Electrohysterogram signal component cataloging with spectral and time-frequency methods

The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].

Preliminary regional rockfall hazard mapping using LIDAR-based slope frequency distribution and CONEFALL modeling

A factor limiting preliminary rockfall hazard mapping at regional scale is often the lack of knowledge of potential source areas. Nowadays, high resolution topographic data (LiDAR) can account for realistic landscape details even at large scale. With such fine-scale morphological variability, quantitative geomorphometric analyses become a relevant approach for delineating potential rockfall instabilities. Using digital elevation model (DEM)-based ?slope families? concept over areas of similar lithology and cliffs and screes zones available from the 1:25,000 topographic map, a susceptibility rockfall hazard map was drawn up in the canton of Vaud, Switzerland, in order to provide a relevant hazard overview. Slope surfaces over morphometrically-defined thresholds angles were considered as rockfall source zones. 3D modelling (CONEFALL) was then applied on each of the estimated source zones in order to assess the maximum runout length. Comparison with known events and other rockfall hazard assessments are in good agreement, showing that it is possible to assess rockfall activities over large areas from DEM-based parameters and topographical elements.

Time-based distribution of Staphylococcus saprophyticus pulsed field gel-electrophoresis clusters in community-acquired urinary tract infections

The epidemiology of urinary tract infections (UTI) by Staphylococcus saprophyticus has not been fully characterised and strain typing methods have not been validated for this agent. To evaluate whether epidemiological relationships exist between clusters of pulsed field gel-electrophoresis (PFGE) genotypes of S. saprophyticus from community-acquired UTI, a cross-sectional surveillance study was conducted in the city of Rio de Janeiro, Brazil. In total, 32 (16%) female patients attending two walk-in clinics were culture-positive for S. saprophyticus. Five PFGE clusters were defined and evaluated against epidemiological data. The PFGE clusters were grouped in time, suggesting the existence of community point sources of S. saprophyticus. From these point sources, S. saprophyticus strains may spread among individuals.

Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals

Background: oscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies. Oscillatory burst events should consequently play a specific functional role, distinct from background EEG activity – especially for cognitive tasks (e.g. working memory tasks), binding mechanisms and perceptual dynamics (e.g. visual binding), or in clinical contexts (e.g. effects of brain disorders). However extracting oscillatory events in single trials, with a reliable and consistent method, is not a simple task. Results: in this work we propose a user-friendly stand-alone toolbox, which models in a reasonable time a bump time-frequency model from the wavelet representations of a set of signals. The software is provided with a Matlab toolbox which can compute wavelet representations before calling automatically the stand-alone application. Conclusion: The tool is publicly available as a freeware at the address: http:// www.bsp.brain.riken.jp/bumptoolbox/toolbox_home.html

A frequency distribution approach to hotspot identification

We present a new global method for the identification of hotspots in conservation and ecology. The method is based on the identification of spatial structure properties through cumulative relative frequency distributions curves, and is tested with two case studies, the identification of fish density hotspots and terrestrial vertebrate species diversity hotspots. Results from the frequency distribution method are compared with those from standard techniques among local, partially local and global methods. Our approach offers the main advantage to be independent from the selection of any threshold, neighborhood, or other parameter that affect most of the currently available methods for hotspot analysis. The two case studies show how such elements of arbitrariness of the traditional methods influence both size and location of the identified hotspots, and how this new global method can be used for a more objective selection of hotspots.

Online bayesian inference in some time-frequency representations of non-stationary processes

The use of Bayesian inference in the inference of time-frequency representations has, thus far, been limited to offline analysis of signals, using a smoothing spline based model of the time-frequency plane. In this paper we introduce a new framework that allows the routine use of Bayesian inference for online estimation of the time-varying spectral density of a locally stationary Gaussian process. The core of our approach is the use of a likelihood inspired by a local Whittle approximation. This choice, along with the use of a recursive algorithm for non-parametric estimation of the local spectral density, permits the use of a particle filter for estimating the time-varying spectral density online. We provide demonstrations of the algorithm through tracking chirps and the analysis of musical data.

Time-frequency analysis of acoustic noise produced by breaking of crisp biscuits

This paper demonstrates by means of joint time-frequency analysis that the acoustic noise produced by the breaking of biscuits is dependent on relative humidity and water activity. It also shows that the time-frequency coefficients calculated using the adaptive Gabor transformation algorithm is dependent on the period of time a biscuit is exposed to humidity. This is a new methodology that can be used to assess the crispness of crisp foods. (c) 2007 Elsevier Ltd. All rights reserved.

