scholarly journals V02-08 SIMPLE, REAL-TIME INTRAOPERATIVE INTRARENAL PRESSURE MONITORING: METHODS AND APPLICATIONS

2021 ◽  
Vol 206 (Supplement 3) ◽  
Author(s):  
Nabeel Shakir ◽  
Lee Zhao
Keyword(s):  
Real Time ◽  
Monitoring Methods ◽  
Pressure Monitoring ◽  
Intrarenal Pressure

scholarly journals GLM-Based Flexible Monitoring Methods: An Application to Real-Time Highway Safety Surveillance

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 362
Author(s):  
Arshad Jamal ◽  
Tahir Mahmood ◽  
Muhamad Riaz ◽  
Hassan M. Al-Ahmadi
Keyword(s):  
Real Time ◽  
Control Charts ◽  
Negative Binomial ◽  
Highway Safety ◽  
Monitoring Methods ◽  
Count Data Models ◽  
Crash Data ◽  
Safety Surveillance ◽  
Study Results ◽  
Best Fit

Statistical modeling of historical crash data can provide essential insights to safety managers for proactive highway safety management. While numerous studies have contributed to the advancement from the statistical methodological front, minimal research efforts have been dedicated to real-time monitoring of highway safety situations. This study advocates the use of statistical monitoring methods for real-time highway safety surveillance using three years of crash data for rural highways in Saudi Arabia. First, three well-known count data models (Poisson, negative binomial, and Conway–Maxwell–Poisson) are applied to identify the best fit model for the number of crashes. Conway–Maxwell–Poisson was identified as the best fit model, which was used to find the significant explanatory variables for the number of crashes. The results revealed that the road type and road surface conditions significantly contribute to the number of crashes. From the perspective of real-time highway safety monitoring, generalized linear model (GLM)-based exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are proposed using the randomized quantile residuals and deviance residuals of Conway–Maxwell (COM)–Poisson regression. A detailed simulation-based study is designed for predictive performance evaluation of the proposed control charts with existing counterparts (i.e., Shewhart charts) in terms of the run-length properties. The study results showed that the EWMA type control charts have better detection ability compared with the CUSUM type and Shewhart control charts under small and/or moderate shift sizes. Finally, the proposed monitoring methods are successfully implemented on actual traffic crash data to highlight the efficacy of the proposed methods. The outcome of this study could provide the analysts with insights to plan sound policy recommendations for achieving desired safety goals.

A New Real-Time Process Monitor Method Based on MRC

2014 ◽  
Vol 971-973 ◽  
pp. 1481-1484
Author(s):  
Ke He Wu ◽  
Long Chen ◽  
Yi Li
Keyword(s):  
Information System ◽  
Real Time ◽  
Process Monitoring ◽  
Time Process ◽  
Monitoring Methods ◽  
Traditional Process ◽  
Kernel Level ◽  
Process Monitor

In order to ensure safe and stable running of applications, this paper analyses the limitation of traditional process-monitoring methods, and then designs a new real-time process monitor method based on Mandatory Running Control (MRC) technology. This method not only can monitor the processes, but also can control them from system kernel level to improve the reliability and safety of applications, so as to ensure the security and stability of information system.

Benefits of Real Time Pressure Monitoring from Surface Read out Devices Case History- Zino Hub

2018 ◽  
Author(s):  
Dennar Linda ◽  
Nanpan Monday ◽  
Aderibigbe Olatubosun ◽  
Emelle Chima ◽  
Ekerendu Onyinyechi ◽  
...  
Keyword(s):  
Real Time ◽  
Case History ◽  
Time Pressure ◽  
Pressure Monitoring

Liquid metal embedded real time microfluidic flow pressure monitoring sensor

2020 ◽  
Vol 305 ◽  
pp. 111909 ◽  
Author(s):  
Kelu Peng ◽  
Junyi Yao ◽  
Sunghyun Cho ◽  
Younghak Cho ◽  
Hyun Soo Kim ◽  
...  
Keyword(s):  
Liquid Metal ◽  
Real Time ◽  
Pressure Monitoring ◽  
Microfluidic Flow ◽  
Flow Pressure

Evaluation of two point of care technologies for measuring monoclonal antibody therapeutic-A concentrations in blood

Bioanalysis ◽  
2020 ◽  
Vol 12 (20) ◽  
pp. 1449-1458
Author(s):  
Saloumeh K Fischer ◽  
Kathi Williams ◽  
Ian Harmon ◽  
Bryan Bothwell ◽  
Hua Xu ◽  
...  
Keyword(s):  
Monoclonal Antibody ◽  
Real Time ◽  
Point Of Care ◽  
Turnaround Time ◽  
Monitoring Methods ◽  
Sample Collection ◽  
Time Data ◽  
Serum Samples ◽  
Quick Turnaround Time

