Biomedical Signal Processing for Automated Detection of Sleep Arousals Based on Multi-Physiological Signals with Ensemble Learning Methods

Shani, Navabeh Sadat Jalili; Moradi, Mohammad H.

doi:10.1007/978-3-031-23239-8_11

Advances in Non-Invasive Biomedical Signal Sensing and Processing With Machine Learning 2023

DOI: 10.1007/978-3-031-23239-8_11

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Biomedical Signal Processing for Automated Detection of Sleep Arousals Based on Multi-Physiological Signals with Ensemble Learning Methods

Navabeh Sadat Jalili Shani

Mohammad H. Moradi

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2024

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Identification of full-night sleep parameters using morphological features of ECG signals: A practical alternative to EEG and EOG signals

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Tezel

et al. 2024

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Identification of full-night sleep parameters using morphological features of ECG signals: A practical alternative to EEG and EOG signals

Yücelbaş,

Tezel

et al. 2024

Biomedical Signal Processing and Control

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Biomedical Signal Processing for Automated Detection of Sleep Arousals Based on Multi-Physiological Signals with Ensemble Learning Methods

Cited by 1 publication

References 39 publications

Identification of full-night sleep parameters using morphological features of ECG signals: A practical alternative to EEG and EOG signals

Identification of full-night sleep parameters using morphological features of ECG signals: A practical alternative to EEG and EOG signals

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