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Extending the Sana Mobile Healthcare Platform with Features Providing ECG Analysis

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Mobile Big Data

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 10))

Abstract

The great development of technology recently provides innovations that improve everyday life. The major benefit of it is that medicine is also affected, so better healthcare can be provided. In that context, it can be critical for patients who suffer from chronic heart diseases to have in their availability a system that can monitor and analyse their electrocardiogram (ECG) displaying either normal or abnormal findings. The current chapter describes such a system that uploads, stores, processes and displays an ECG, calculating certain ECG findings necessary for doctors to make a diagnosis. To this end, the SANA mobile healthcare platform, with its OpenMRS open source enterprise electronic medical record system, has been chosen and extended in this work for storing, processing and displaying the ECG data. OpenMRS provides a user-friendly interface and a database for collecting medical big data. Analysis of ECG signals is leveraged by the Physionet toolkit. Physionet contains many ECG databases and the WFDB software for processing ECG signals. According to the scenario we have processed, an ECG is uploaded onto OpenMRS platform using a mobile device or any other Internet-enabled device and is stored in the database that OpenMRS uses. Then, ECG signal is filtered using a finite impulse response (FIR) filter to remove noise and using WFDB functions it is processed so certain intervals are determined. Finally, with the appropriate algorithms specific ECG findings are calculated. When the procedure completes, the results are stored into the database using SQL Queries. Using an HTML Form results and graphs are integrated into the OpenMRS website highlighting abnormal values with red color. Authorized users can have access to this information through any web browser.

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Author information

Authors and Affiliations

  1. Department of Informatics Engineering, Technological Educational Institute of Crete, Heraklion, Crete, Greece

    Katerina Tsampi, Spyros Panagiotakis, Elias Hatzakis, Georgia Atsali, Kostas Vassilakis, George Mastorakis & Athanasios Malamos

  2. Foundation for Research and Technology—Hellas, Institute of Computer Science, Heraklion, Crete, Greece

    Emmanouil Lakiotakis

  3. Department of Computer Science, University of Nicosia, Nicosia, Cyprus

    Constandinos X. Mavromoustakis

Authors
  1. Katerina Tsampi
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  2. Spyros Panagiotakis
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  3. Elias Hatzakis
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  4. Emmanouil Lakiotakis
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  5. Georgia Atsali
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  6. Kostas Vassilakis
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  7. George Mastorakis
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  8. Constandinos X. Mavromoustakis
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  9. Athanasios Malamos
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Corresponding author

Correspondence to Spyros Panagiotakis .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Nicosia, Nicosia, Cyprus

    Georgios Skourletopoulos

  2. Department of Business Administration, Technological Educational Institute Crete, Agios Nikolaos, Greece

    George Mastorakis

  3. Department of Computer Science, University of Nicosia, Nicosia, Cyprus

    Constandinos X. Mavromoustakis

  4. Department of Computer Science and Engineering, University Politehnica of Bucharest, Bucharest, Romania

    Ciprian Dobre

  5. Department of Informatics Engineering, Technological Educational Institute of Crete, Crete, Greece

    Evangelos Pallis

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Tsampi, K. et al. (2018). Extending the Sana Mobile Healthcare Platform with Features Providing ECG Analysis. In: Skourletopoulos, G., Mastorakis, G., Mavromoustakis, C., Dobre, C., Pallis, E. (eds) Mobile Big Data. Lecture Notes on Data Engineering and Communications Technologies, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-67925-9_12

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  • DOI: https://doi.org/10.1007/978-3-319-67925-9_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67924-2

  • Online ISBN: 978-3-319-67925-9

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