The Experts below are selected from a list of 9729 Experts worldwide ranked by ideXlab platform
Maxime Cannesson - One of the best experts on this subject based on the ideXlab platform.
-
machine learning algorithm to predict hypotension based on high fidelity arterial pressure Waveform Analysis
Anesthesiology, 2018Co-Authors: Feras Hatib, Zhongping Jian, Sai Buddi, J J Settels, Karen Sibert, Joseph Rinehart, Maxime CannessonAbstract:Editor’s PerspectiveWhat We Already Know about This TopicThe ability to predict intraoperative hypotension may advance the ability to prevent hypotension-associated complications effectivelyThe extent to which advanced Waveform Analysis of invasive arterial lines may provide meaningful forewarning r
President - One of the best experts on this subject based on the ideXlab platform.
-
An Introduction to Time Waveform Analysis
1999Co-Authors: Timothy A Dunton, PresidentAbstract:In recent years there has been a resurgence in the use of time Waveform Analysis techniques. Condition monitoring personnel have now come to realize some of the limitations of the FFT process. Since many find the time Waveform Analysis process difficult and confusing the technique is rarely used to its full potential. The key to the successful utilization of time Waveform data is knowing when to use it. This paper examines the limitations of the FFT process and identifies specific applications where enhancing FFT information with time Waveform Analysis is appropriate. The paper also details in practical terms how to set up, acquire and manipulate time Waveform data. Having discussed the acquisition of the data the paper continues to discuss the interpretation of the data including the time-frequency relationship, symmetry, and pattern recognition of common faults.
Isis Amerwahlin - One of the best experts on this subject based on the ideXlab platform.
-
fetal electrocardiogram st Waveform Analysis in intrapartum surveillance
British Journal of Obstetrics and Gynaecology, 2007Co-Authors: Isis Amerwahlin, Sabaratnam Arulkumaran, Henrik Hagberg, Karel Marsal, Gerard H A VisserAbstract:ST Waveform Analysis of fetal electrocardiogram (ECG) for intrapartum surveillance (STAN) is a newly introduced method for fetal surveillance. The purpose of this commentary is to assist in the proper use of fetal ECG in combination with cardiotocography (CTG) during labour. Guidelines and recommendations concerning CTG and ST Waveform interpretation and classification are stated that were agreed on by the European experts on ST Waveform Analysis for intrapartum surveillance during a meeting in Utretcht, the Netherlands in January 2007.
-
fetal ecg Waveform Analysis
Best Practice & Research in Clinical Obstetrics & Gynaecology, 2004Co-Authors: K G Rosen, Isis Amerwahlin, R Luzietti, Hakan NorenAbstract:Fetal ECG Waveform Analysis as an adjunct to electronic fetal monitoring (EFM) has developed over the last 3 decades. From a multitude of potential parameters, ST Waveform Analysis has been documented to provide the information required to shift EFM from a screening device to a diagnostic tool that meets the standards of evidence-based medicine. This chapter details the experimental and clinical evolution of the STAN methodology for intrapartum fetal surveillance. Observational data formed the basis for cardiotocograph (CTG) and ST Waveform Analysis clinical guidelines. Data from two large, randomized controlled trials (6826 cases) are summarized together with the first Analysis of the recently completed EU project of 7823 term fetuses monitored as part of the study to introduce ST Analysis into clinical practice. The reduction in the incidence of newborns with marked neurological symptoms is supported by these findings. The detection of ST changes allowed earlier and more consistent intervention.
Yongqin Li - One of the best experts on this subject based on the ideXlab platform.
-
Prediction of Defibrillation Outcome by Ventricular Fibrillation Waveform Analysis: A Clinical Review
Journal of Clinical and Experimental Cardiology, 2013Co-Authors: Mi He, Bihua Chen, Yushun Gong, Kaifa Wang, Yongqin LiAbstract:The most frequent initial rhythm in out-of-hospital witnessed cardiac arrest is ventricular fibrillation (VF) and electrical defibrillation is still the only effective therapy for the termination of this life-threatening cardiac arrhythmia. Even though earlier defibrillation is greatly emphasized during cardiopulmonary resuscitation (CPR), unnecessary or repetitive high energy defibrillations are associated with decreased post-resuscitation myocardial function. Optimizing the timing of defibrillation is of great importance in order to discriminate patients should receive immediate defibrillation versus alternate therapies such as CPR. Since characteristics of VF Waveform changes over time and with CPR, which exhibit predictable ability of defibrillation success, quantitative Analysis of VF Waveform has the potential to guide defibrillation. This article reviewed methods developed for VF Waveform Analysis (including time domain, frequency domain, time-frequency domain, nonlinear Analysis, and combination Analysis techniques) and their performances for the prediction of defibrillation outcomes in clinical settings. The retrospective meta-Analysis confirmed that VF Waveform could predict the return of organized electrical activity, restoration of spontaneous circulation, and survival reliably. Additionally, predictors based on time-frequency and nonlinear methods were superior to other methods on the whole. However, no prospective studies have been performed to identify the optimal time of defibrillation utilizing VF Waveform Analysis until now. Therefore, the value of VF Waveform Analysis to guide clinical countershock management still needs further investigation.
-
Ventricular Fibrillation Waveform Analysis during Cardiopulmonary Resuscitation
Signa Vitae, 2010Co-Authors: Yongqin Li, Wanchun TangAbstract:Ventricular fibrillation (VF) is the primary rhythm associated with cardiac arrest characterized as rapid, disorganized contractions of the heart with complex electrocardiogram (ECG) patterns. Recent studies have reported that performing cardiopulmonary resuscitation (CPR) procedure prior to shock increases the survival rate especially especially when VF is untreated for more than 5 minutes. The Waveform Analysis is objective help in the choice of the right therapy (shock parameters, shock first or CPR first, drug administration). This Analysis is a precondition of individually optimized defibrillation and contribute substantially to an increased quality of CPR and reduce delivery of failed rescue shock. Animal and clinical studies confirmed that ventricular fibrillation Waveform Analysis contains information to reliably predict the countershock success rate and further improved countershock outcome prediction.
Martin Pfennigbauer - One of the best experts on this subject based on the ideXlab platform.
-
Echo Digitization and Waveform Analysis in Airborne and Terrestrial Laser Scanning
Signal Processing, 2011Co-Authors: Andreas Ullrich, Martin PfennigbauerAbstract:LIDAR technology based on time-of-flight ranging with short laser pulses enables the acquisition of accurate and dense 3D data in form of so-called point clouds. The technique is employed from different platforms like stable tripods in terrestrial laser scanning or aircrafts, cars, and ships in airborne and mobile laser scanning. Historically, these instruments used analogue signal detection and processing schemes with the exception of instruments dedicated for scientific research projects or bathymetry. In 2004, a laser scanner device for commercial applications and for mass data production, the RIEGL LMS-Q560, was introduced to the market, making use of a radical alternative approach: digitizing the echo signals received by the instrument for every laser pulse and analysing these echo signals off-line in a so-called full Waveform Analysis in order to retrieve almost all information contained in the echo signal using transparent algorithms adaptable to specific applications. In the field of laser scanning the somewhat unspecific term “full Waveform data” has since been established. We attempt a classification of the different types of the full Waveform data found in the market. We discuss the challenges in echo digitization and Waveform Analysis from an instrument manufacturer’s point of view. We will address the benefits to be gained by using this technique, especially with respect to the so-called multi-target capability of pulsed time-of-flight LIDAR instruments.
