Context-aware home monitoring system for Parkinson's disease patietns : ambient and werable sensing for freezing of gait detection

Tesi en modalitat de cotutela: Universitat Politècnica de Catalunya i Technische Universiteit Eindhoven. This PhD Thesis has been developed in the framework of, and according to, the rules of the Erasmus Mundus Joint Doctorate on Interactive and Cognitive Environments EMJD ICE [FPA no. 2010-0012]Parkinson’s disease (PD). It is characterized by brief episodes of inability to step, or by extremely short steps that typically occur on gait initiation or on turning while walking. The consequences of FOG are aggravated mobility and higher affinity to falls, which have a direct effect on the quality of life of the individual. There does not exist completely effective pharmacological treatment for the FOG phenomena. However, external stimuli, such as lines on the floor or rhythmic sounds, can focus the attention of a person who experiences a FOG episode and help her initiate gait. The optimal effectiveness in such approach, known as cueing, is achieved through timely activation of a cueing device upon the accurate detection of a FOG episode. Therefore, a robust and accurate FOG detection is the main problem that needs to be solved when developing a suitable assistive technology solution for this specific user group. This thesis proposes the use of activity and spatial context of a person as the means to improve the detection of FOG episodes during monitoring at home. The thesis describes design, algorithm implementation and evaluation of a distributed home system for FOG detection based on multiple cameras and a single inertial gait sensor worn at the waist of the patient. Through detailed observation of collected home data of 17 PD patients, we realized that a novel solution for FOG detection could be achieved by using contextual information of the patient’s position, orientation, basic posture and movement on a semantically annotated two-dimensional (2D) map of the indoor environment. We envisioned the future context-aware system as a network of Microsoft Kinect cameras placed in the patient’s home that interacts with a wearable inertial sensor on the patient (smartphone). Since the hardware platform of the system constitutes from the commercial of-the-shelf hardware, the majority of the system development efforts involved the production of software modules (for position tracking, orientation tracking, activity recognition) that run on top of the middle-ware operating system in the home gateway server. The main component of the system that had to be developed is the Kinect application for tracking the position and height of multiple people, based on the input in the form of 3D point cloud data. Besides position tracking, this software module also provides mapping and semantic annotation of FOG specific zones on the scene in front of the Kinect. One instance of vision tracking application is supposed to run for every Kinect sensor in the system, yielding potentially high number of simultaneous tracks. At any moment, the system has to track one specific person - the patient. To enable tracking of the patient between different non-overlapped cameras in the distributed system, a new re-identification approach based on appearance model learning with one-class Support Vector Machine (SVM) was developed. Evaluation of the re-identification method was conducted on a 16 people dataset in a laboratory environment. Since the patient orientation in the indoor space was recognized as an important part of the context, the system necessitated the ability to estimate the orientation of the person, expressed in the frame of the 2D scene on which the patient is tracked by the camera. We devised method to fuse position tracking information from the vision system and inertial data from the smartphone in order to obtain patient’s 2D pose estimation on the scene map. Additionally, a method for the estimation of the position of the smartphone on the waist of the patient was proposed. Position and orientation estimation accuracy were evaluated on a 12 people dataset. Finally, having available positional, orientation and height information, a new seven-class activity classification was realized using a hierarchical classifier that combines height-based posture classifier with translational and rotational SVM movement classifiers. Each of the SVM movement classifiers and the joint hierarchical classifier were evaluated in the laboratory experiment with 8 healthy persons. The final context-based FOG detection algorithm uses activity information and spatial context information in order to confirm or disprove FOG detected by the current state-of-the-art FOG detection algorithm (which