Skip to main content
Erschienen in: Wireless Personal Communications 1/2018

01.06.2018

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

verfasst von: Sandeep K. Sood, Isha Mahajan

Erschienen in: Wireless Personal Communications | Ausgabe 1/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

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.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
4.
Zurück zum Zitat Shu, Z., Wan, J., Zhang, D., & Li, D. (2016). Cloud integrated cyber physical systems for complex industrial applications. Mobile Networks and Applications, 21(5), 865–878.CrossRef Shu, Z., Wan, J., Zhang, D., & Li, D. (2016). Cloud integrated cyber physical systems for complex industrial applications. Mobile Networks and Applications, 21(5), 865–878.CrossRef
5.
Zurück zum Zitat Muthukaruppan, S., & Er, M. J. (2012). A hybrid particle swarm optimization based fuzzy expert system for the diagnosis of coronary artery disease. Expert Systems with Applications, 39(14), 11657–11665.CrossRef Muthukaruppan, S., & Er, M. J. (2012). A hybrid particle swarm optimization based fuzzy expert system for the diagnosis of coronary artery disease. Expert Systems with Applications, 39(14), 11657–11665.CrossRef
6.
Zurück zum Zitat Yang, J. G., Kim, J. K., Kang, U. G., & Lee, Y. H. (2013). Coronary heart disease optimization system on adaptive-network-based fuzzy inference system and linear discriminant analysis (ANFISLDA). Personal and Ubiquitous Computing, 18(6), 1351–1362.CrossRef Yang, J. G., Kim, J. K., Kang, U. G., & Lee, Y. H. (2013). Coronary heart disease optimization system on adaptive-network-based fuzzy inference system and linear discriminant analysis (ANFISLDA). Personal and Ubiquitous Computing, 18(6), 1351–1362.CrossRef
7.
Zurück zum Zitat Pandey, S., Voorsluys, W., Niu, S., Khandoker, A., & Buyya, R. (2012). An autonomic cloud environment for hosting ECG data analysis services. Future Generation Computer Systems, 28(1), 147–154.CrossRef Pandey, S., Voorsluys, W., Niu, S., Khandoker, A., & Buyya, R. (2012). An autonomic cloud environment for hosting ECG data analysis services. Future Generation Computer Systems, 28(1), 147–154.CrossRef
8.
Zurück zum Zitat Xia, H., Asif, I., & Zhao, X. (2013). Cloud-ECG for real time ECG monitoring and analysis. Journal of Computer Methods and Programs in Medicine, 110(3), 253–259.CrossRef Xia, H., Asif, I., & Zhao, X. (2013). Cloud-ECG for real time ECG monitoring and analysis. Journal of Computer Methods and Programs in Medicine, 110(3), 253–259.CrossRef
9.
Zurück zum Zitat Lyu, Y., Hong, J., Wei, Y., Yang, J., Tang, Y., Wang, W., et al. (2015). Dynamic evaluation model of coronary heart disease for ubiquitous healthcare. Computers in Industry, 65(1), 35–44.CrossRef Lyu, Y., Hong, J., Wei, Y., Yang, J., Tang, Y., Wang, W., et al. (2015). Dynamic evaluation model of coronary heart disease for ubiquitous healthcare. Computers in Industry, 65(1), 35–44.CrossRef
11.
Zurück zum Zitat Shah, T., Yavari, A., Mitra, K., Saguna, S., Jayaraman, P. P., Rabhi, F., et al. (2016). Remote Healthcare cyber physical system: Quality of service challenges and opporunities. IET Cyber Physical Systems Theory and Applications, 2(1), 4048. Shah, T., Yavari, A., Mitra, K., Saguna, S., Jayaraman, P. P., Rabhi, F., et al. (2016). Remote Healthcare cyber physical system: Quality of service challenges and opporunities. IET Cyber Physical Systems Theory and Applications, 2(1), 4048.
