992 resultados para source localisation


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Managing the sustainability of urban infrastructure requires regular health monitoring of key infrastructure such as bridges. The process of structural health monitoring involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors, and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures, and acoustic emission is one technique that is finding an increasing use in the monitoring of civil infrastructures such as bridges. Acoustic emission technique is based on the recording of stress waves generated by rapid release of energy inside a material, followed by analysis of recorded signals to locate and identify the source of emission and assess its severity. This chapter first provides a brief background of the acoustic emission technique and the process of source localization. Results from laboratory experiments conducted to explore several aspects of the source localization process are also presented. The findings from the study can be expected to enhance knowledge of the acoustic emission process, and to aid the development of effective bridge structure diagnostics systems.

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This paper presents a novel method for enabling a robot to determine the direction to a sound source through interacting with its environment. The method uses a new neural network, the Parameter-Less Self-Organizing Map algorithm, and reinforcement learning to achieve rapid and accurate response.

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This work sets out to evaluate the potential benefits and pit-falls in using a priori information to help solve the Magnetoencephalographic (MEG) inverse problem. In chapter one the forward problem in MEG is introduced, together with a scheme that demonstrates how a priori information can be incorporated into the inverse problem. Chapter two contains a literature review of techniques currently used to solve the inverse problem. Emphasis is put on the kind of a priori information that is used by each of these techniques and the ease with which additional constraints can be applied. The formalism of the FOCUSS algorithm is shown to allow for the incorporation of a priori information in an insightful and straightforward manner. In chapter three it is described how anatomical constraints, in the form of a realistically shaped source space, can be extracted from a subject’s Magnetic Resonance Image (MRI). The use of such constraints relies on accurate co-registration of the MEG and MRI co-ordinate systems. Variations of the two main co-registration approaches, based on fiducial markers or on surface matching, are described and the accuracy and robustness of a surface matching algorithm is evaluated. Figures of merit introduced in chapter four are shown to given insight into the limitations of a typical measurement set-up and potential value of a priori information. It is shown in chapter five that constrained dipole fitting and FOCUSS outperform unconstrained dipole fitting when data with low SNR is used. However, the effect of errors in the constraints can reduce this advantage. Finally, it is demonstrated in chapter six that the results of different localisation techniques give corroborative evidence about the location and activation sequence of the human visual cortical areas underlying the first 125ms of the visual magnetic evoked response recorded with a whole head neuromagnetometer.

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The process of structural health monitoring (SHM) involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures and acoustic emission (AE) is one technique that is finding an increasing use. Acoustic emission waves are the stress waves generated by the mechanical deformation of materials. AE waves produced inside a structure can be recorded by means of sensors attached on the surface. Analysis of these recorded signals can locate and assess the extent of damage. This paper describes preliminary studies on the application of AE technique for health monitoring of bridge structures. Crack initiation or structural damage will result in wave propagation in solid and this can take place in various forms. Propagation of these waves is likely to be affected by the dimensions, surface properties and shape of the specimen. This, in turn, will affect source localization. Various laboratory test results will be presented on source localization, using pencil lead break tests. The results from the tests can be expected to aid in enhancement of knowledge of acoustic emission process and development of effective bridge structure diagnostics system.

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The topography of the visual evoked magnetic response (VEMR) to a pattern onset stimulus was investigated using 4 check sizes and 3 contrast levels. The pattern onset response consists of three early components within the first 200ms, CIm, CIIm and CIIIm. The CIIm is usually of high amplitude and is very consistent in latency within a subject. Half field (HF) stimuli produce their strongest response over the contralateral hemisphere; the RHF stimulus exhibiting a lower positivity (outgoing field) and an upper negativity (ingoing field), rotated towards the midline. LHF stimulation produced the opposite response, a lower negative and an upper positive. Larger check sizes produce a single area of ingoing and outgoing field while smaller checks produce on area of ingoing and outgoing field over each hemisphere. Latency did not appear to vary with change in contrast but amplitudes increased with increasing contrast. A more detailed topographic study incorporating source localisation procedures suggested a source for CIIm - 4cm below the scalp, close to the midline with current flowing towards the lateral surface. Similar depth and position estimates but with opposite polarity were obtained for the pattern shift P100m previously. Hence, the P100m and the CIIm may originate in similar areas of visual cortex but reveal different aspects of visual processing. © 1992 Human Sciences Press, Inc.