uses only wearable sensor data). A dataset with home data of 3 PD patients was produced using two Kinect cameras and a smartphone in synchronized recording. The new context-based FOG detection algorithm and the wearable-only FOG detection algorithm were both evaluated with the home dataset and their results were compared. The context-based algorithm very positively influences the reduction of false positive detections, which is expressed through achieved higher specificity. In some cases, context-based algorithm also eliminates true positive detections, reducing sensitivity to the lesser extent. The final comparison of the two algorithms on the basis of their sensitivity and specificity, shows the improvement in the overall FOG detection achieved with the new context-aware home system.Esta tesis propone el uso de la actividad y el contexto espacial de una persona como medio para mejorar la detección de episodios de FOG (Freezing of gait) durante el seguimiento en el domicilio. La tesis describe el diseño, implementación de algoritmos y evaluación de un sistema doméstico distribuido para detección de FOG basado en varias cámaras y un único sensor de marcha inercial en la cintura del paciente. Mediante de la observación detallada de los datos caseros recopilados de 17 pacientes con EP, nos dimos cuenta de que se puede lograr una solución novedosa para la detección de FOG mediante el uso de información contextual de la posición del paciente, orientación, postura básica y movimiento anotada semánticamente en un mapa bidimensional (2D) del entorno interior. Imaginamos el futuro sistema de consciencia del contexto como una red de cámaras Microsoft Kinect colocadas en el hogar del paciente, que interactúa con un sensor de inercia portátil en el paciente (teléfono inteligente). Al constituirse la plataforma del sistema a partir de hardware comercial disponible, los esfuerzos de desarrollo consistieron en la producción de módulos de software (para el seguimiento de la posición, orientación seguimiento, reconocimiento de actividad) que se ejecutan en la parte superior del sistema operativo del servidor de puerta de enlace de casa. El componente principal del sistema que tuvo que desarrollarse es la aplicación Kinect para seguimiento de la posición y la altura de varias personas, según la entrada en forma de punto 3D de datos en la nube. Además del seguimiento de posición, este módulo de software también proporciona mapeo y semántica. anotación de zonas específicas de FOG en la escena frente al Kinect. Se supone que una instancia de la aplicación de seguimiento de visión se ejecuta para cada sensor Kinect en el sistema, produciendo un número potencialmente alto de pistas simultáneas. En cualquier momento, el sistema tiene que rastrear a una persona específica - el paciente. Para habilitar el seguimiento del paciente entre diferentes cámaras no superpuestas en el sistema distribuido, se desarrolló un nuevo enfoque de re-identificación basado en el aprendizaje de modelos de apariencia con one-class Suport Vector Machine (SVM). La evaluación del método de re-identificación se realizó con un conjunto de datos de 16 personas en un entorno de laboratorio. Dado que la orientación del paciente en el espacio interior fue reconocida como una parte importante del contexto, el sistema necesitaba la capacidad de estimar la orientación de la persona, expresada en el marco de la escena 2D en la que la cámara sigue al paciente. Diseñamos un método para fusionar la información de seguimiento de posición del sistema de visión y los datos de inercia del smartphone para obtener la estimación de postura 2D del paciente en el mapa de la escena. Además, se propuso un método para la estimación de la posición del Smartphone en la cintura del paciente. La precisión de la estimación de la posición y la orientación se evaluó en un conjunto de datos de 12 personas. Finalmente, al tener disponible información de posición, orientación y altura, se realizó una nueva clasificación de actividad de seven-class utilizando un clasificador jerárquico que combina un clasificador de postura basado en la altura con clasificadores de movimiento SVM traslacional y rotacional. Cada uno de los clasificadores de movimiento SVM y el clasificador jerárquico conjunto se evaluaron en el experimento de laboratorio con 8 personas sanas. El último algoritmo de detección de FOG basado en el contexto utiliza información de actividad e información de texto espacial para confirmar o refutar el FOG detectado por el algoritmo de detección de FOG actual. El algoritmo basado en el contexto influye muy positivamente en la reducción de las detecciones de falsos positivos, que se expresa a través de una mayor especificidadPostprint (published version

