P.R. White

Ultrasonic propagation in cancellous bone: a new stratified model

The theoretical modeling of ultrasonic propagation in cancellous bone is pertinent to improving the ultrasonic diagnosis of osteoporosis. First, this paper reviews applications of Biots theory to this problem. Next, a new approach is presented, based on an idealization of cancellous bone as a periodic array of bone-marrow layers. Schoenbergs theory is applied to this model to predict wave properties. Bovine bone samples were tested in vitro using pulses centered at 1 MHz over various angles relative to the orientated cancellous structure. Two longitudinal modes (fast and slow waves) were observed for propagation parallel to the structure, but only one was observed for propagation normal to the structure. Angular-dependence of velocities was examined, and the fast wave was found to be strongly anisotropic. These results gave qualitative agreement with predictions of Schoenbergs theory. Although this new model is a simplification of the cancellous architecture, it has potential for future research.

Propagation through nonlinear time-dependent bubble clouds and the estimation of bubble populations from measured acoustic characteristics

For several decades the propagation characteristics of acoustic pulses (attenuation and sound speed) have been inverted in attempts to measure the size distributions of gas bubbles in liquids. While this has biomedical and industrial applications, most notably it has been attempted in the ocean for defence and environmental purposes, where the bubbles are predominantly generated by breaking waves. Such inversions have required assumptions, and the state–of–the–art technique still assumes that the bubbles undergo linear, steady–state monochromatic pulsations in the free field, without interacting. The measurements always violate, to a greater or lesser extent, these assumptions. The errors incurred by the use of such assumptions have been difficult to quantify, but are expected to be most severe underneath breakers in the surf zone, where the void fraction is greatest. Very few measurements have been made in this important region of the ocean. This paper provides a method by which attenuation can be predicted through clouds of bubbles which need not be homogeneous, nor restricted to linear steady–state monochromatic pulsations. To allow inversion of measured surf zone attenuations to estimate bubble populations with current computational facilities, this model is simplified such that the bubble cloud is assumed to be homogeneous and the bubbles oscillating in steady state (although still nonlinearly). The uses of the new methods for assessing the errors introduced in using state–of–the–art inversions are discussed, as are their implications for oceanographic and industrial nonlinear bubble counters, for biomedical contrast agents, and for sonar target detection in the surf zone.

Signal processing techniques applied to human sleep EEG signals - a review

Abstract A bewildering variety of methods for analysing sleep EEG signals can be found in the literature. This article provides an overview of these methods and offers guidelines for choosing appropriate signal processing techniques. The review considers the three key stages required for the analysis of sleep EEGs namely, pre-processing, feature extraction, and feature classification. The pre-processing section describes the most frequently used signal processing techniques that deal with preparation of the sleep EEG signal prior to further analysis. The feature extraction and classification sections are also dedicated to highlight the most commonly used signal analysis methods used for characterising and classifying the sleep EEGs. Performance criteria of the addressed techniques are given where appropriate. The online supplementary materials accompanying this article comprise an extended taxonomy table for each section, which contains the relevant signal processing techniques, their brief descriptions (including their pros and cons where possible) and their specific applications in the field of sleep EEG analysis. In order to further increase the readability of the article, signal processing techniques are also categorised in tabular format based on their application in intensively researched sleep areas such as sleep staging, transient pattern detection and sleep disordered breathing diagnosis.

Training methods for image noise level estimation on wavelet components

The estimation of the standard deviation of noise contaminating an image is a fundamental step in wavelet-based noise reduction techniques. The method widely used is based on the mean absolute deviation (MAD). This model-based method assumes specific characteristics of the noise-contaminated image component. Three novel and alternative methods for estimating the noise standard deviation are proposed in this work and compared with the MAD method. Two of these methods rely on a preliminary training stage in order to extract parameters which are then used in the application stage. The sets used for training and testing, 13 and 5 images, respectively, are fully disjoint. The third method assumes specific statistical distributions for image and noise components. Results showed the prevalence of the training-based methods for the images and the range of noise levels considered.

The effect of reverberation on the damping of bubbles

The measurement of an acoustic emission, or scatter, from a bubble is not difficult. However, an accurate interpretation of that signal in terms of the bubble dynamics may require careful consideration. The study presented here is at first sight relatively simple: comparison of the predicted and measured quality factors of injected bubbles. While the measurement is normally done by monitoring the decay of passive emissions from a bubble, this technique becomes difficult with smaller bubbles. Therefore an active technique is introduced, which removes all the frequency-dependent effects on the measurement (such as transducer response) bar one. That, critically, is the effect of the change in the bubble resonance (frequency and damping) which results from the loading on the bubble due to the reverberant field. The vast majority of theoretical treatments of bubble acoustics assume free field conditions, yet the environmental conditions rarely if ever match these. Therefore measurements of bubble damping are compared both with the established free field theory, and with a new theory relevant to the prevailing reverberant conditions (whether caused by tank surfaces, monochromatic neighboring bubbles, or both).