12.
Zurück zum Zitat Mitchell, R., & Chen, I. R. (2015). Behavior rule specification based intrusion detection for safety critical medical cyber physical system. IEEE Transaction on Dependable and Secure Computing, 12(1), 16–30.CrossRef Mitchell, R., & Chen, I. R. (2015). Behavior rule specification based intrusion detection for safety critical medical cyber physical system. IEEE Transaction on Dependable and Secure Computing, 12(1), 16–30.CrossRef
14.
Zurück zum Zitat Prittopaul, P., Sathya, S., & Jayasree, K. (2015). Cyber physical system approach for heart attack detection and control using wireless monitoring and actuation system. In IEEE sponsored 9th international conference on intelligent systems and control. https://doi.org/10.1109/ISCO.2015.7282352. Prittopaul, P., Sathya, S., & Jayasree, K. (2015). Cyber physical system approach for heart attack detection and control using wireless monitoring and actuation system. In IEEE sponsored 9th international conference on intelligent systems and control. https://​doi.​org/​10.​1109/​ISCO.​2015.​7282352.
15.
Zurück zum Zitat Jang, J. S. R. (1993). ANFIS: Adaptive-network-based fuzzy inference system. IEEE Transaction on Systems, Man, and Cybernetics, 23(3), 665–684.CrossRef Jang, J. S. R. (1993). ANFIS: Adaptive-network-based fuzzy inference system. IEEE Transaction on Systems, Man, and Cybernetics, 23(3), 665–684.CrossRef
16.
Zurück zum Zitat Won, J. M., Park, S. Y., & Lee, J. S. (2002). Parameter conditions for monotonic takagisugenokang fuzzy system. Fuzzy Sets and Systems, 132(2), 135–146.MathSciNetCrossRefMATH Won, J. M., Park, S. Y., & Lee, J. S. (2002). Parameter conditions for monotonic takagisugenokang fuzzy system. Fuzzy Sets and Systems, 132(2), 135–146.MathSciNetCrossRefMATH
17.
Zurück zum Zitat Sun, Y., Li, J., Liu, J., Sun, B., & Chow, C. (2014). An improvement of symbolic aggregate approximation distance measure for time series. Neurocomputing, 138(6), 189–198.CrossRef Sun, Y., Li, J., Liu, J., Sun, B., & Chow, C. (2014). An improvement of symbolic aggregate approximation distance measure for time series. Neurocomputing, 138(6), 189–198.CrossRef
19.
Zurück zum Zitat Bystrov, D., & Westin, J.: Practice Neuro Fuzzy Logic Systems Matlab Toolbox GUI. ch, 2, 8–39. Bystrov, D., & Westin, J.: Practice Neuro Fuzzy Logic Systems Matlab Toolbox GUI. ch, 2, 8–39.
20.
Zurück zum Zitat Tutuncu, G. Y., & Kayaalp, N. (2015). An aggregated fuzzy naive bayes data classifier. Journal of Computational and Applied Mathematics, 286(1), 17–27.MathSciNetCrossRefMATH Tutuncu, G. Y., & Kayaalp, N. (2015). An aggregated fuzzy naive bayes data classifier. Journal of Computational and Applied Mathematics, 286(1), 17–27.MathSciNetCrossRefMATH
21.
Zurück zum Zitat Cheng, C. H., & Mon, D. L. (1993). Fuzzy system reliability analysis by interval of confidence. Fuzzy Sets and Systems, 56(1), 29–35.CrossRef Cheng, C. H., & Mon, D. L. (1993). Fuzzy system reliability analysis by interval of confidence. Fuzzy Sets and Systems, 56(1), 29–35.CrossRef
Metadaten
Titel
A Fog Assisted Cyber-Physical Framework for Identifying and Preventing Coronary Heart Disease
verfasst von
Sandeep K. Sood
Isha Mahajan
Publikationsdatum
01.06.2018
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2018
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-018-5680-y

Weitere Artikel der Ausgabe 1/2018

Wireless Personal Communications 1/2018 Zur Ausgabe

Neuer Inhalt