Context-aware home monitoring system for Parkinson's disease patietns : ambient and werable sensing for freezing of gait detection

Parkinson’s disease (PD). It is characterized by brief episodes of inability to step, or by extremely short steps that typically occur on gait initiation or on turning while walking. The consequences of FOG are aggravated mobility and higher affinity to falls, which have a direct effect on the quality of life of the individual. There does not exist completely effective pharmacological treatment for the FOG phenomena. However, external stimuli, such as lines on the floor or rhythmic sounds, can focus the attention of a person who experiences a FOG episode and help her initiate gait. The optimal effectiveness in such approach, known as cueing, is achieved through timely activation of a cueing device upon the accurate detection of a FOG episode. Therefore, a robust and accurate FOG detection is the main problem that needs to be solved when developing a suitable assistive technology solution for this specific user group. This thesis proposes the use of activity and spatial context of a person as the means to improve the detection of FOG episodes during monitoring at home. The thesis describes design, algorithm implementation and evaluation of a distributed home system for FOG detection based on multiple cameras and a single inertial gait sensor worn at the waist of the patient. Through detailed observation of collected home data of 17 PD patients, we realized that a novel solution for FOG detection could be achieved by using contextual information of the patient’s position, orientation, basic posture and movement on a semantically annotated two-dimensional (2D) map of the indoor environment. We envisioned the future context-aware system as a network of Microsoft Kinect cameras placed in the patient’s home that interacts with a wearable inertial sensor on the patient (smartphone). Since the hardware platform of the system constitutes from the commercial of-the-shelf hardware, the majority of the system development efforts involved the production of software modules (for position tracking, orientation tracking, activity recognition) that run on top of the middle-ware operating system in the home gateway server. The main component of the system that had to be developed is the Kinect application for tracking the position and height of multiple people, based on the input in the form of 3D point cloud data. Besides position tracking, this software module also provides mapping and semantic annotation of FOG specific zones on the scene in front of the Kinect. One instance of vision tracking application is supposed to run for every Kinect sensor in the system, yielding potentially high number of simultaneous tracks. At any moment, the system has to track one specific person - the patient. To enable tracking of the patient between different non-overlapped cameras in the distributed system, a new re-identification approach based on appearance model learning with one-class Support Vector Machine (SVM) was developed. Evaluation of the re-identification method was conducted on a 16 people dataset in a laboratory environment. Since the patient orientation in the indoor space was recognized as an important part of the context, the system necessitated the ability to estimate the orientation of the person, expressed in the frame of the 2D scene on which the patient is tracked by the camera. We devised method to fuse position tracking information from the vision system and inertial data from the smartphone in order to obtain patient’s 2D pose estimation on the scene map. Additionally, a method for the estimation of the position of the smartphone on the waist of the patient was proposed. Position and orientation estimation accuracy were evaluated on a 12 people dataset. Finally, having available positional, orientation and height information, a new seven-class activity classification was realized using a hierarchical classifier that combines height-based posture classifier with translational and rotational SVM movement classifiers. Each of the SVM movement classifiers and the joint hierarchical classifier were evaluated in the laboratory experiment with 8 healthy persons. The final context-based FOG detection algorithm uses activity information and spatial context information in order to confirm or disprove FOG detected by the current state-of-the-art FOG detection algorithm (which uses only wearable sensor data). A dataset with home data of 3 PD patients was produced using two Kinect cameras and a smartphone in synchronized recording. The new context-based FOG detection algorithm and the wearable-only FOG detection algorithm were both evaluated with the home dataset and their results were compared. The context-based algorithm very positively influences the reduction of false positive detections, which is expressed through achieved higher specificity. In some cases, context-based algorithm also eliminates true positive detections, reducing sensitivity to the lesser extent. The final comparison of the two algorithms on the basis of their sensitivity and specificity, shows the improvement in the overall FOG detection achieved with the new context-aware home system.Esta tesis propone el uso de la actividad y el contexto espacial de una persona como medio para mejorar la detección de episodios de FOG (Freezing of gait) durante el seguimiento en el domicilio. La tesis describe el diseño, implementación de algoritmos y evaluación de un sistema doméstico distribuido para detección de FOG basado en varias cámaras y un único sensor de marcha inercial en la cintura del paciente. Mediante de la observación detallada de los datos caseros recopilados de 17 pacientes con EP, nos dimos cuenta de que se puede lograr una solución novedosa para la detección de FOG mediante el uso de información contextual de la posición del paciente, orientación, postura básica y movimiento anotada semánticamente en un mapa bidimensional (2D) del entorno interior. Imaginamos el futuro sistema de consciencia del contexto como una red de cámaras Microsoft Kinect colocadas en el hogar del paciente, que interactúa con un sensor de inercia portátil en el paciente (teléfono inteligente). Al constituirse la plataforma del sistema a partir de hardware comercial disponible, los esfuerzos de desarrollo consistieron en la producción de módulos de software (para el seguimiento de la posición, orientación seguimiento, reconocimiento de actividad) que se ejecutan en la parte superior del sistema operativo del servidor de puerta de enlace de casa. El componente principal del sistema que tuvo que desarrollarse es la aplicación Kinect para seguimiento de la posición y la altura de varias personas, según la entrada en forma de punto 3D de datos en la nube. Además del seguimiento de posición, este módulo de software también proporciona mapeo y semántica. anotación de zonas específicas de FOG en la escena frente al Kinect. Se supone que una instancia de la aplicación de seguimiento de visión se ejecuta para cada sensor Kinect en el sistema, produciendo un número potencialmente alto de pistas simultáneas. En cualquier momento, el sistema tiene que rastrear a una persona específica - el paciente. Para habilitar el seguimiento del paciente entre diferentes cámaras no superpuestas en el sistema distribuido, se desarrolló un nuevo enfoque de re-identificación basado en el aprendizaje de modelos de apariencia con one-class Suport Vector Machine (SVM). La evaluación del método de re-identificación se realizó con un conjunto de datos de 16 personas en un entorno de laboratorio. Dado que la orientación del paciente en el espacio interior fue reconocida como una parte importante del contexto, el sistema necesitaba la capacidad de estimar la orientación de la persona, expresada en el marco de la escena 2D en la que la cámara sigue al paciente. Diseñamos un método para fusionar la información de seguimiento de posición del sistema de visión y los datos de inercia del smartphone para obtener la estimación de postura 2D del paciente en el mapa de la escena. Además, se propuso un método para la estimación de la posición del Smartphone en la cintura del paciente. La precisión de la estimación de la posición y la orientación se evaluó en un conjunto de datos de 12 personas. Finalmente, al tener disponible información de posición, orientación y altura, se realizó una nueva clasificación de actividad de seven-class utilizando un clasificador jerárquico que combina un clasificador de postura basado en la altura con clasificadores de movimiento SVM traslacional y rotacional. Cada uno de los clasificadores de movimiento SVM y el clasificador jerárquico conjunto se evaluaron en el experimento de laboratorio con 8 personas sanas. El último algoritmo de detección de FOG basado en el contexto utiliza información de actividad e información de texto espacial para confirmar o refutar el FOG detectado por el algoritmo de detección de FOG actual. El algoritmo basado en el contexto influye muy positivamente en la reducción de las detecciones de falsos positivos, que se expresa a través de una mayor especificida

