ECG readings.

Journal

Wireless Personal CommunicationsSpringer Journals

Published: Jun 1, 2018

References

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