Pretty impressive.

From the Figure in on page 2 https://arxiv.org/pdf/1707.01836.pdf#page=2

> Figure 2. Deep Neural Network architecture. Our deep neural network consisted of 33 convolutional layers followed by a linear output layer into a softmax. The network accepts raw ECG data as input (sampled at 200 Hz, or 200 samples per second), and outputs a prediction of one out of 12 possible rhythm classes every 256 input samples. The first and last layer are special-cased due to the pre-activation residual blocks.

^^^ 33 convolutional layers --- wow that's pretty deep for 1-D input.