Quantification of undersea gas leaks from carbon capture and storage facilities, from pipelines and from methane seeps, by their acoustic emissions

In recent years, because of the importance of leak detection from carbon capture and storage facilities and the need to monitor methane seeps and undersea gas pipelines, there has been an increased requirement for methods of detecting bubbles released from the seabed into the water column. If undetected and uncorrected, such leaks can generate huge financial and environmental losses. This paper describes a theory by which the passive acoustic signals detected by a hydrophone array can be used to quantify gas leakage, providing a practical (as opposed to research), passive and remote detection system which can monitor over a period of years using simple instrumentation. The sensitivity in detecting and quantifying the flux of gas is shown to exceed by more than two orders of magnitude the sensitivity of the current model-based techniques used commercially for gas leaks from large, long pipelines.

Speech spectral amplitude estimators using optimally shaped Gamma and Chi priors

In this paper, four STFT based speech enhancement algorithms are proposed. The algorithms enhance speech by estimating its short time spectral amplitude and are combinations of two estimators (MMSE and MAP) with two speech spectral amplitude priors (Gamma and Chi). The proposed priors have a shape parameter a, whose effect on the quality of speech is a focal point of our investigation. Rather than using a priori estimated values of a, we seek those values that maximise the quality of the enhanced speech, in an a posteriori fashion. The performance of the algorithms is first evaluated as a function of the shape parameter a and optimal values are then sought by means of a formal subjective listening test. Finally, the parallel examination of four speech enhancement algorithms offers an insight into the relative importance of the employed priors and estimators, as the proposed algorithms are only different with respect to these two elements.

Automatic detection and classification of odontocete whistles.

Methods for the fully automatic detection and species classification of odontocete whistles are described. The detector applies a number of noise cancellation techniques to a spectrogram of sound data and then searches for connected regions of data which rise above a pre-determined threshold. When tested on a dataset of recordings which had been carefully annotated by a human operator, the detector was able to detect (recall) 79.6% of human identified sounds that had a signal-to-noise ratio above 10 dB, with 88% of the detections being valid. A significant problem with automatic detectors is that they tend to partially detect whistles or break whistles into several parts. A classifier has been developed specifically to work with fragmented whistle detections. By accumulating statistics over many whistle fragments, correct classification rates of over 94% have been achieved for four species. The success rate is, however, heavily dependent on the number of species included in the classifier mix, with the mean correct classification rate dropping to 58.5% when 12 species were included.

The frequency dependence of compressional wave velocity and attenuation coefficient of intertidal marine sediments

To advance the present understanding of the frequency dependence of compressional wave velocity and attenuation in marine sediments a series of well-constrained in situ acoustic transmission experiments (16 to 100kHz) were performed on intertidal sediments. The processing techniques incorporated in situ spreading losses, sediment to transducer coupling and thorough error analyses. Significant variations in velocity and attenuation were observed over scales of tens of meters within the same sediment type. Velocity was generally nondispersive in sands, while highly variable silt velocities prevented any meaningful dispersion estimates from being determined. The attenuation coefficient was proportional to frequency for 75% of the experimental sites. The measured compressional wave properties were compared to predictions from the Grain-Shearing model. For the sandy sites, the phase velocities predicted by the Grain Shearing model exceed those measured, while predicted phase velocities agreed with measured gro...

The detection and dimension of bubble entrainment and comminution

Data on bubble entrainment and comminution are gathered in three experiments, involving the breakup of a disk of air trapped between two plates, and bubble cloud generation under a waterfall, and a plunging jet. In the second two cases, an automated acoustic system for characterizing the entrainment is employed. The data sets are compared with an existing theory for bubble fragmentation, in which a key parameter is the number of spatial dimensions associated with the insertion of randomly positioned planes which are used to divide up the bubble. While an appropriate best-fit theoretical curve can be obtained for the bubble population histograms generated by air disk comminution, waterfalls and plunging jets produce multimodal distributions which the theory cannot model. The differing roles of shape oscillations and surface waves in bubble fragmentation, and the issues involved with incorporating these into the model, are examined.