Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

Studio neuroradiologico (morfologico e funzionale) nei pazienti con Epilessia Frontale Notturna

L'epilessia frontale notturna (EFN) è caratterizzata da crisi motorie che insorgono durante il sonno. Scopo del progetto è studiare le cause fisiopatologiche e morfo-funzionali che sottendono ai fenomeni motori nei pazienti con EFN e identificare alterazioni strutturali e/o metaboliche mediante tecniche avanzate di Risonanza Magnetica (RM). Abbiamo raccolto una casistica di pazienti con EFN afferenti al Centro Epilessia e dei Disturbi del Sonno del Dipartimento di Scienze Neurologiche, Università di Bologna. Ad ogni paziente è stato associato un controllo sano di età (± 5 anni) e sesso corrispondente. Tutti sono stati studiati mediante tecniche avanzate di RM comprendenti Spettroscopia del protone (1H-MRS), Tensore di diffusione ed imaging 3D ad alta risoluzione per analisi morfometriche. In particolare, la 1H-MRS è stata effettuata su due volumi di interesse localizzati nei talami e nel giro del cingolo anteriore. Sono stati inclusi nell’analisi finale 19 pazienti (7 M), età media 34 anni (range 19-50) e 14 controlli (6 M) età media 30 anni (range 19-40). A livello del cingolo anteriore il rapporto della concentrazione di N-Acetil-Aspartato rispetto alla Creatina (NAA/Cr) è risultato significativamente ridotto nei pazienti rispetto ai controlli (p=0,021). Relativamente all’analisi di correlazione, l'analisi tramite modelli di regressione multipla ha evidenziato che il rapporto NAA/Cr nel cingolo anteriore nei pazienti correlava con la frequenza delle crisi (p=0,048), essendo minore nei pazienti con crisi plurisettimanali/plurigiornaliere. Per interpretare il dato ottenuto è possibile solo fare delle ipotesi. L’NAA è un marker di integrità, densità e funzionalità neuronale. E’ possibile che alla base della EFN ci siano alterazioni metaboliche tessutali in precise strutture come il giro del cingolo anteriore. Questo apre nuove possibilità sull’utilizzo di strumenti di indagine basati sull’analisi di biosegnali, per caratterizzare aree coinvolte nella genesi della EFN ancora largamente sconosciute e chiarire ulteriormente l’eziologia di questo tipo di epilessia.

Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

TDOA for Narrow-band Signal with Low Sampling Rate and Imperfect Synchronization

Time-based localization techniques such as multilateration are favoured for positioning to wide-band signals. Applying the same techniques with narrow-band signals such as GSM is not so trivial. The process is challenged by the needs of synchronization accuracy and timestamp resolution both in the nanoseconds range. We propose approaches to deal with both challenges. On the one hand, we introduce a method to eliminate the negative effect of synchronization offset on time measurements. On the other hand, we propose timestamps with nanoseconds accuracy by using timing information from the signal processing chain. For a set of experiments, ranging from sub-urban to indoor environments, we show that our proposed approaches are able to improve the localization accuracy of TDOA approaches by several factors. We are even able to demonstrate errors as small as 10 meters for outdoor settings with narrow-band signals.

Exploring differences between phonetic classes in Sleep Apnoea Syndrome Patients using automatic speech processing techniques

This work is part of an on-going collaborative project between the medical and signal processing communities to promote new research efforts on automatic OSA (Obstructive Apnea Syndrome) diagnosis. In this paper, we explore the differences noted in phonetic classes (interphoneme) across groups (control/apnoea) and analyze their utility for OSA detection

Rectangular room dimensions estimation using narrowband signal and sectorized antennas

A system for estimation of unknown rectangular room dimensions based on two radio transceivers, both capable of full duplex operations, is presented. The approach is based on CIR measurements taken at the same place where the signal is transmitted (generated), commonly known as self- to-self CIR. Another novelty is the receiver antenna design which consists of eight sectorized antennas with 45° aperture in the horizontal plane, whose total coverage corresponds to the isotropic one. The dimensions of a rectangular room are reconstructed directly from radio impulse responses by extracting the information regarding features like round trip time, received signal strength and reverberation time. Using radar approach the estimation of walls and corners positions are derived. Additionally, the analysis of the absorption coefficient of the test environment is conducted and a typical coefficient for office room with furniture is proposed. Its accuracy is confirmed through the results of volume estimation. Tests using measured data were performed, and the simulation results confirm the feasibility of the approach.

Photonic processing subsystem based on visual cortex architecture

Optical signal processing in any living being is more complex than the one obtained in artificial systems. Cortex architecture, although only partly known, gives some useful ideas to be employed in communications. To analyze some of these structures is the objective of this paper. One of the main possibilities reported is handling signals in a parallel way. As it is shown, according to the signal characteristics each signal impinging onto a single input may be routed to a different output. At the same time, identical signals, coming to different inputs, may be routed to the same output without internal conflicts. This is due to the change of some of their characteristics in the way out when going through the intermediate levels. The simulation of this architecture is based on simple logic cells. The basis for the proposed architecture is the five layers of the mammalian retina and the first levels of the visual cortex.

