Electrocardiogram wave segmentation using machine learning

A method comprising:

• training a machine learning model using labeled electrocardiogram measurements,
• wherein the labeled electrocardiogram measurements comprise labeled segments,
• and wherein the labeled segments comprise a segment labeled as an artifact;
• classifying, using the machine learning model, a portion of an electrocardiogram measurement as an artifact, wherein the classifying the portion as the artifact comprises:
• classifying the portion as a pause indicating that a heart stopped,
• determining a probability that classifying the portion as the pause is correct, and
• classifying the portion as the artifact in response to determining that the probability does not meet a threshold;
• normalizing the electrocardiogram measurement except the portion of the electrocardiogram measurement classified as the artifact;
• and
• detecting a cardiac event from the normalized electrocardiogram measurement.