Abstract This paper presents an overview of wet gas multiphase metering and a new meterdesign to meet future offshore challenges. The design introduces new microwaveelectronics, transmission as well as resonance measurements, a salinitymeasurement system, reduced PVT dependence and a new HP/HT design. Building on the success of wet gas metering in accuracy and reliability, thenew meter increases operators' ability to detect the onset of formation waterproduction and accurately measure flow rates where an increasing amount ofliquid and water is present in the flow (due to gas wells produced over a widerrange of process conditions). The new meter design will have an increased importance for subsea tiebacksapplications. While today's wet gas meters are well suited for subsea tiebacks, current subsea developments require longer horizontal production pipelines, where accurate and sensitive measurement of water is crucial to ensure flowassurance and maintain maximum production capacity of the pipeline. Furthermore, the restrictive and remote nature of subsea fields means that thecosts for subsea interventions and periodic fluid sampling (PVT) are high. Thenew meter is more robust to changes in PVT (fluid composition) and reduces theneed for frequent fluid sampling. The paper will describe the development and technology choices of the newinstrument and how it will meet future subsea field demands. It will explain how the new microwave electronics provides more stable andaccurate measurements; how transmission and resonance measurements extend theoperating range to 80–100% GVF and 0–100% WLR; how two complementarytechnologies - a salinity probe for liquid film measurements at low GVF andFormation Water Detection Function software for droplets measurements at highGVF, provide the first complete salinity measurement system in wet gasapplications. The paper will also show how multivariate analysis and new measurements enablethe meter to compensate automatically for changes in produced fluidcomposition. The paper will be highly significant to oil and gas operators looking toincrease flow assurance and oil & gas production from wet gas fields andmeet the growing offshore challenges of varying process conditions, intervention costs, and subsea tie-backs.

The main problem during pulse check in out-of-hospital cardiac arrest is the discrimination between normal pulse-generating rhythm (PR) and pulseless electrical activity (PEA). It has been suggested that circulatory information can be acquired by measuring the thoracic impedance via the defibrillator pads. To investigate this, we performed an experimental study where we retrospectively analyzed 127 PEA segments and 91 PR segments out of 219 and 113 segments. A PEA versus PR classification framework was developed, that uses short segments (< 10 s) of ECG and impedance measurements to discriminate between the two rhythms. Using realistic data analyzed over a duration of 3 s, our system correctly identifies 90.0% of the segments with rhythm being pulseless electrical activity, and 91.5% of the normal pulse rhythm segments. Automatic identification of pulse could avoid unnecessary pulse checks and thereby reduce no-flow time and potentially increase the chance of survival.

Aims: To investigate the potential for finding an alternative for the 'pulse check' during CPR, we studied the use of thoracic impedance measured via the defibrillator pads for circulation assessment during CPR.Materials and methods: Transthoracic impedance, ECG and arterial pressures were recorded on 69 patients with a resulting data set of 434 segments. The circulatory-related impedance waveform was first isolated manually and features characterising its shape were suggested.Results: The features were correlated with corresponding blood pressure measurements, where a tow, but significant, correlation coefficient (0.3) was found. By dividing the data set in groups of sufficient and insufficient circulation and using a neural network, we found that trends in features of the impedance waveform showed a discriminative potential for the two groups. Our classifier achieved a sensitivity of 90% for recognising insufficient circulation with a specificity of 82%.Conclusions: We have shown that the circulation-related information found in the impedance signal may be used for circulatory assessment, especially the recognition of restoration of spontaneous circulation after cardiac arrest. (C) 2006 Elsevier Ireland Ltd. All rights reserved.

It has been suggested to develop automated external defibrillators with the ability to monitor cardiopulmonary resuscitation (CPR) performance online and give corrective feedback in order to improve the resuscitation quality. Thoracic impedance changes are closely correlated to lung volume changes and can be used to monitor the ventilatory activity. We developed a pattern-recognition-based detection system that uses thoracic impedance to accurately detect ventilation during ongoing CPR. The detection system was developed and evaluated on recordings of real-world resuscitation efforts of cardiac arrest patients where ventilations were manually annotated by human experts. The annotated ventilations were detected with an overall positive predictive value of 95.5% for a sensitivity of 90.4%. During chest compressions, the detection system achieved a mean positive predictive value of 94.8% for a sensitivity of 88.7%. The results suggest that accurate ventilation detection during CPR based on the proposed approach is feasible, and that the performance is not significantly degraded in the presence of chest compressions.

Several studies have shown that the carotid pulse check is time-consuming and inaccurate. The sensitivity and specificity of manual pulse check has been reported to be 90% and 55% respectively. It has been suggested that circulatory information can be acquired by measuring the thoracic impedance via the defibrillator pads. We established a dataset of thoracic impedance measurement recorded using a modified automated external defibrillator By usingfeatures describing the impedance waveform resulting from a heart contraction in a pattern recognition framework, we were able to classify periods with systolic blood pressure above or below 80 mmHg with a sensitivity of 90% and a specificity of 82 %.

Possible clinical states of a cardiac arrest patient are ventricular fibrillation/tachycardia (VF/VT), asystole (ASY) or pulseless electrical activity (PEA), and the treatment goals are return of spontaneous circulation (ROSC) and neurologic ally intact survival. Waveform analysis has been used in VF to predict treatment outcomes and we hypothesised that similar analysis in PEA could predict transformation to ROSC. We analysed 120 and 83 PEA segments prior to transitions to ROSC and ASY, respectively, to investigate the ability often electrocardiograph (ECG) features to predict transitions to ROSC or ASY using neural networks. The feature combination that yielded the best discrimination had a meanplusmnSD area under the receiver operating characteristics curve of 0.88plusmn0.02. The results suggest that the ECG contains information regarding the dynamics of PEA which can be used to study effects of therapies in cardiac arrest patients.

It has been suggested to acquire circulatory information from patients undergoing resuscitation from cardiac arrest by analyzing their thoracic electrical impedance using modified automated external defibrillators (AEDs). To investigate the potential of this idea, we studied the correlation between two impedance-derived parameters related to circulation, the negative peak of the impedance fluctuation (Zpeak) and its first time derivative (dZpeak), and arterial blood pressure measurements in 26 patients undergoing resuscitation and 32 hemodynamically stable patients. The highest correlation coefficient, rho=0.4338 was found between the systolic blood pressure and the magnitude of the negative peak of the first time derivative of the impedance. The poor correlation indicates that the impedance-derived parameters are not suitable for quantification of circulation, but can be used to indicate circulation

In the US alone, several hundred thousands die of sudden cardiac arrests each year. Basic life support defined as chest compressions and ventilations and early defibrillation are the only factors proven to increase the survival of patients with out-of-hospital cardiac arrest, and are key elements in the chain of survival defined by the American Heart Association. The current cardiopulmonary resuscitation guidelines treat all patients the same, but studies show need for more individualization of treatment. This review will focus on ideas on how to strengthen the weak parts of the chain of survival including the ability to measure the effects of therapy, improve time efficiency, and optimize the sequence and quality of the various components of cardiopulmonary resuscitation.