SleepPPG-Net: a deep learning algorithm for robust sleep staging from
continuous photoplethysmography

SleepPPG-Net: a deep learning algorithm for robust sleep staging from continuous photoplethysmography

11 February 2022

Peter H. Charlton

Joachim A. Behar

Papers citing "SleepPPG-Net: a deep learning algorithm for robust sleep staging from continuous photoplethysmography"

10 / 10 papers shown

Title
wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological Signals Jonathan Carter Lionel Tarassenko MLAU 45 0 0 07 Nov 2024
SleepNetZero: Zero-Burden Zero-Shot Reliable Sleep Staging With Neural Networks Based on Ballistocardiograms Shuzhen Li Yuxin Chen Xuesong Chen Ruiyang Gao Yupeng Zhang ... Ziyi Ye Weijun Huang Hongliang Yi Yue Leng Yi Wu 30 0 0 30 Oct 2024
Optimizing Photoplethysmography-Based Sleep Staging Models by Leveraging Temporal Context for Wearable Devices Applications Joseph A. P. Quino D. Cárdenas Marcelo A. F. Toledo F. M. Dias Estela Ribeiro J. Krieger Marco A. Gutierrez 27 0 0 01 Oct 2024
SleepPPG-Net2: Deep learning generalization for sleep staging from photoplethysmography Shirel Attia Revital Shani Hershkovich Alissa Tabakhov Angeleene Ang Sharon Haimov Riva Tauman Joachim A. Behar 37 2 0 10 Apr 2024
SleepVST: Sleep Staging from Near-Infrared Video Signals using Pre-Trained Transformers Jonathan Carter João Jorge O. Gibson Lionel Tarassenko 29 2 0 04 Apr 2024
A Review of Deep Learning Methods for Photoplethysmography Data Guangkun Nie Jiabao Zhu Gongzheng Tang Deyun Zhang Shijia Geng Qinghao Zhao Shenda Hong 30 6 0 23 Jan 2024
RawECGNet: Deep Learning Generalization for Atrial Fibrillation Detection from the Raw ECG N. Ben-Moshe K. Tsutsui Shany Biton Brimer L. Sörnmo Joachim A. Behar 30 6 0 26 Dec 2023
Generalization in medical AI: a perspective on developing scalable models Joachim A. Behar Jeremy Levy Leo Anthony Celi OOD 27 6 0 09 Nov 2023
A machine-learning sleep-wake classification model using a reduced number of features derived from photoplethysmography and activity signals Douglas A. Almeida F. M. Dias Marcelo A. F. Toledo D. Cárdenas Filipe A. C. Oliveira Estela Ribeiro J. Krieger Marco A. Gutierrez 9 0 0 07 Aug 2023
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 279 9,136 0 06 Jun 2015