Heart Disorder Detection with Menard Algorithm on Apache Spark

  • Lorenzo CarnevaleEmail author
  • Antonio Celesti
  • Maria Fazio
  • Placido Bramanti
  • Massimo Villari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10465)


Nowadays, healthcare is facing Big Data processing in order to support medical staff by means of decision making tools. In this context, a challenging topic is the storing and analysis of data in the cardiology field. Electrocardiogram produces signals about the heart health that need to be processed in order to detect a possible disorder. In this paper, we discuss an Apache Spark based tool and that uses the Menard algorithm. In order to validate our solution, we performed experiments on a use case in which the algorithm has been implemented in order to detect heart disorder. Experiments prove the goodness of our approach in terms of performance.


Big Data Healthcare Cardiology Heart ECG Arrhythmia 



This work has been supported by Cloud for Europe (C4E) Tender: REALIZATION OF A RESEARCH AND DEVELOPMENT PROJECT (PRE-COMMERCIAL PROCUREMENT) ON “CLOUD FOR EUROPE”, Italy-Rome: Research and development services and related consultancy services Contract notice: 2014/S 241-424518. Directive: 2004/18/EC ( Authors would like to thank Fabio Pandolfo for his valuable technical support in this scientific work.


  1. 1.
    Celesti, A., Celesti, F., Fazio, M., Bramanti, P., Villari, M.: Are next-generation sequencing tools ready for the cloud? Trends Biotechnol. 35(6), 486–489 (2017)CrossRefGoogle Scholar
  2. 2.
    Celesti, A., Maria, F., Romano, A., Bramanti, A., Bramanti, P., Villari, M.: An oais-based hospital information system on the cloud: analysis of a nosql column-oriented approach. IEEE J. Biomed. Health Inform. PP(99), 1 (2017)CrossRefGoogle Scholar
  3. 3.
    Ma’sum, M.A., Jatmiko, W., Suhartanto, H.: Enhanced tele ECG system using hadoop framework to deal with big data processing. In: 2016 International Workshop on Big Data and Information Security (IWBIS). IEEE, October 2016Google Scholar
  4. 4.
    Wang, Y., Wang, L., Chen, X., Zhu, W.: P wave detection and delineation based on distances transform. In: 2016 IEEE Trustcom/BigDataSE/ISPA. IEEE, August 2016Google Scholar
  5. 5.
    Carnevale, L., Celesti, A., Fazio, M., Bramanti, P., Villari, M.: How to enable clinical workflows to integrate big healthcare data. In: 2017 IEEE Symposium on Computers and Communications (ISCC) (ISCC 2017). Heraklion, Greece, July 2017Google Scholar
  6. 6.
    Alshraideh, H., Otoom, M., Al-Araida, A., Bawaneh, H., Bravo, J.: A web based cardiovascular disease detection system. J. Med. Syst. 39(10), 122 (2015)CrossRefGoogle Scholar
  7. 7.
    Menrad, A. (ed.): Dual microprocessor system for cardiovascular data acquisition, processing and recording. In: Inr. Con5 Industrial Elect. Contr. Instrument. IEEE (1981)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  • Lorenzo Carnevale
    • 1
    • 3
    Email author
  • Antonio Celesti
    • 2
  • Maria Fazio
    • 1
  • Placido Bramanti
    • 3
  • Massimo Villari
    • 1
    • 3
  1. 1.Department of EngineeringUniversity of MessinaMessinaItaly
  2. 2.Scientific Research Organisational UnitUniversity of MessinaMessinaItaly
  3. 3.IRCCS Centro Neurolesi “Bonino Pulejo”MessinaItaly

Personalised recommendations