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Review on the Heart Disease Detection Using IoT Framework

Komal Saini1 , Sandeep Sharma2

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 669-674, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.669674

Online published on Mar 31, 2019

Copyright © Komal Saini , Sandeep Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Komal Saini , Sandeep Sharma, “Review on the Heart Disease Detection Using IoT Framework,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.669-674, 2019.

MLA Style Citation: Komal Saini , Sandeep Sharma "Review on the Heart Disease Detection Using IoT Framework." International Journal of Computer Sciences and Engineering 7.3 (2019): 669-674.

APA Style Citation: Komal Saini , Sandeep Sharma, (2019). Review on the Heart Disease Detection Using IoT Framework. International Journal of Computer Sciences and Engineering, 7(3), 669-674.

BibTex Style Citation:
@article{Saini_2019,
author = {Komal Saini , Sandeep Sharma},
title = {Review on the Heart Disease Detection Using IoT Framework},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {669-674},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3899},
doi = {https://doi.org/10.26438/ijcse/v7i3.669674}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.669674}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3899
TI - Review on the Heart Disease Detection Using IoT Framework
T2 - International Journal of Computer Sciences and Engineering
AU - Komal Saini , Sandeep Sharma
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 669-674
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

IOT is the trending technology which may affect the networking, communication and business. Among the various applications of Internet of Things, healthcare is one of the important one. Heart disease is the leading cause of death worldwide, therefore in order to reduce this there is a need for efficient heart disease detection system. Remote health monitoring system is emerging as an essential part in one’s life. Various wearable sensors either worn or attached to the body of the patients helps in the collection of various health metrics. These sensor devices generate the data at a very high speed and it is difficult to manage and store the huge amount of data. In this paper the review on an IOT framework is given for the prediction of the heart disease. The first part focuses on the acquisition of the data using various sensors, second part focus on the data storage using cloud technologies, and third part is about the analysis of the data using various machine learning algorithms.

Key-Words / Index Term

ZigBee, Bluetooth, Sensors, Cloud, Data mining, wearable devices

References

[1] M.U. Farooq, Muhammad Waseem, Sadia Mazhar, Anjum Khairi, Talha Kamal “A Review on Internet of things”, International Journal of Computer Applications, Vol. 113, No.1, pp.1-7 ,2015.
[2] Zeinab Kamal Aldein Mohammed, Elmustafa Sayed AliAhmed, “Internet of Things Applications, Challenges and Related Future Technologies”, World Scientific News, pp.126-148, 2017.
[3] Vandana Sharma, Ravi Tiwari, “A Review on “IOT” & It’s Smart Applications”, International Journal of Science, Engineering and Technology Research (IJSETR), Vol. 5, Issue.2, pp.472-476, 2016.
[4] Stephanie Baker , Wei Xiang, Ian Atkinson, “Internet of Things for Smart Healthcare: Technologies, Challenges and opportunities”, IEEE Access 2017.
[5] Juan Pablo Tello P., Oscar Manjarres, Mauricio Quijano, Arcelio Ulises Blanco, ”Remote Monitoring System of RCG and Temperature Signal using Bluetooth”, International Symponium on information technology and education, IEEE 2012
[6] R.N. Kirtana, Y.V. Lokeswari, “An IoT Based HRV Monitoring System for Hypertensive Patients ”, IEEE international conference on computer, communication, and signal processing, 2017
[7] Nair Siddharth, Shivakumar, M. Sasikala, “Design of Vital Sign Monitor based on Wireless Sensor Networks and Telemedicine technology”
[8] Abdulaziz Shehab, Ahmed Ismail, Lobna Osman, Mohamed Elhoseny and I.M. El-Henawy, “ Quantified Self Using IoT Wearable Devices”, Proceedings of the international conference on advanced intelligent systems and informatics, Springer International publishing, pp.820-831, 2018
[9] Zhe Yang, Qihao Zhou, lei Lei, Kan Zheng, Wei Xiang, “An IoT-cloud based Wearable ECG Monitoring System for Smart Healthcare”, Mobile and Wireless Health , Springer publications2016
[10] Moeen Hassanalieragh, Alex Page, et al, “Health Monitoring and Management using Internet of things (IoT) sensing with clpoud based processing: opportunities and challenges”, international conference on service somputing, IEEE, 2015.
[11] Chao Li, Xiangpei hu, Lili Zhang, “The IoT based heart disease monitoring system for pervasive healthcare service”, international conference on knowledge based and intelligent information and engineering systems, Elsevier publication 2017.
[12] Jihwan Lee, Jaehyo Jung, Youn Tae Kim, ”Design and development of mobile cardiac marker monitoring system for prevention of acute cardiovascular disease”, IEEE 2011.
[13] Priyan Malarvizhi Kumar, Usha Devi Gandhi, “A Novel three tier internet of things architecture with machine learning algorithm for early detection of heart disease ”, international journal of computer and electrical engineering, pp.1-14, 2017.
[14] Meherwar Fatima, Maruf Pasha, “Survey of machine learning algorithms for disease diagnostic”, journal of intelligent learning systems and applications, Vol.9, pp.1-16, 2017.
[15] Uma N Dulhare, “Prediction system for heart disease using Naïve Bayes and particle swarm optimization”, Biomedical research, Vol.29, issue.12, pp.2646-2649, 2018.
[16] Lalitha Kumari Gaddala, Dr. N. Naga Malleswara Rao, “An analysis of heart disease prediction using swarm intelligence algorithms”, International journal of innovations in engineering and technology, Vol.9, issue.3, pp.081-087, 2018.
[17] Sanjay Kumar Sen, “Predicting and diagnosis of heart disease using machine learning algorithms”, International journal of engineering and computer science, Vol.6, issue.6, pp.21623-21631, june 2017.
[18] Youness Khourdiffi, Mohamed Bahaj, “Heart disease prediction and classification using machine learning algorithms optimized by particle swarm optimization and ant colony optimization”, International journal of intelligent engineering and systems, Vol.12, no.1, pp.242-252, 2018.
[19] Hamza Turabieh, “Ahybrid ANN-GWO algorithm for prediction of heart disease”, American journal of operations research, vol.6, pp.136-146, 2016.
[20] Hlaudi Daniel Masethe, Mosima Anna Masethe, “Prediction of heart disease using classification algorithm”, Proceedings of the world congress on engineering and computer science, Vol.2, pp.22-24, 2014.