Automatic sleep apnea detection and sleep classification using the ECG and the SpO2 signals

Dissertation for a Masters Degree in Computer and Electronic EngineeringThe present work describes the aspects to implement a system that can be used as a swift and accessible screening tool in patients whose complaints are compatible with OSAS (Obstructive Sleep Apnea Syndrome). This system only uses two signals, electrocardiogram (ECG) and the saturation of oxygen in arterial blood flow (SPO2). This system would be applied for the ambulatory automatic screening of OSAS, which currently are done in a Hospital environment, with a substantial waiting list. The system also would overcome the time consuming visual sleep scoring that contributes for the mentioned waiting list. We have developed a system that automatically detects OSAS based on the ECG and SpO2. However this system has to be paired up with another that detects the awake/sleep/REM periods (also based on the ECG), which is also part of this work. This last component has proved to produce results that are complex to classify,for which there is still a lack of research work. However we have described the necessary algorithms, and have used state-of-the-art signal processing tools, such as wavelets

Information Processing Constraints and Asset Mispricing

I analyse a series of natural quasi-experiments - centred on betting exchange data on the Wimbledon Tennis Championships - to determine whether information processing constraints are partially responsible for mispricing in asset markets. I find that the arrival of information during each match leads to substantial mispricing between two equivalent assets, and that part of this mispricing can be attributed to differences in the frequency with which the two prices are updated inplay. This suggests that information processing constraints force the periodic neglect of one of the assets, thereby causing substantial, albeit temporary, mispricing in this simple asset market

Scalar and vector Slepian functions, spherical signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and, particularly for applications in the geosciences, for scalar and vectorial signals defined on the surface of a unit sphere.Comment: Submitted to the 2nd Edition of the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verlag. This is a slightly modified but expanded version of the paper arxiv:0909.5368 that appeared in the 1st Edition of the Handbook, when it was called: Slepian functions and their use in signal estimation and spectral analysi

Collisionless dynamics in Globular Clusters

Since globular clusters (GCs) are old, low-N systems their dynamics is widely believed to be fully dominated by collisional two-body processes, and their surface brightness profiles are fit by King models. However, for many GCs, especially those with HST-resolved central regions, and `extra-tidal' features, King models provide poor fits. We suggest that this is partly because collisionless dynamics is also important and contribute to shaping the cluster properties. We show using time-scale and length-scale arguments that except for the very centers of clusters, collisionless dynamics should be more important than collisional. We then fit 38 GCs analyzed by Noyola and Gebhardt (2006) with (collisional) King and (collisionless) DARKexp models over the full available radial range, and find that the latter provide a better fit to 29 GCs; for six of these the fit is at least ~5x better in term of rms. DARKexp models are theoretically derived maximum entropy equilibrium states of self-gravitating collisionless systems and have already been shown to fit the results of dark matter N-body simulations. (We do not attempt fits with ad hoc fitting functions.)Comment: 27 pages, 18 figures; accepted to MNRA

Slepian functions and their use in signal estimation and spectral analysis

It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and on the surface of a sphere.Comment: Submitted to the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verla

Increased risk of A(H1N1)pdm09 influenza infection in UK pig industry workers compared to a general population cohort.

BACKGROUND: Pigs are mixing vessels for influenza viral reassortment but the extent of influenza transmission between swine and humans is not well understood. OBJECTIVES: To assess whether occupational exposure to pigs is a risk factor for human infection with human and swine-adapted influenza viruses. METHODS: UK pig industry workers were frequency-matched on age, region, sampling month, and gender with a community-based comparison group from the Flu Watch study. HI assays quantified antibodies for swine and human A(H1) and A(H3) influenza viruses (titres≥40 considered seropositive and indicative of infection). Virus-specific associations between seropositivity and occupational pig exposure were examined using multivariable regression models adjusted for vaccination. Pigs on the same farms were also tested for seropositivity. RESULTS: 42% of pigs were seropositive to A(H1N1)pdm09. Pig industry workers showed evidence of increased odds of A(H1N1)pdm09 seropositivity compared to the comparison group, albeit with wide confidence intervals (CI), Adjusted Odds Ratio after accounting for possible cross reactivity with other swine A(H1) viruses (aOR) 25.3, 95% CI [1.4-536.3], p=0.028. CONCLUSION: The results indicate that A(H1N1)pdm09 virus was common in UK pigs during the pandemic and subsequent period of human A(H1N1)pdm09 circulation, and occupational exposure to pigs was a risk factor for human infection. Influenza immunization of pig industry workers may reduce transmission and the potential for virus reassortment. This article is protected by copyright. All rights reserved

Causal relationship between polycystic ovary syndrome and coronary artery disease: A Mendelian randomisation study.

