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A Smart IoT Gateway Capable of Prescreening for Atrial Fibrillation

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Internet of Things (GIoTS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13533))

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Abstract

Atrial fibrillation (AF) is a cardiac arrhythmia occurring when the atria lose their normal rhythm causing the heart to beat erratically. The estimated number of individuals with atrial fibrillation globally in 2010 was 33.5 million. Despite continued research in this area there is no universal standard for detecting atrial fibrillation. The majority of published detectors rely on manual classification techniques that are implemented on standalone devices. This paper proposes a dual convolutional neural network (CNN) based AF detection system. The proposed system transforms 5 s windows of electrocardiogram data to two-dimensional images via a stationary wavelet transform to serve as CNN inputs. The dual CNN system implements a model tailored for an IoT gateway device to prescreen arrhythmia cases locally. Less obvious arrhythmia cases are transferred to a secondary model hosted on a cloud server for further prediction. Local classification of AF reduces the overheads for cloud storage capacity and transfer of data. The proposed runtime system ultimately received an F1 score of 0.94 when evaluated using previously unseen data.

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Authors and Affiliations

  1. FTI Consulting, The Academy, 42 Pearse Street, Dublin, Ireland

    Eoin Flanagan

  2. School of Electronic Engineering, Dublin City University, Dublin, Ireland

    Robert Sadleir

Authors
  1. Eoin Flanagan
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  2. Robert Sadleir
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Correspondence to Eoin Flanagan .

Editor information

Editors and Affiliations

  1. University of Murcia, Murcia, Spain

    Aurora González-Vidal

  2. Central Michigan University, Mount Pleasant, MI, USA

    Ahmed Mohamed Abdelgawad

  3. University of Quebec at Montreal, Montreal, QC, Canada

    Essaid Sabir

  4. IoT Forum, Mandat International, Geneva, Switzerland

    Sébastien Ziegler

  5. University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Latif Ladid

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Flanagan, E., Sadleir, R. (2022). A Smart IoT Gateway Capable of Prescreening for Atrial Fibrillation. In: González-Vidal, A., Mohamed Abdelgawad, A., Sabir, E., Ziegler, S., Ladid, L. (eds) Internet of Things. GIoTS 2022. Lecture Notes in Computer Science, vol 13533. Springer, Cham. https://doi.org/10.1007/978-3-031-20936-9_9

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  • DOI: https://doi.org/10.1007/978-3-031-20936-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20935-2

  • Online ISBN: 978-3-031-20936-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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