Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021

The electrocardiogram (ECG) is a non-invasive representation of the electrical
activity of the heart. Although the twelve-lead ECG is the standard diagnostic
screening system for many cardiological issues, the limited accessibility of
twelve-lead ECG devices provides a rationale for smaller, lower-cost, and
easier to use devices. While single-lead ECGs are limiting, reduced-lead ECG
systems hold promise, with evidence that subsets of the standard twelve leads
can capture useful information and can even be comparable to twelve-lead ECGs
in some limited contexts. In 2017 we challenged the public to classify AF from
a single-lead ECG, and in 2020 we challenged the public to diagnose a much
larger number of cardiac problems using twelve-lead recordings. However, there
is limited evidence to demonstrate the utility of reduced-lead ECGs for
capturing a wide range of diagnostic information.

In this year's Challenge, we ask the following question: 'Will two do?' This
year's Challenge builds on last year's Challenge, which asked participants to
classify cardiac abnormalities from twelve-lead ECGs. We are asking you to
build an algorithm that can classify cardiac abnormalities from either twelve-
lead, six-lead, three-lead, and two-lead ECGs. We will test each algorithm on
databases of twelve-lead, six-lead, three-lead, and two-lead ECGs, and the
differences in performances of the algorithms on these databases will reveal
the utility of reduced-lead ECGs in comparison to standard twelve-lead EGCs.