Can venous occlusion plethysmography be used to measure high rates of arterial inflow?

To investigate whether venous occlusion plethysmography (VOP) may be used to measure high rates of arterial inflow associated with exercise, venous occlusions were performed at rest, and following dynamic handgrip exercise at 15, 30, 45, and 60 % of maximum voluntary contraction (MVC) in seven healthy males. The effect of including more than one cardiac cycle in the calculation of blood flow was assessed by comparing the cumulative blood flow over one, two, three, or four cardiac cycles. The inclusion of more than one cardiac cycle at 30 and 60 % MVC, and more than two cardiac cycles at 15 and 45 % MVC resulted in a lower blood flow compared to using only the first cardiac cycle (P < 0.05). Despite the small time interval over which arterial inflow was measured (~1 second), this did not affect the reproducibility of the technique. Reproducibility (coefficient of variation for arterial inflow over three trials) tended to be poorer at the higher workloads, although this was not significant (12.7 ± 6.6 %, 16.2 ± 7.3 %, and 22.9 ± 9.9 % for the 15, 30, and 45 % MVC workloads; P=0.102). There was also a tendency for greater reproducibility with the inclusion of more cardiac cycles at the highest workload, but this did not reach significance (P=0.070). In conclusion, when calculated over the first cardiac cycle only during venous occlusion, high rates of FBF can be measured using VOP, and this can be achieved without a significant decrease in the reproducibility of the measurement.

Arterial traffic congestion analysis using Bluetooth duration data

The aim of this study is to assess the potential use of Bluetooth data for traffic monitoring of arterial road networks. Bluetooth data provides the direct measurement of travel time between pairs of scanners, and intensive research has been reported on this topic. Bluetooth data includes “Duration” data, which represents the time spent by Bluetooth devices to pass through the detection range of Bluetooth scanners. If the scanners are located at signalised intersections, this Duration can be related to intersection performance, and hence represents valuable information for traffic monitoring. However the use of Duration has been ignored in previous analyses. In this study, the Duration data as well as travel time data is analysed to capture the traffic condition of a main arterial route in Brisbane. The data consists of one week of Bluetooth data provided by Brisbane City Council. As well, micro simulation analysis is conducted to further investigate the properties of Duration. The results reveal characteristics of Duration, and address future research needs to utilise this valuable data source.

Arterial travel time estimation : revisiting the classical procedure

Travel time is an important network performance measure and it quantifies congestion in a manner easily understood by all transport users. In urban networks, travel time estimation is challenging due to number of reasons such as, fluctuations in traffic flow due to traffic signals, significant flow to/from mid link sinks/sources, etc. The classical analytical procedure utilizes cumulative plots at upstream and downstream locations for estimating travel time between the two locations. In this paper, we discuss about the issues and challenges with classical analytical procedure such as its vulnerability to non conservation of flow between the two locations. The complexity with respect to exit movement specific travel time is discussed. Recently, we have developed a methodology utilising classical procedure to estimate average travel time and its statistic on urban links (Bhaskar, Chung et al. 2010). Where, detector, signal and probe vehicle data is fused. In this paper we extend the methodology for route travel time estimation and test its performance using simulation. The originality is defining cumulative plots for each exit turning movement utilising historical database which is self updated after each estimation. The performance is also compared with a method solely based on probe (Probe-only). The performance of the proposed methodology has been found insensitive to different route flow, with average accuracy of more than 94% given a probe per estimation interval which is more than 5% increment in accuracy with respect to Probe-only method.

