Machine learning techniques for detecting electrode misplacement and interchanges when recording ECGs: A systematic review and meta-analysis.

Journal: Journal of electrocardiology
Published Date: Aug 19, 2020

Abstract

INTRODUCTION: Electrode misplacement and interchange errors are known problems when recording the 12‑lead electrocardiogram (ECG). Automatic detection of these errors could play an important role for improving clinical decision making and outcomes in cardiac care. The objectives of this systematic review and meta-analysis is to 1) study the impact of electrode misplacement on ECG signals and ECG interpretation, 2) to determine the most challenging electrode misplacements to detect using machine learning (ML), 3) to analyse the ML performance of algorithms that detect electrode misplacement or interchange according to sensitivity and specificity and 4) to identify the most commonly used ML technique for detecting electrode misplacement/interchange. This review analysed the current literature regarding electrode misplacement/interchange recognition accuracy using machine learning techniques.

Authors

  • Khaled Rjoob
    Faculty of Computing, Engineering & Built Environment, Ulster University, UK. Electronic address: rjoob-k@ulster.ac.uk.
  • Raymond Bond
    Ulster University, School of Computing, York St, Northern Ireland.
  • Dewar Finlay
    Nanotechnology and Integrated Bioengineering Centre, Ulster University, Jordanstown, Northern Ireland, United Kingdom.
  • Victoria McGilligan
    Faculty of Life & Health Sciences, Centre for Personalised Medicine, Ulster University, UK.
  • Stephen J Leslie
    Department of Diabetes & Cardiovascular Science, University of the Highlands and Islands, Centre for Health Science, Inverness, UK.
  • Ali Rababah
    Faculty of Computing, Engineering & Built Environment, Ulster University, UK.
  • Daniel Guldenring
    HTW Berlin, Wilhelminenhofstr. 75A, 12459 Berlin, Germany.
  • Aleeha Iftikhar
    Faculty of Computing, Engineering & Built Environment, Ulster University, UK.
  • Charles Knoery
    Department of Diabetes & Cardiovascular Science, University of the Highlands and Islands, Centre for Health Science, Inverness, UK.
  • Anne McShane
    Emergency Department, Letterkenny University Hospital, Donegal, Ireland.
  • Aaron Peace
    Western Health and Social Care Trust, C-TRIC, Ulster University, UK.

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