Deep learning for automated sleep staging using instantaneous heart rate
Abstract Clinical sleep evaluations currently require multimodal data collection and manual review by human experts, making them expensive and unsuitable for longer term studies. Sleep staging using cardiac rhythm is an active area of research because it can be measured much more easily using a wide...
Main Authors: | Niranjan Sridhar, Ali Shoeb, Philip Stephens, Alaa Kharbouch, David Ben Shimol, Joshua Burkart, Atiyeh Ghoreyshi, Lance Myers |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2020-08-01
|
Series: | npj Digital Medicine |
Online Access: | https://doi.org/10.1038/s41746-020-0291-x |
Similar Items
-
Author Correction: Deep learning for automated sleep staging using instantaneous heart rate
by: Niranjan Sridhar, et al.
Published: (2020-10-01) -
Deep Recurrent Learning for Heart Sounds Segmentation based on Instantaneous Frequency Features
by: Alvaro Joaquin Gaona, et al.
Published: (2020-12-01) -
Deep learning for automated sleep monitoring
by: Tsinalis, Orestis
Published: (2016) -
Simultaneous identification and classification of oculomotor subsystems in isolation and in coordination
by: Ghoreyshi Langroudi, Atiyeh
Published: (2011) -
An algorithm for seizure onset detection using intracranial EEG
by: Kharbouch, Alaa, et al.
Published: (2015)