This demonstrates the viability of KD for performance improvement of single-channel ECG based sleep staging in 4-class(W-L-D-R) and 3-class(W-N-R) classification.
The multitasking network consists of a combination of Encoder-Decoder and Encoder-IncResNet, to fetch the average respiration rate and the respiration signal.
Furthermore, the model was also evaluated on three other databases.
Recently, a Machine Learning (ML) method was used to model reflectance waveforms onto SpO$_2$ obtained from transmittance waveforms.
However, these traditional methods require expert knowledge and are unable to model a wide range of arrhythmia.