Integration of embedded data processing algorithms inside PAMELA devices

PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

Análisis espectral de señales cardiacas mediante frecuencia dominante

La Ingeniería Biomédica surgió en la década de 1950 como una fascinante mezcla interdisciplinaria, en la cual la ingeniería, la biología y la medicina aunaban esfuerzos para analizar y comprender distintas enfermedades. Las señales existentes en este área deben ser analizadas e interpretadas, más allá de las capacidades limitadas de la simple vista y la experiencia humana. Aquí es donde el procesamiento digital de la señal se postula como una herramienta indispensable para extraer la información relevante oculta en dichas señales. La electrocardiografía fue una de las primeras áreas en las que se aplicó el procesado digital de señales hace más de 50 años. Las señales electrocardiográficas continúan siendo, a día de hoy, objeto de estudio por parte de cardiólogos e ingenieros. En esta área, las técnicas de procesamiento de señal han ayudado a encontrar información oculta a simple vista que ha cambiado la forma de tratar ciertas enfermedades que fueron ya diagnosticadas previamente. Desde entonces, se han desarrollado numerosas técnicas de procesado de señales electrocardiográficas, pudiéndose resumir estas en tres grandes categorías: análisis tiempo-frecuencia, análisis de organización espacio-temporal y separación de la actividad atrial del ruido y las interferencias. Este proyecto se enmarca dentro de la primera categoría, análisis tiempo-frecuencia, y en concreto dentro de lo que se conoce como análisis de frecuencia dominante, la cual se va a aplicar al análisis de señales de fibrilación auricular. El proyecto incluye una parte teórica de análisis y desarrollo de algoritmos de procesado de señal, y una parte práctica, de programación y simulación con Matlab. Matlab es una de las herramientas fundamentales para el procesamiento digital de señales por ordenador, la cual presenta importantes funciones y utilidades para el desarrollo de proyectos en este campo. Por ello, se ha elegido dicho software como herramienta para la implementación del proyecto. ABSTRACT. Biomedical Engineering emerged in the 1950s as a fascinating interdisciplinary blend, in which engineering, biology and medicine pooled efforts to analyze and understand different diseases. Existing signals in this area should be analyzed and interpreted, beyond the limited capabilities of the naked eye and the human experience. This is where the digital signal processing is postulated as an indispensable tool to extract the relevant information hidden in these signals. Electrocardiography was one of the first areas where digital signal processing was applied over 50 years ago. Electrocardiographic signals remain, even today, the subject of close study by cardiologists and engineers. In this area, signal processing techniques have helped to find hidden information that has changed the way of treating certain diseases that were already previously diagnosed. Since then, numerous techniques have been developed for processing electrocardiographic signals. These methods can be summarized into three categories: time-frequency analysis, analysis of spatio-temporal organization and separation of atrial activity from noise and interferences. This project belongs to the first category, time-frequency analysis, and specifically to what is known as dominant frequency analysis, which is one of the fundamental tools applied in the analysis of atrial fibrillation signals. The project includes a theoretical part, related to the analysis and development of signal processing algorithms, and a practical part, related to programming and simulation using Matlab. Matlab is one of the fundamental tools for digital signal processing, presenting significant functions and advantages for the development of projects in this field. Therefore, we have chosen this software as a tool for project implementation.

Information processing in the human brain: magnetoencephalographic approach.

Rapid progress in effective methods to image brain functions has revolutionized neuroscience. It is now possible to study noninvasively in humans neural processes that were previously only accessible in experimental animals and in brain-injured patients. In this endeavor, positron emission tomography has been the leader, but the superconducting quantum interference device-based magnetoencephalography (MEG) is gaining a firm role, too. With the advent of instruments covering the whole scalp, MEG, typically with 5-mm spatial and 1-ms temporal resolution, allows neuroscientists to track cortical functions accurately in time and space. We present five representative examples of recent MEG studies in our laboratory that demonstrate the usefulness of whole-head magnetoencephalography in investigations of spatiotemporal dynamics of cortical signal processing.

Chemotactic signal integration in bacteria.

Chemotactic signaling in Escherichia coli involves transmission of both negative and positive signals. In order to examine mechanisms of signal processing, behavioral responses to dual inputs have been measured by using photoactivable "caged" compounds, computer video analysis, and chemoreceptor deletion mutants. Signaling from Tar and Tsr, two receptors that sense amino acids and pH, was studied. In a Tar deletion mutant the photoactivated release of protons, a Tsr repellent, and of serine, a Tsr attractant, in separate experiments at pH 7.0 resulted in tumbling (negative) or smooth-swimming (positive) responses in ca. 50 and 140 ms, respectively. Simultaneous photorelease of protons and serine resulted in a single tumbling or smooth-swimming response, depending on the relative amounts of the two effectors. In contrast, in wild-type E. coli, proton release at pH 7.0 resulted in a biphasic response that was attributed to Tsr-mediated tumbling followed by Tar-mediated smooth-swimming. In wild-type E. coli at more alkaline pH values the Tar-mediated signal was stronger than the Tsr signal, resulting in a strong smooth-swimming response preceded by a diminished tumbling response. These observations imply that (i) a single receptor time-averages the binding of different chemotactic ligands generating a single response; (ii) ligand binding to different receptors can result in a nonintegrated response with the tumbling response preceding the smooth-swimming response; (iii) however, chemotactic signals of different intensities derived from different receptors can also result in an apparently integrated response; and (iv) the different chemotactic responses to protons at neutral and alkaline pH may contribute to E. coli migration toward neutrality.

Digital filtering using burst processing techniques /

Thesis (M. S.)--University of Illinois at Urbana-Champaign.

Direct support and general support maintenance manual : translator, signal data CV-3098/G (NSN 5895-00-237-2472) for satellite communication terminal AN/FSC-78(V).

"June 1978."

High-resolution spatial processing in underwater acoustics /

Mode of access: Internet.