Importance of Interleukin 6 in Pathogenesis of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn’s disease (CD), is an uncontrolled chronic inflammation of the gastrointestinal tract caused by an interaction of diverse genes and environmental factors. There is growing evidence that cytokine production plays an important role in IBD. One of the key roles in signaling pathway in development of IBD is performed by interleukin 6 (IL-6), although molecular mechanism of this pathway is not yet fully understood. In order to assess the clinical relevance of IL-6 serum concentration in patients with CD and UC we performed cross-sectional, case-control study of IL-6 levels in patients’ and healthy blood donors’ sera. A total of 100 CD and UC patients and 71 healthy blood donors were investigated. Clinical activity of CD and UC was evaluated using the Crohn\u27s disease activity index and Truelove-Witt\u27s criteria, respectively. Quantitative assessment of serum IL-6 was performed with solid-phase, enzyme-labeled, chemiluminescent sequential immunometric assay. Our results indicate that serum IL-6 is a clinically relevant parameter for CD and UC that strongly correlates with inflammatory activity of disease. We confirmed and extended the role of cytokine production patterns for IBD presentation in Croatian population

Polymorphisms of Interleukin-23 Receptor in Patients with Inflammatory Bowel Disease in a Croatian Tertiary Center

The Interleukin-23 signalling pathway is important for the differentiation of TH17 lymphocytes and is involved in the pathogenesis of Inflammatory bowel disease. Polymorphisms in the IL-23 receptor gene were previously found to be associated with Inflammatory bowel disease in various populations. The aim of this study was to determine whether the specific rs11209026 and rs7530511 single-nucleotide polymorphisms in the Interleukin-23 receptor gene are associated with Crohn’s disease and ulcerative colitis in a Croatian patient population. A total of 50 patients with Crohn’s disease and 93 patients with ulcerative colitis, as well as 99 healthy control subjects were included in the study. The results deter- mined a significantly higher occurrence of rs11209026 in control group compared to patients with inflammatory bowel disease, suggesting a protective effect of this polymorphism. The rs11209026 variant was strongly associated with Crohn’s disease, but it was absent in ulcerative colitis. However, there was no significant association between the rs7530511 poly- morphism with either ulcerative colitis or Crohn’s disease. Associations presented in this study give potentially impor- tant insight into the roles of specific Interleukin-23 receptor polymorphisms in Crohn’s disease pathogenesis in the Cro- atian population

