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March 21, 2026Physiological Measurement0 citationsOpen Access

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

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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.

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Cite This Study

Djanian et al. (2026) studied this question.

synapsesocial.com/papers/69be38596e48c4981c678a78https://doi.org/10.1088/1361-6579/ae5458
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