Browsing by Author Fan, S-Z

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Showing results 1 to 11 of 11
Issue DateTitleAuthor(s)
2016Analyzing Heart Rate Variability Using a Photoplethysmographic Signal Measuring SystemChen, Y-F; Shieh, J-S; Fan, S-Z; Chiang, W-T; Abbod, MF; Liu, Q
2019Applying Time-Frequency Image of Convolutional Neural Network to Extract Feature on Long-Term EEG Signals to Predict Depth of AnesthesiaHuang, Y; Chen, J; Abbod, M; Fan, S-Z; Shieh, J-S; Kung, Y-C
2014A critical care monitoring system for depth of anaesthesia analysis based on entropy analysis and physiological information databaseWei, Q; Li, Y; Fan, S-Z; Liu, Q; Abbod, MF; Lu, C-W; Lin, T-Y; Jen, K-K; Wu, S-J; Shieh, J-S
2020Deep Convolutional Autoencoder Applied for Generative Continuous Arterial Blood Pressure via PhotoplethysmographySadrawi, M; Lin, Y-T; Lin, C-H; Mathunjwa, B; Fan, S-Z; Abbod, M; Shieh, J-S
2016EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgeryLiu, Q; Chen, Y-F; Fan, S-Z; Abbod, MF; Shieh, J-S
2017Electroencephalogram Similarity Analysis using Temporal and Spectral Dynamics Analysis for Propofol and Desflurane Induced UnconsciousnessLiu, Q; Ma, L; Fan, S-Z; Abbod, M; Shieh, J-S
2018Frontal EEG Temporal and Spectral Dynamics Similarity Analysis between Propofol and Desflurane Induced Anesthesia using Hilbert-Huang TransformLiu, Q; Ma, L; Fan, S-Z; Abbod, M; Ai, Q; Chen, K; Shieh, J-S
9-Jul-2020Genetic Deep Convolutional Autoencoder Applied for Generative Continuous Arterial Blood Pressure via PhotoplethysmographySadrawi, M; Lin, Y-T; Lin, C-H; Mathunjwa, B; Fan, S-Z; Abbod, MF; Shieh, J-S
2016Improved spectrum analysis in EEG for measure of depth of anesthesia based on phase-rectified signal averagingQuan, L; Chen, Y-F; Fan, S-Z; Abbod, M; Shieh, J-S
2017Quasi-Periodicities Detection Using Phase-Rectified Signal Averaging in EEG Signals as a Depth of Anesthesia MonitorLiu, Q; Chen, Y-F; Fan, S-Z; Abbod, M; Sheih, J-S
2019Spectrum analysis of EEG signals using CNN to model patient’s consciousness level based on anesthesiologists’ experienceLiu, Q; Cai, J; Fan, S-Z; Abbod, MF; Shieh, J-S; Kung, Y; Lin, L