PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 21, 2026Physiological Measurement0 citationsOpen Access

Towards real-time sleep stage classification: A deep learning approach leveraging PPG and ECG

View Full Paper
SDShagen DjanianTNThomas Dyhre NielsenSNSøren H. Nielsen

Key Points

  • The aim is to develop a model for classifying sleep stages using PPG and ECG data.
  • Utilized minimally processed PPG sensor data
  • Employed deep learning algorithms for classification
  • Focused on real-time processing and application
  • Achieved effective classification of sleep stages
  • Enhanced potential for adaptive CSTs using wearable sensors

Abstract

This work contributes to sleep health by developing a sleep stage classification model for minimally processed PPG sensor data and takes a step further towards making adaptive CSTs feasible for use with wearable sensors.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Djanian et al. (2026) studied this question.

synapsesocial.com/papers/69be38596e48c4981c678a78https://doi.org/10.1088/1361-6579/ae5458
Ask AI
Helpful
Bookmark
Share
View Full Paper