Importance of Interleukin 6 in Pathogenesis of Inflammatory Bowel Disease

Inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn’s disease (CD), is an uncontrolled chronic inflammation of the gastrointestinal tract caused by an interaction of diverse genes and environmental factors. There is growing evidence that cytokine production plays an important role in IBD. One of the key roles in signaling pathway in development of IBD is performed by interleukin 6 (IL-6), although molecular mechanism of this pathway is not yet fully understood. In order to assess the clinical relevance of IL-6 serum concentration in patients with CD and UC we performed cross-sectional, case-control study of IL-6 levels in patients’ and healthy blood donors’ sera. A total of 100 CD and UC patients and 71 healthy blood donors were investigated. Clinical activity of CD and UC was evaluated using the Crohn\u27s disease activity index and Truelove-Witt\u27s criteria, respectively. Quantitative assessment of serum IL-6 was performed with solid-phase, enzyme-labeled, chemiluminescent sequential immunometric assay. Our results indicate that serum IL-6 is a clinically relevant parameter for CD and UC that strongly correlates with inflammatory activity of disease. We confirmed and extended the role of cytokine production patterns for IBD presentation in Croatian population

Interakcija između interleukina-6, C-reaktivnog proteina i interleukina-6 (-174) G/C polimorfizma u patogenezi Crohnove bolesti i ulceroznog kolitisa

Inflammatory bowel diseases are multifactorial disorders the clinical manifestation of which depends on the interaction among immune response, genetic and environmental factors. There is growing evidence that cytokines and gene polymorphisms have an important role in disease pathogenesis in various populations although molecular mechanism of their signaling and interactions is not fully understood yet. The present study aimed at exploring the effects of interleukin-6, C-reactive protein and interleukin-6 rs1800795 polymorphism on the development of Crohn’s disease, ulcerative colitis and inflammatory bowel diseases overall and at determining differences between inflammatory bowel disease patients and healthy controls. A total of 132 inflammatory bowel disease patients and 71 healthy blood donors were investigated. In order to assess the clinical relevance of interleukin-6 and C-reactive protein serum concentration and interleukin-6 rs1800795 single nucleotide polymorphism in patients with Crohn’s disease and ulcerative colitis, we performed a cross-sectional, case-control study. Quantitative assessment of serum interleukin-6 and C-reactive protein was performed with solid-phase, enzyme-labeled, chemiluminescent sequential immunometric and immunoturbidimetric assay, respectively. A real-time fluorescence resonance energy transfer-based method on a LightCyclerTM PCR 1.2 was used for genotyping of IL-6 rs1800795 polymorphism. Both interleukin-6 and C-reactive protein serum levels were elevated in Crohn’s disease and ulcerative colitis patients. Positive correlations were observed between C-reactive protein and interleukin-6 serum concentration and ulcerative colitis activity index as measured by modified Truelove-Witt’s severity index scale. C-reactive protein serum level was higher in Crohn’s disease patients without intestinal resection than in Crohn’s disease patients with prior intestinal resection. In ulcerative colitis patients, interleukin-6 and C-reactive protein serum levels were statistically significantly higher in CC interleukin-6 genotype in comparison to GG+GC genotype. Analysis of the promoter region of the interleukin-6 rs1800795 gene polymorphism showed no statistically significant difference in allele frequency either between inflammatory bowel disease patients and healthy controls or between the two inflammatory bowel disease phenotypes and healthy controls. Associations presented in this study give a potentially important insight into the role of interleukin-6 and C-reactive protein signaling and interleukin-6 polymorphism in the pathogenesis of Crohn’s disease and ulcerative colitis disease.Upalne bolesti crijeva predstavljaju multifaktorski poremećaj klinička manifestacija kojega ovisi o interakciji imunog odgovora te genetskih i okolišnih čimbenika. Rezultati više novijih istraživanja upućuju na ulogu citokina i polimorfizama gena u patogenezi bolesti u različitim populacijama, iako molekularni mehanizmi njihova singaliziranja i interakcije još nisu dovoljno poznati. Cilj ovoga istraživanja bio je ispitati učinke interleukina-6, C-reaktivnog proteina i interleukin-6 rs1800795 na razvoj Crohnove bolesti, ulceroznoga kolitisa i upalnih bolesti crijeva općenito te utvrditi razlike između skupine ispitanika oboljelih od upalnih bolesti crijeva i kontrolne skupine ispitanika. U istraživanje je uključeno ukupno 132 oboljela od upalnih bolesti crijeva i 71 zdravi davatelj krvi. Serumska koncentracija interleukina-6 određena je kemiluminiscentnom sekvencijskom imunometričnom, a koncentracija C-reaktivnog proteina imunoturbidimetrijskom metodom. Analiza polimorfizma rs1800795 provodila se na uređaju LightCyclerTM PCR 1.2 u stvarnome vremenu temeljem prijenosa energije uslijed fluorescentne rezonancije. Serumske koncentracije interleukina-6 i C-reaktivnoga proteina bile su povišene i u oboljelih od Crohnove bolesti i oboljelih od ulceroznoga kolitisa. Utvrđene su pozitivne korelacije između serumskih koncentracija C-reaktivnoga proteina i interleukina-6 i indeksa aktivnosti ulceroznoga kolitisa mjerenoga prema ljestvici MTWSI. Serumska koncentracija C-reaktivnog proteina bila je viša u oboljelih od Crohnove bolesti bez prethodne resekcije crijeva u usporedbi s oboljelima od Crohnove bolesti s prethodnom resekcijom crijeva. U oboljelih od ulceroznoga kolitisa serumske koncentracije interleukina-6 i C-reaktivnog proteina bile su statistički značajno više kod CC genotipa interleukina-6 u usporedbi s genotipom GG+GC. Analizom polimorfizma promotorske regije IL-6 rs1800795 nisu uočene razlike u učestalosti alela između oboljelih od Crohnove bolelsti, oboljelih od ulceroznoga kolitisa i kontrolne skupine ispitanika, ni razlike između kontrolne skupine ispitanika i oboljelih od upalnih bolesti crijeva općenito. Rezultati ove studije pružaju potencijalno važan uvid u ulogu signaliziranja interleukina-6 i C-reaktivnoga proteina te polimorfizma interleukina-6 u patogenezi Crohnove bolesti i ulceroznoga kolitisa

