Benjamin

Bianchi

Cover

David J. McEneaney

Escalona

Gilberto I. Perpiñan

Hingorani

Jekovaa

Kelly

Krahn

Lynn

Mann

Omar J. Escalona

Pedro R. Vizcaya

Peng

Porée

Roth

Stark

Tsouri

Walpole

Zhang

Zimetbaum

English

In this study, the feasibility of interpreting heart rhythms from far-field bipolar ECG arm-band lead recordings on the left-upper-arm (LUA), is evaluated in a clinical multichannel arm-ECG mapping database (N = 153 subjects) for the prospective development of long-term heart rhythm monitoring from comfortable arm wearable devices. A preliminary multivariable linear regression analysis on ECG chest Lead I from 10 selected far-field bipolar leads along the left arm, indicated that 3 of them in the LUA were relevant and worth evaluating in more detail from a heart rhythm information perspective.  To derive a good and effective estimation process, a time series non-linear regression point estimator, using an artificial neural network with 2 lags was investigated, showing a correlation coefficient of up to 0.969 for a single subject. Then, a vector approach was adopted for the whole LUA database, aiming to develop a subject independent estimation process of the P-QRS-T waveform interval and its heart rhythm attributes in the standard chest Lead I. In the same study, the first 96 coefficients, of the Discrete Cosine Transform on the P-QRS-T interval were used as a means for reducing the dimensionality of the input space, with a loss of just 0.1% in power, and reducing the dimensionality to just 5% of the original size. The trained ANN for ECG Lead I estimation from one upper arm Lead-1 showed a correlation coefficient above 80% on a beat-to-beat basis, an improvement on all but 1.34% of the beats estimated for a typical train/test partition of the LUA database. The non-triviality of the results was tested with random and intentional true negatives. Information theory analytics revealed that there is an estimated information of 1.6 bits/beat between LUA armband bipolar leads and the standard Lead I

Vizcaya, Pedro

Perpiñan, Gilberto

McEneaney, David

Escalona, OJ

Ulster University's Research Portal

Standard ECG Lead I Prospective Estimation Study from Far-field Bipolar Leads on the Left Upper Arm: A Neural Network Approach

Crossref

Standard ECG lead I prospective estimation study from far-field bipolar leads on the left upper arm: A neural network approach

https://pure.ulster.ac.uk/ws/files/75961462/BSPC_Open_Access_paper_Pedro_et_al._date_published_4Mar_2019.pdf

Standard ECG Lead I Prospective Estimation Study from Far-field Bipolar Leads on the Left Upper Arm: A Neural Network Approach

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Ulster University's Research Portal

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