Fig. 2: Transfer learning.
From: A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
The source model (ECG model) is trained using ECG data and PSG based labels scored according to the R&K rules (Siesta data set in this work) and then its knowledge is transferred to learn a new task, involving PPG input data and PSG annotation according to the AASM rules (Eindhoven data set in this work), resulting in the PPG model.