Aim: Current blood monitoring methods require sample collection and testing at a central lab, which can take days. Point of care (POC) devices with quick turnaround time can provide an alternative with faster results, allowing for real-time data leading to better treatment decisions for patients. Results/Methodology: An assay to measure monoclonal antibody therapeutic-A was developed on two POC devices. Data generated using 75 serum samples (65 clinical & ten spiked samples) show correlative results to the data generated using Gyrolab technology. Conclusion: This case study uses a monoclonal antibody therapeutic-A concentration assay as an example to demonstrate the potential of POC technologies as a viable alternative to central lab testing with quick results allowing for real-time decision-making.

scholarly journals Effectiveness of a new one-hour blood pressure monitoring method to diagnose hypertension: a diagnostic accuracy clinical trial protocol

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e029268
Author(s):  
Luis González-de Paz ◽  
Belchin Kostov ◽  
Maria del Carme Alvira-Balada ◽  
Cristina Colungo ◽  
Noemí García ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Sensitivity And Specificity ◽  
Blood Pressure Monitoring ◽  
Random Sequence ◽  
Home Blood Pressure ◽  
Monitoring Methods ◽  
Pressure Monitoring ◽  
Monitoring Method ◽  
Policy Makers ◽  
Patient’S Experience

Introduction24-hour ambulatory blood pressure monitoring (ABPM) is the gold standard diagnostic method for hypertension, but has some shortcomings in clinical practice while clinical settings often lack sufficient devices to accommodate all patients with suspected hypertension. Home blood pressure monitoring (HBPM) and office blood pressure monitoring (OBPM) also have shortcomings, such as the white coat effect or a lack of accuracy. This study aims to study the validity of a new method of diagnosing hypertension consisting of monitoring blood pressure (BP) for 1 hour and comparing it with OBPM and HBPM and examining the sensitivity and specificity of this method compared with 24-hour ABPM. The patient experience will be examined in each method.Methods and analysisA minimum sample of 214 patients requiring a diagnostic test for hypertension from three urban primary healthcare centres will be included. Participants will undergo 24-hour ABPM, 1-hour BP measurement (1-BPM), OBPM for three consecutive weeks and HBPM. Patients will follow a random sequence to first receive 24-hour ABPM or 1-hour ABPM. Daytime 24-hour ABPM records will be compared with the other monitoring methods using the correlation coefficient and Bland Altman plots. The kappa concordance index and the sensitivity and specificity of the methods will be calculated. The patient’s experience will be studied, with selected indicators of efficiency and satisfaction calculated using parametric tests.Ethics and disseminationThe protocol has been authorised by the research ethics committee of the Hospital Clinic of Barcelona (Ref. HCB/2014/0615): protocol details and amendments will be recorded and reported to ClinicalTrials.com. The results will be disseminated in peer-reviewed literature, and to policy makers and healthcare partners.Trial registrationNCT03147573; Pre-results.

The Use of Adaptive PCA-Based Condition Monitoring Methods in Machining Processes

2012 ◽  
Author(s):  
Marco Grasso ◽  
Bianca Maria Colosimo ◽  
Giovanni Moroni
Keyword(s):  
Real Time ◽  
Process Monitoring ◽  
Reference Model ◽  
Time Window ◽  
End Milling ◽  
Monitoring Methods ◽  
Time Data ◽  
Machining Processes ◽  
Adaptive Approach ◽  
Adaptive Monitoring

In different manufacturing applications the assessment of the health conditions of a machine tool, together with the quality and stability of the process, requires the capability of dealing with response variables described in terms of profile data. In the frame of in-process monitoring of sensor signals this is the case, for instance, of monitoring either series production of large lots of parts or machining processes characterized by cyclic signals, where both the condition of the machine components and the final quality of the worked piece may be correlated with the stability of repeating signal profiles in time. However, as far as real time data acquisition is concerned, and when measurements are performed with high sampling frequency, data are likely to be auto-correlated, and hence it is of fundamental importance to develop adaptive monitoring tools robust with respect to non-steady state conditions. The paper deals with the utilization of profile monitoring approaches for in-process monitoring of manufacturing operations and investigates their applicability to the problem of monitoring auto-correlated signals. In particular Principal Component Analysis (PCA) is applied in combination with an adaptive approach based on a moving time window for continuously revise the reference model is evaluated and discussed. A real case study is used to test the performances of the method: the task is to detect tool chipping and breakage in end milling operations by means of real-time monitoring of cutting force signals. The evolution of tool wear imposes a trend in observed signals which leads to the need for an adaptive approach to properly isolate the breakage event from the slow pattern change due to wear mechanism.

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