A Machine Condition Monitoring System Based on Generic Technologies

Upotreba generičkog hardvera omogućuje da se težište razvoja sustava motrenja prebaci na stranu izrade softvera. U radu je opisan sustav motrenja rotacijskih strojeva zasnovan na navedenom konceptu. Uvodno je izrađen pregled značaja sustava motrenja rotacijskih strojeva u prediktivnom održavanju industrijske opreme, te su analizirane značajke i mogućnosti suvremenih sustava motrenja. Dobivena saznanja iskorištena su u procesu dizajna sustava. Dizajn sustava rezultirao je izgradnjom konceptualne strukture sustava motrenja. U toj strukturi je jedinica za prihvat mjernih signala i obradu podataka, prepoznata kao ključni dio sustava motrenja. Opisan je izbor softverske i hardverske platforme procesne jedinice, kao i tipovi mjernih davača koji mogu biti korišteni za motrenje rotacijskih električnih strojeva. Opisani su idejno rješenje i struktura glavnog programa procesne jedinice, kao i ugrađeni algoritmi za pojedine obrade karakteristične za sustave motrenja rotacijskih strojeva. Ukratko su opisani korisničko sučelje sustava i dostupni oblici grafičke prezentacije prikupljenih podataka. U opisu korisničkoga sučelja korišteni su grafički prikazi izmjerenih vrijednosti prikupljenih procesnom jedinicom prilikom mjerenja na sinkronom generatoru u elektrani, čime je pokazana funkcionalnost ostvarenog sustava motrenja.The use of generic hardware enables us to base design of new condition monitoring systems on software development. In this thesis, the rotational machine condition monitoring system based on the former concept is described. At the beginning of the thesis, the overview of the importance of the machine condition monitoring systems in the prediction maintenance of the industrial equipment is given. Additionally, the features of the present machine condition monitoring systems are analyzed. Gathered knowledge is then exploited in the phase of system design. System design phase resulted in conceptual structure of the new machine condition monitoring system. In the given structure, unit for signal acquisition and data processing is recognized as the key part of the system. Description of the selection process of the software and hardware platform for the processing unit, along with the overview of the measurement sensors used for rotational machine condition monitoring, is given. The conceptual solution and the final configuration of the main program for the processing unit are given, along with the description of embedded algorithms distinctive for the machine condition monitoring systems. Short description of the system user face and available graphical displays for information presentation is given. For the description of the user face graphical displays, the measured values obtained by the processing unit during measurements on the synchronous generator in the power plant are used. Measurement results are used to show the obtained functionality of the produced machine condition monitoring system

Turquie contemporaine Contemporary Turquey

Le séminaire sur la Turquie contemporaine a deux objectifs principaux : 1.) permettre aux étudiants de mieux tirer parti leur séjour de mobilité en abordant avec des spécialistes une série de thématiques fondamentales pour la compréhension de la Turquie contemporaine et 2.) fournir un cadre d’accueil méthodologique et un centre de ressources pour la préparation d’un travail de recherche sur la Turquie contemporaine