Workshop: Causal Machine Learning for Real-World Impact

Identifying Causal Effects Of Exercise On Irregular Heart Rhythm Events Using Wearable Device Data

Lauren Hannah · Adam Bouyamourn


Wearable devices can passively monitor user health by tracking a set of metrics, including activity and heart rate. The Apple Watch introduced Irregular Rhythm Notifications (IRNs), which alert a user when the watch detects an arrhythmia over a sustained period that is highly suggestive of atrial fibrillation (AFib). Arrhythmias like AFib are often episodic, and episodes are suspected to have triggers like sleep changes, alcohol intake, or exercise. We study the proximal connection between Apple Exercise Minutes, a measure of moderate to strenuous exercise, and IRN events, using a causal observational study with data from the Apple Heart and Movement Study. We find that while increased exercise levels have a broadly protective effect, a large daily increase in exercise relative to a user's baseline increases the risk of an IRN on that day.

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