OBJECTIVE: Polycystic ovary syndrome (PCOS) has been associated with an increased risk of coronary artery disease (CAD). However, it remains uncertain whether this increased risk is the result of PCOS per se or, alternatively, is explained by obesity, a common feature of PCOS. The aim of this study was to assess the causal association between PCOS and CAD and the role of obesity herein. DESIGN AND METHODS: We conducted two-sample Mendelian randomisation analyses in large-scale, female-specific datasets to study the association between genetically predicted (1) risk of PCOS and risk of CAD, (2) body mass index (BMI) and risk of PCOS and (3) BMI and risk of CAD. Primary analyses were conducted with the inverse-variance weighted (IVW) method. Simple median, penalized weighted median and contamination mixture analyses were performed to assess the robustness of the outcomes. RESULTS: IVW analyses did not show a statistically significant association between PCOS and CAD (odds ratio [OR]: 0.99, 95% confidence interval [CI]: 0.89, 1.11). In contrast, genetically predicted BMI was statistically significantly associated with an increased odds of PCOS (OR: 3.21, 95% CI: 2.26, 4.56) and CAD (OR: 1.38, 95% CI: 1.14, 1.67). Similar results were obtained when secondary analyses were performed. CONCLUSION: These sex-specific analyses show that the genetically predicted risk of PCOS is not associated with the risk of CAD. Instead, the genetically predicted risk of obesity (and its downstream metabolic effects) is the common denominator of both PCOS and CAD risk

Severe zinc depletion of escherichia coli: roles for high affinity zinc binding by ZinT, zinc transport and zinc-independent proteins

Zinc ions play indispensable roles in biological chemistry. However, bacteria have an impressive ability to acquire Zn2+ from the environment, making it exceptionally difficult to achieve Zn2+ deficiency, and so a comprehensive understanding of the importance of Zn2+ has not been attained. Reduction of the Zn2+ content of Escherichia coli growth medium to 60 nM or less is reported here for the first time, without recourse to chelators of poor specificity. Cells grown in Zn2+-deficient medium had a reduced growth rate and contained up to five times less cellular Zn2+. To understand global responses to Zn2+ deficiency, microarray analysis was conducted of cells grown under Zn2+-replete and Zn2+-depleted conditions in chemostat cultures. Nine genes were up-regulated more than 2-fold (p<0.05) in cells from Zn2+-deficient chemostats, including zinT (yodA). zinT is shown to be regulated by Zur ( zinc uptake regulator). A mutant lacking zinT displayed a growth defect and a 3-fold lowered cellular Zn2+ level under Zn2+ limitation. The purified ZinT protein possessed a single, high affinity metal-binding site that can accommodate Zn2+ or Cd2+. A further up-regulated gene, ykgM, is believed to encode a non-Zn2+ finger-containing paralogue of the Zn2+ finger ribosomal protein L31. The gene encoding the periplasmic Zn2+- binding protein znuA showed increased expression. During both batch and chemostat growth, cells "found" more Zn2+ than was originally added to the culture, presumably because of leaching from the culture vessel. Zn2+ elimination is shown to be a more precise method of depleting Zn2+ than by using the chelator N,N,N',N'-tetrakis(2-pyridylmethyl)ethylenediamine

Electrophysiological Heterogeneity of Fast-Spiking Interneurons: Chandelier versus Basket Cells

In the prefrontal cortex, parvalbumin-positive inhibitory neurons play a prominent role in the neural circuitry that subserves working memory, and alterations in these neurons contribute to the pathophysiology of schizophrenia. Two morphologically distinct classes of parvalbumin neurons that target the perisomatic region of pyramidal neurons, chandelier cells (ChCs) and basket cells (BCs), are generally thought to have the same "fast-spiking" phenotype, which is characterized by a short action potential and high frequency firing without adaptation. However, findings from studies in different species suggest that certain electrophysiological membrane properties might differ between these two cell classes. In this study, we assessed the physiological heterogeneity of fast-spiking interneurons as a function of two factors: species (macaque monkey vs. rat) and morphology (chandelier vs. basket). We showed previously that electrophysiological membrane properties of BCs differ between these two species. Here, for the first time, we report differences in ChCs membrane properties between monkey and rat. We also found that a number of membrane properties differentiate ChCs from BCs. Some of these differences were species-independent (e.g., fast and medium afterhyperpolarization, firing frequency, and depolarizing sag), whereas the differences in the first spike latency between ChCs and BCs were species-specific. Our findings indicate that different combinations of electrophysiological membrane properties distinguish ChCs from BCs in rodents and primates. Such electrophysiological differences between ChCs and BCs likely contribute to their distinctive roles in cortical circuitry in each species. © 2013 Povysheva et al