Wearable Technology: Signal Recovery of Electrocardiogram from Short Spaced Leads in the Far-Field Using Discrete Wavelet Transform Based Techniques

Niamh McCallan, Dewar Finlay, Pardis Biglarbeigi, Gilberto Perpiñan, Michael Jennings, Kok Yew Ng, James McLaughlin, Omar Escalona

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    3 Citations (Scopus)

    Abstract

    Bipolar ECG leads recorded from closely spaced electrodes are challenging in any context. When they are positioned distally with respect to the source field (far-field), the recovery of clinically useful signal content represents an even greater challenge. Due to the increased interest in ambulatory wellness devices, particularly wrist-worn devices, there is a renewed interest in recovering ECG signals from distally located bipolar leads.In this study 10 bipolar leads were simultaneously recorded at various locations along the left arm. At the same time, a conventional proximal reading on the chest using Lead I was also recorded and stored. This process was repeated for 11 healthy subjects. ECGs were recorded for a period of approximately 6 minutes for each subject and sampled at a frequency of 2048 Hz. Wavelet-based filtering using Daubechies 4 wavelet decomposition and soft threshold was applied to each lead. QRS detection performance was assessed against Lead I for each subject. This investigation found that a lead positioned transversally (using BIS gelled electrodes) on the upper arm provided the best accuracy against the benchmark QRS detection (SEN = 0.998, PPV = 0.984). The most distally positioned bipolar lead using dry electrodes faired least favourable (SEN = 0.272, PPV = 0.202).

    Original languageEnglish
    Title of host publication2019 Computing in Cardiology, CinC 2019
    PublisherIEEE Computer Society
    ISBN (Electronic)9781728169361
    DOIs
    Publication statusPublished (in print/issue) - Sept 2019
    Event2019 Computing in Cardiology, CinC 2019 - Singapore, Singapore
    Duration: 8 Sept 201911 Sept 2019

    Publication series

    NameComputing in Cardiology
    Volume2019-September
    ISSN (Print)2325-8861
    ISSN (Electronic)2325-887X

    Conference

    Conference2019 Computing in Cardiology, CinC 2019
    Country/TerritorySingapore
    CitySingapore
    Period8/09/1911/09/19

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