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The 19 channel Neuromagnetometer system in the Clinical Neurophysiology Unit at Aston University is a multi-channel system, unique in the United Kingdom. A bite bar head localisation and MRI co-registration strategy which enabled accurate and reproducible localisation of MEG data into cortical space was developed. This afforded the opportunity to study magnetic fields of the human cortex generated by stimulation of peripheral nerve, by stimulation of visceral sensory receptors and by those evoked through voluntary finger movement. Initially, a study of sensory-motor evoked data was performed in a healthy control population. The techniques developed were then applied to patients who were to undergo neurosurgical intervention for the treatment of epilepsy and I or space occupying lesions. This enabled both validation of the effective accuracy of source localisation using MEG as well as to determine the clinical value of MEG in presurgical assessment of functional localisation in human cortex. The studies in this thesis have demonstrated that MEG can repeatedly and reliably locate sources contained within a single gyrus and thus potentially differentiate between disparate gyral activation. This ability is critical in the clinical application of any functional imaging technique; which is yet to be fully validated by any other 'non-invasive' functional imaging methodology. The technique was also applied to the study of visceral sensory representation in the cortex which yielded important data about the multiple cortical representation of visceral sensory function.

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Bridges are an important part of a nation’s infrastructure and reliable monitoring methods are necessary to ensure their safety and efficiency. Most bridges in use today were built decades ago and are now subjected to changes in load patterns that can cause localized distress, which can result in bridge failure if not corrected. Early detection of damage helps in prolonging lives of bridges and preventing catastrophic failures. This paper briefly reviews the various technologies currently used in health monitoring of bridge structures and in particular discusses the application and challenges of acoustic emission (AE) technology. Some of the results from laboratory experiments on a bridge model are also presented. The main objectives of these experiments are source localisation and assessment. The findings of the study can be expected to enhance the knowledge of acoustic emission process and thereby aid in the development of an effective bridge structure diagnostics system.

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Advances in functional brain imaging have allowed the development of new investigative techniques with clinical application—ranging from presurgical mapping of eloquent cortex to identifying cortical regions involved in religious experiences. Similarly a variety of methods are available to referring physicians, ranging from metabolic measures such as functional magnetic resonance imaging and positron emission tomography to measurements based on electrical activity such as electroencephalography and magnetoencephalography. However, there are no universal benchmarks by which to judge between these methods. In this study we attempt to develop a standard for functional localisation, based on the known functional organisation of somatosensory cortex. Studies have shown spatially distinct sites of brain activity in response to stimulation of various body parts. Generally these studies have focused on areas with large cortical representations, such as the index finger and face. We tested the limits of magnetoencephalography source localisation by stimulation of body parts, namely the clunis and the cubitus, that map to proximal and relatively poorly represented regions of somatosensory cortex.

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The problems of using a single channel magnetometer (BTi, Model 601) in an unshielded clinical environment to measure visual evoked magnetic responses (VEMR) were studied. VEMR to flash and pattern reversal stimuli were measured in 100 normal subjects. Two components, the P100M to pattern reversal and P2M to flash, were measured successfully in the majority of patients. The mean latencies of these components in different decades of life were more variable than the visual evoked potentials (VEP) that have been recorded to these stimuli. The latency of the P100M appeared to increase significantly after about 55 years of age whereas little change occurred for the flash P2M. The effects of blur, check size, stimulus size and luminance intensity on the latency and amplitude of the VEMR were studied. Blurring a small (32') check significantly increased latency whereas blurring a large (70') check had little effect on latency. Increasing check size significantly reduced latency of the P100M but had little effect on amplitude. Increasing the field size decreases the latency and increases the amplitude of the P100M. Within a normal subject, most of the temporal variability of the P100M appeared to be associated with run to run variation rather than between recording sessions on the same day or between days. Reproducibility of the P100M was improved to a degree by employing a magnetically shielded room. Increasing flash intensity decreases the latency and increases the amplitude of the P2M component. The magnitude of the effects of varying stimulus parameters on the VEMR were frequently greater than is normally seen in the VEP. The topography of the P100M and P2M varied over the scalp in normal subjects. Full field responses to a large check could be explained as approximately the sum of the half field responses and were consistent with the cruciform model of the visual cortex. Preliminary source localisation data suggested a shallower source in the visual cortex for the flash P2M compared with the P100M. The data suggest that suitable protocols could be devised to obtain normative data of sufficient quality to use the VEMR to flash and pattern clinically.