# Anomaly detection for time series data with only positive samples?

I'm having a time series ECG dataset. I want to do anomaly detection (anything different from normal ECG should be abnormal).

The point is I'm having only positive samples with very few negative samples.

How to model this problem ? Is it possible to model this as probability distribution and whenever some negative samples comes just taking the divergence from positive distribution ?