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Electroencephalogram Based Detection of Deep Sedation in ICU Patients Using Atomic Decomposition.

, , , , , , , , and . IEEE Trans. Biomed. Engineering, 65 (12): 2684-2691 (2018)

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Personalized Sedation Level Monitoring in ICU Patients Using Heart Rate Variability., , , , and . CinC, www.cinc.org, (2016)Clustering analysis to identify distinct spectral components of encephalogram burst suppression in critically ill patients., , , , , , , , and . EMBC, page 7258-7261. IEEE, (2015)Effect of Haptic Force Feedback on Upper Limb., and . ICETET, page 55-58. IEEE Computer Society, (2009)Electroencephalogram Based Detection of Deep Sedation in ICU Patients Using Atomic Decomposition., , , , , , , , and . IEEE Trans. Biomed. Engineering, 65 (12): 2684-2691 (2018)Brain Monitoring of Sedation in the Intensive Care Unit Using a Recurrent Neural Network., , , , and . EMBC, page 1-4. IEEE, (2018)A novel dictionary for neonatal EEG seizure detection using atomic decomposition., , , , and . EMBC, page 1073-1076. IEEE, (2012)Predicting Ordinal Level of Sedation from the Spectrogram of Electroencephalography., , and . CW, page 292-295. IEEE, (2018)Robustness of time frequency distribution based features for automated neonatal EEG seizure detection., , , , and . EMBC, page 2829-2832. IEEE, (2014)Neonatal Seizure Detection Using Atomic Decomposition With a Novel Dictionary., , , , and . IEEE Trans. Biomed. Engineering, 61 (11): 2724-2732 (2014)Heart rate variability as a biomarker for sedation depth estimation in ICU patients., , , , , , , , and . EMBC, page 6397-6400. IEEE, (2016)