Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

The removal of patients who live outside the practice boundary:a study of outside-area removals in Northern Ireland in 2001-2002

It has been suggested that there are significant overlaps between removals due to deregistration and removals arising because patients live outside the practice area. If this is true, it would mean that the current estimates of deregistration would need to be revised upwards. All outside-area removals for the calendar years 2001 and 2002 were reviewed and characterised by age, sex and Jarman score of the enumeration district of the patients' residence and distance from the practice. The average outside-area removal rate was just over one removal per practice per year. Removal rates were highest between the ages of 18 and 44 years; there were no significant differences between the sexes. Rates of removal increased exponentially with distance, although even at marked distances from the practice there were about 10 patients remaining on the list for each one removed. Residents in deprived areas were more likely to be removed, although because areas most distal to the practice tend to be affluent, overall there was a predominance of affluent patients among those who are removed. In Northern Ireland rates of outside-area removal are only slightly higher than those of deregistration. It is evident that GPs are exercising some discretion as to which of the outside-area patients they retain on their list. This has the potential to cause some misunderstanding and resentment among patients, as has been reported previously.

Catheter-related bloodstream infection in adult haematology patients:Catheter removal practice and outcome

The aim of the present study was to describe the practice of central venous catheter (CVC) removal and outcomes of catheter-related bloodstream infection (CR-BSI) in adult haematology patients. Patients were identified retrospectively according to diagnosis coding of inpatient episodes and evaluated when, on examination of medical records, there had been evidence of sepsis with strong clinical suspicion that the source was the CVC. Demographic and bacteriological data, as well as therapeutic measures and clinical outcomes, were recorded. One hundred and three patient episodes were evaluated. The most frequent type of CVC was the Hickman catheter and the most frequently isolated pathogen was coagulase-negative staphylococci. Twenty-five percent of episodes were managed with catheter removal. Treatment failure, defined as recurrence of infection within 90 days or mortality attributed to sepsis within 30 days, occurred significantly more frequently in the group managed without catheter removal (52.5% versus 4%, P

Removal of natural hormones in dairy farm wastewater using reactive and sorptive materials

The objective of this study was to examine the estrogen and androgen hormone removal efficiency of reactive (Connelly zero-valent iron (ZVI), Gotthart Maier ZVI) and sorptive (AquaSorb 101 granular activated carbon (GAC) and OrganoLoc PM-100 organo clay (OC)) materials from HPLC grade water and constructed wetland system (CWS) treated dairy farm wastewater. Batch test studies were performed and hormone concentration analysis carried out using highly sensitive reporter gene assays (RGAs). The results showed that hormonal interaction with these materials is selective for individual classes of hormones. Connelly ZVI and AquaSorb 101 GAC were more efficient in removing testosterone (Te) than 17?-estradiol (E2) and showed faster removal rates of estrogen and androgen than the other materials. Gotthart Maier ZVI was more efficient in removing E2 than Te. OrganoLoc PM-100 OC achieved the lowest final concentration of E2 equivalent (EEQ) and provided maximum removal of both estrogens and androgens.

Removal of naphthenic acids from crude oil using amino acid ionic liquids

A number of tetraalkylammonium and tetraalkylphosphonium amino acid based ionic liquids (AAILs) have been successfully used and recycled for the reactive extraction of naphthenic acids from crude oil and crude oil distillates. Spectral studies show that the mechanism by which this occurs is through the formation of a zwitterionic complex. Therein, the amino acid anion plays a key role in the formation of this complex. (C) 2013 Elsevier Ltd. All rights reserved.

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.