№ files_lp_3_process_7_058713
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Research article presenting the application of phase-rectified signal averaging to detect quasi-periodicities in electroencephalogram signals for assessing depth of anesthesia, with comparative evaluation against established nonlinear EEG indices in surgical patients.
Authors: Quan Liu; Yi-Feng Chen; Shou-Zen Fan; Maysam F. Abbod; Jiann-Shing Shieh
Type of document: Research article
Field: Biomedical engineering; Clinical anesthesia monitoring
Subject: Depth of anesthesia assessment using EEG analysis
Methodology: Phase-rectified signal averaging applied to electroencephalogram signals
Comparison methods: Sample entropy; Detrended fluctuation analysis; Permutation entropy
Evaluation metrics: Area under the receiver operating characteristic curve; Pearson correlation coefficient
Sample size: 56 surgical patients
Clinical context: General anesthesia during surgery
Keywords: Depth of anesthesia; Electroencephalogram; Phase-rectified signal averaging; Quasi-periodicities; Acceleration capacity; Deceleration capacity; Bispectral index; Expert assessment of conscious level
Price: 8 / 10 USD
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1.3 GHz Phase Averaging Reference Line for NML
Year: 2000
Region / City: Fermilab
Subject: Accelerator physics, RF signal distribution
Document type: Research paper
Organization: Fermilab
Author: Brian Chase, Ed Cullerton
Target audience: Researchers in accelerator physics
Period of validity: N/A
Approval date: N/A
Date of changes: N/A
Bayesian Model Averaging for Structural Equation Modeling
Year: 2015
Region / City: N/A
Subject: Bayesian Model Averaging, Structural Equation Modeling
Document Type: Package Documentation
Organization / Institution: N/A
Author: Chansoon Lee, David Kaplan
Target Audience: Researchers, Data Scientists, Statisticians
Validity Period: N/A
Approval Date: N/A
Date of Changes: N/A
URL: http://bise.wceruw.org/publications.html
References: Kaplan, D., Lee, C. (2015). Bayesian Model Averaging Over Directed Acyclic Graphs With Implications for the Predictive Performance of Structural Equation Models. Structural Equation Modeling.
Description: Bayesian Model Averaging (BMA) applied to Structural Equation Modeling, expanding upon previous work by Madigan et al. and Raftery et al. with a focus on directed acyclic graphs.
Topics: Quasi-Periodicities Phase-Rectified Averaging