Authors:
Utkars Jain
1
;
Adam A. Butchy
1
;
Michael T. Leasure
1
;
Veronica A. Covalesky
2
;
3
;
Daniel Mccormick
2
;
3
and
Gary S. Mintz
4
Affiliations:
1
Heart Input Output Inc., 128 N. Craig Street, Suite 406, Pittsburgh, U.S.A.
;
2
Cardiology Consultants of Philadelphia, Philadelphia, Pennsylvania, U.S.A.
;
3
Jefferson University Hospital, Philadelphia, Pennsylvania, U.S.A.
;
4
The Cardiovascular Research Foundation, New York, U.S.A.
Keyword(s):
ECG, Limited Lead Systems, ECG Synthesis, ECG Reconstruction.
Abstract:
The electrocardiogram (ECG) is the most widely used, non-invasive, cardiovascular test. There exist many lead variations including a one, three, six, and 12-lead device. In this work, we use ECGio, a validated deep learning model for the assessment of coronary artery disease, to reconstruct ECG signals with various combinations of leads, ranging from a single lead, to the full 12-leads. We are able to show 0.6536 R2, and 0.0747 mean absolute error (MAE) in the accurate reconstruction of a full 12-lead signal from just lead II. We go one step further and look at which individual leads, and in what combinations, yield the most accurate reconstructions as measured by R2 and MAE. As you would expect, the larger the quantity of leads included, the more accurate the reconstruction. Overall, the mean performance across all possible lead combinations is 0.8335 R2, and 0.0538 MAE. This work opens the door for seeing if ECGio can handle systematic noise injection and missing or misplaced leads.