The effect of a high fat meal on postprandial arterial stiffness in men with obesity and type 2 diabetes

Context: Postprandial dysmetabolism is emerging as an important cardiovascular risk factor. Augmentation index (AIx) is a measure of systemic arterial stiffness and independently predicts cardiovascular outcome. Objective: The objective of this study was to assess the effect of a standardized high-fat meal on metabolic parameters and AIx in 1) lean, 2) obese nondiabetic, and 3) subjects with type 2 diabetes mellitus (T2DM). Design and Setting: Male subjects (lean, n = 8; obese, n = 10; and T2DM, n = 10) were studied for 6 h after a high-fat meal and water control. Glucose, insulin, triglycerides, and AIx (radial applanation tonometry) were measured serially to determine the incremental area under the curve (iAUC). Results: AIx decreased in all three groups after a high-fat meal. A greater overall postprandial reduction in AIx was seen in lean and T2DM compared with obese subjects (iAUC, 2251 +/- 1204, 2764 +/- 1102, and 1187 +/- 429% . min, respectively; P < 0.05). The time to return to baseline AIx was significantly delayed in subjects with T2DM (297 +/- 68 min) compared with lean subjects (161 +/- 88 min; P < 0.05). There was a significant correlation between iAUC AIx and iAUC triglycerides (r = 0.50; P < 0.05). Conclusions: Obesity is associated with an attenuated overall postprandial decrease in AIx. Subjects with T2DM have a preserved, but significantly prolonged, reduction in AIx after a high-fat meal. The correlation between AIx and triglycerides suggests that postprandial dysmetabolism may impact on vascular dynamics. The markedly different response observed in the obese subjects compared with those with T2DM was unexpected and warrants additional evaluation.

Arterial travel time estimation & prediction : a literature review

This report is the fourth deliverable of the Real Time and Predictive Traveller Information project and the first deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. The objective of this report is to review the literature pertaining to travel time estimation and prediction models for arterial traffic.

Fundamental understanding on the use of Bluetooth MAC scanner for arterial travel time estimation

This report is the eight deliverable of the Real Time and Predictive Traveller Information project and the third deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. Brisbane arterial network is highly equipped with Bluetooth MAC Scanners, which can provide travel time information. Literature is limited with the knowledge on the Bluetooth protocol based data acquisition process and accuracy and reliability of the analysis performed using the data. This report expands the body of knowledge surrounding the use of data from Bluetooth MAC Scanner (BMS) as a complementary traffic data source. A multi layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.

Intra-arterial waveform analysis: a study of senior nurse knowledge in a general intensive care unit

The aim of this small-scale study was to assess what knowledge senior nurses within a general intensive care unit (GICU) had in relation to intra-arterial blood pressure (IABP) waveform analysis. Its core objective was: To assess what knowledge was held by the senior nursing team with regard to arterial waveform interpretation, arterial waveform morphology and the technical aspects associated with arterial waveform monitoring.

Advanced arterial blood gas analysis in septic shock : a Singaporean nursing case review.

Introduction The admission to the Intensive Care Unit with a diagnosis of sepsis and/or septic shock is not uncommon. The aim of this article is to present a nursing case review of a patient admitted to the intensive care unit with a diagnosis of septic shock and the use of bedside acid–base formulae to inform clinical decision making. Method We chose to use a case review. This method is useful in reporting unusual or rare cases and is typically seen more in medicine than in nursing. Discussion The gentleman in question was a self-presentation with a short history of fever and worsening shortness of breath. His condition worsened where he required admission to the intensive care unit. The use of ‘advanced’ acid–base interpretation to guide his nursing care provided a platform from which to advance a deeper understanding of the intricacies the critically ill patient often presents. Conclusion The use of case review is enlightening in understanding the disease process and the decision-making that accompanies this. The lessons learnt are applicable to a wider nursing audience because understanding acid–base physiology is beneficial in supporting and advancing critical care nursing practice.

Arterial short-term travel time prediction using Bluetooth data

This project recognized lack of data analysis and travel time prediction on arterials as the main gap in the current literature. For this purpose it first investigated reliability of data gathered by Bluetooth technology as a new cost effective method for data collection on arterial roads. Then by considering the similarity among varieties of daily travel time on different arterial routes, created a SARIMA model to predict future travel time values. Based on this research outcome, the created model can be applied for online short term travel time prediction in future.