Time-frequency analysis combining wavelets and the envelope technique for fault identification in rotary machines

Nowadays the method based on demodulation by envelope finds wide application in industry as a technique for evaluation of bearings and other components in rotating machinery. In recent years the application of Wavelets for fault diagnosis in machinery has also obtained good development. This article demonstrates the effectiveness of the combined application of Wavelets and envelope technique (also known as HFRT High-Frequency Resonance Technique) to remove background noise from signals collected from defect bearings and identification of the characteristic frequencies of defects. A comparison of the results obtained with the isolated application of only one method against the combined technique is performed showing the increased capacity in detection of faults in rolling bearings. © (2013) Trans Tech Publications, Switzerland.

Design and Computation of Warped Time-Frequency Transforms

In this work we introduce an analytical approach for the frequency warping transform. Criteria for the design of operators based on arbitrary warping maps are provided and an algorithm carrying out a fast computation is defined. Such operators can be used to shape the tiling of time-frequency plane in a flexible way. Moreover, they are designed to be inverted by the application of their adjoint operator. According to the proposed mathematical model, the frequency warping transform is computed by considering two additive operators: the first one represents its nonuniform Fourier transform approximation and the second one suppresses aliasing. The first operator is known to be analytically characterized and fast computable by various interpolation approaches. A factorization of the second operator is found for arbitrary shaped non-smooth warping maps. By properly truncating the operators involved in the factorization, the computation turns out to be fast without compromising accuracy.

Dynamic identification of structures: experimental assessment of modal parameteres through methods in frequency domain, in time-frequency domain and model updating

Among the experimental methods commonly used to define the behaviour of a full scale system, dynamic tests are the most complete and efficient procedures. A dynamic test is an experimental process, which would define a set of characteristic parameters of the dynamic behaviour of the system, such as natural frequencies of the structure, mode shapes and the corresponding modal damping values associated. An assessment of these modal characteristics can be used both to verify the theoretical assumptions of the project, to monitor the performance of the structural system during its operational use. The thesis is structured in the following chapters: The first introductive chapter recalls some basic notions of dynamics of structure, focusing the discussion on the problem of systems with multiply degrees of freedom (MDOF), which can represent a generic real system under study, when it is excited with harmonic force or in free vibration. The second chapter is entirely centred on to the problem of dynamic identification process of a structure, if it is subjected to an experimental test in forced vibrations. It first describes the construction of FRF through classical FFT of the recorded signal. A different method, also in the frequency domain, is subsequently introduced; it allows accurately to compute the FRF using the geometric characteristics of the ellipse that represents the direct input-output comparison. The two methods are compared and then the attention is focused on some advantages of the proposed methodology. The third chapter focuses on the study of real structures when they are subjected to experimental test, where the force is not known, like in an ambient or impact test. In this analysis we decided to use the CWT, which allows a simultaneous investigation in the time and frequency domain of a generic signal x(t). The CWT is first introduced to process free oscillations, with excellent results both in terms of frequencies, dampings and vibration modes. The application in the case of ambient vibrations defines accurate modal parameters of the system, although on the damping some important observations should be made. The fourth chapter is still on the problem of post processing data acquired after a vibration test, but this time through the application of discrete wavelet transform (DWT). In the first part the results obtained by the DWT are compared with those obtained by the application of CWT. Particular attention is given to the use of DWT as a tool for filtering the recorded signal, in fact in case of ambient vibrations the signals are often affected by the presence of a significant level of noise. The fifth chapter focuses on another important aspect of the identification process: the model updating. In this chapter, starting from the modal parameters obtained from some environmental vibration tests, performed by the University of Porto in 2008 and the University of Sheffild on the Humber Bridge in England, a FE model of the bridge is defined, in order to define what type of model is able to capture more accurately the real dynamic behaviour of the bridge. The sixth chapter outlines the necessary conclusions of the presented research. They concern the application of a method in the frequency domain in order to evaluate the modal parameters of a structure and its advantages, the advantages in applying a procedure based on the use of wavelet transforms in the process of identification in tests with unknown input and finally the problem of 3D modeling of systems with many degrees of freedom and with different types of uncertainty.

Topographic time-frequency decomposition of the EEG

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.

Time-frequency characterization of a sound propagation channel as an educational tool

This paper discusses the use of sound waves to illustrate multipath radio propagation concepts. Specifically, a procedure is presented to measure the time-varying frequency response of the channel. This helps demonstrate how a propagation channel can be characterized in time and frequency, and provides visualizations of the concepts of coherence time and coherence bandwidth. The measurements are very simple to carry out, and the required equipment is easily available. The proposed method can be useful for wireless or mobile communication courses.