bioRxivSystems BiologyPreprint
A machine learning approach for automatic sleep staging using heart rate variability
Suvradeep ChakrabortyiD, Manish Kumar GoyaliD, Paritosh Goyal, Priyadarshini MishraiD
Abstract
This manuscript has been withdrawn by bioRxiv as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- EEG-Beats: Automated analysis of heart rate variability (HVR) from EEG-EKG
Supakjeera Thanapaisal, Sabrina Mosher, … Kay A. Robbins·bioRxiv·Jul 21, 2020
- Sleep as a random walk - A superstatistical analysis of EEG data across sleep stages
Claus Metzner, Achim Schilling, … Patrick Krauß·Communications BiologyPeer-reviewed·Dec 10, 2021
- Automatic sleep stage classification using physiological signals acquired by Dreem headband
S. Bakian Dogaheh, M. H. Moradi·bioRxiv·Oct 5, 2023
- Sleep Identification Enabled by Supervised Training Algorithms (SIESTA): An open-source platform for automatic sleep staging of rodent polysomnographic data
Carlos S. Caldart, Raymond E.A. Sanchez, … Horacio O. de la Iglesia·bioRxiv·Jul 6, 2020
- The potential of ensemble-based automated sleep staging on single-channel EEG signal from a wearable device
Federico Salfi, Domenico Corigliano, … M. Ferrara·Journal of Sleep ResearchPeer-reviewed·Jan 19, 2026
- Dynamics of peripheral blood flow across sleep stages