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Real-Time Analysis of ECG Data Using Mobile Data Stream Management System

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Database Systems for Advanced Applications (DASFAA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7239))

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Abstract

Monitoring and analyzing electrocardiogram(ECG) signals for the purpose of detecting cardiac arrhythmia is a challenging task, and often requires a Complex Event Processing (CEP) system to analyze real-time streamed data. Various server-based CEP engines exist today. However, they have practical limitations to be used in environments where network connectivity is poor and yet continuous real-time monitoring and analysis is critical. In this paper, we introduce a lightweight mobile-based CEP engine called Mobile Data Stream Management System (MDSMS) that runs on the smart phone. MDSMS is built on an extensible architecture with concepts such as lightweight scheduling and efficient tuple representation. MDSMS enables developers to easily incorporate domain specific functionalities with User Defined Operator (UDO) and User Defined Function (UDF). MDSMS also has other useful features, such as mechanisms for archiving streamed data in local or remote data stores. We also show effectiveness of our MDSMS by implementing a portable, continuous, and real-time cardiac arrhythmia detection system based on the MDSMS. The system consists of ECG sensor and a smart phone connected to each other via a wireless connection. MDSMS can detect and classify various arrhythmia conditions from ECG streams by executing arrhythmia detection algorithms written in Continuous Query Language.

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Author information

Authors and Affiliations

  1. Samsung Advanced Institute of Technology, South Korea

    Seokjin Hong, Rana Prasad Sahu, M. R. Srikanth, Supriya Mandal, Kyoung-Gu Woo & Il-Pyung Park

Authors
  1. Seokjin Hong
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  2. Rana Prasad Sahu
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  3. M. R. Srikanth
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  4. Supriya Mandal
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  5. Kyoung-Gu Woo
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  6. Il-Pyung Park
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Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, Seoul National University, Gwanak-ro, Gwanak-gu, 151747, Seoul, South Korea

    Sang-goo Lee

  2. Computer School, Wuhan University, Luo-jia-shan, Wuchang, 430081, Wuhan, Hubei Province, China

    Zhiyong Peng

  3. School of Information Technology and Electrical Engineering, University of Queensland, 4072, Brisbane, QLD, Australia

    Xiaofang Zhou

  4. Department of Computer Science, Kangwon National University, 192-1, Hyoja2-Dong, 200701, Chuncheon, Kangwon, South Korea

    Yang-Sae Moon

  5. Institute for Computer Science and Business Information, University of Duisburg-Essen, Schützenbahn 70, 45117, Essen, Germany

    Rainer Unland

  6. School of Information and Communication Engineering, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, 4072, Cheongju, Chungbuk, South Korea

    Jaesoo Yoo

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© 2012 Springer-Verlag Berlin Heidelberg

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Hong, S., Sahu, R.P., Srikanth, M.R., Mandal, S., Woo, KG., Park, IP. (2012). Real-Time Analysis of ECG Data Using Mobile Data Stream Management System. In: Lee, Sg., Peng, Z., Zhou, X., Moon, YS., Unland, R., Yoo, J. (eds) Database Systems for Advanced Applications. DASFAA 2012. Lecture Notes in Computer Science, vol 7239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29035-0_16

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  • DOI: https://doi.org/10.1007/978-3-642-29035-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29034-3

  • Online ISBN: 978-3-642-29035-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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