845 resultados para Intelligent Driver Training System


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The use of the SenseWear™ armband (SWA), an objective monitor of physical activity, is a relatively new device used by researchers to measure energy expenditure. These monitors are practical, relatively inexpensive and easy-to-use. The aim of the present study was to assess the validity of SWAs for the measurement of energy expenditure (EE) in circuit resistance training (CRT) at three different intensities in moderately active, healthy subjects. The study subjects (17 females, 12 males) undertook CRT at 30, 50 and 70% of the 15 repetition maximum for each exercise component wearing an SWA as well as an Oxycon Mobile (OM) portable metabolic system (a gold standard method for measuring EE). The EE rose as exercise intensity increased, but was underestimated by the SWAs. For women, Bland-Altman plots showed a bias of 1.13 ± 1.48 METs and 32.1 ± 34.0 kcal in favour of the OM system, while for men values of 2.33 ± 1.82 METs and 75.8 ± 50.8 kcal were recorded.

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This paper describes the architecture of a computer system conceived as an intelligent assistant for public transport management. The goal of the system is to help operators of a control center in making strategic decisions about how to solve problems of a fleet of buses in an urban network. The system uses artificial intelligence techniques to simulate the decision processes. In particular, a complex knowledge model has been designed by using advanced knowledge engineering methods that integrates three main tasks: diagnosis, prediction and planning. Finally, the paper describes two particular applications developed following this architecture for the cities of Torino (Italy) and Vitoria (Spain).

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This paper describes the multi-agent organization of a computer system that was designed to assist operators in decision making in the presence of emergencies. The application was developed for the case of emergencies caused by river floods. It operates on real-time receiving data recorded by sensors (rainfall, water levels, flows, etc.) and applies multi-agent techniques to interpret the data, predict the future behavior and recommend control actions. The system includes an advanced knowledge based architecture with multiple symbolic representation with uncertainty models (bayesian networks). This system has been applied and validated at two particular sites in Spain (the Jucar basin and the South basin).

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La Internet de las Cosas (IoT), como parte de la Futura Internet, se ha convertido en la actualidad en uno de los principales temas de investigación; en parte gracias a la atención que la sociedad está poniendo en el desarrollo de determinado tipo de servicios (telemetría, generación inteligente de energía, telesanidad, etc.) y por las recientes previsiones económicas que sitúan a algunos actores, como los operadores de telecomunicaciones (que se encuentran desesperadamente buscando nuevas oportunidades), al frente empujando algunas tecnologías interrelacionadas como las comunicaciones Máquina a Máquina (M2M). En este contexto, un importante número de actividades de investigación a nivel mundial se están realizando en distintas facetas: comunicaciones de redes de sensores, procesado de información, almacenamiento de grandes cantidades de datos (big--‐data), semántica, arquitecturas de servicio, etc. Todas ellas, de forma independiente, están llegando a un nivel de madurez que permiten vislumbrar la realización de la Internet de las Cosas más que como un sueño, como una realidad tangible. Sin embargo, los servicios anteriormente mencionados no pueden esperar a desarrollarse hasta que las actividades de investigación obtengan soluciones holísticas completas. Es importante proporcionar resultados intermedios que eviten soluciones verticales realizadas para desarrollos particulares. En este trabajo, nos hemos focalizado en la creación de una plataforma de servicios que pretende facilitar, por una parte la integración de redes de sensores y actuadores heterogéneas y geográficamente distribuidas, y por otra lado el desarrollo de servicios horizontales utilizando dichas redes y la información que proporcionan. Este habilitador se utilizará para el desarrollo de servicios y para la experimentación en la Internet de las Cosas. Previo a la definición de la plataforma, se ha realizado un importante estudio focalizando no sólo trabajos y proyectos de investigación, sino también actividades de estandarización. Los resultados se pueden resumir en las siguientes aseveraciones: a) Los modelos de datos definidos por el grupo “Sensor Web Enablement” (SWE™) del “Open Geospatial Consortium (OGC®)” representan hoy en día la solución más completa para describir las redes de sensores y actuadores así como las observaciones. b) Las interfaces OGC, a pesar de las limitaciones que requieren cambios y extensiones, podrían ser utilizadas como las bases para acceder a sensores y datos. c) Las redes de nueva generación (NGN) ofrecen un buen sustrato que facilita la integración de redes de sensores y el desarrollo de servicios. En consecuencia, una nueva plataforma de Servicios, llamada Ubiquitous Sensor Networks (USN), se ha definido en esta Tesis tratando de contribuir a rellenar los huecos previamente mencionados. Los puntos más destacados de la plataforma USN son: a) Desde un punto de vista arquitectónico, sigue una aproximación de dos niveles (Habilitador y Gateway) similar a otros habilitadores que utilizan las NGN (como el OMA Presence). b) Los modelos de datos están basado en los estándares del OGC SWE. iv c) Está integrado en las NGN pero puede ser utilizado sin ellas utilizando infraestructuras IP abiertas. d) Las principales funciones son: Descubrimiento de sensores, Almacenamiento de observaciones, Publicacion--‐subscripcion--‐notificación, ejecución remota homogénea, seguridad, gestión de diccionarios de datos, facilidades de monitorización, utilidades de conversión de protocolos, interacciones síncronas y asíncronas, soporte para el “streaming” y arbitrado básico de recursos. Para demostrar las funcionalidades que la Plataforma USN propuesta pueden ofrecer a los futuros escenarios de la Internet de las Cosas, se presentan resultados experimentales de tres pruebas de concepto (telemetría, “Smart Places” y monitorización medioambiental) reales a pequeña escala y un estudio sobre semántica (sistema de información vehicular). Además, se está utilizando actualmente como Habilitador para desarrollar tanto experimentación como servicios reales en el proyecto Europeo SmartSantander (que aspira a integrar alrededor de 20.000 dispositivos IoT). v Abstract Internet of Things, as part of the Future Internet, has become one of the main research topics nowadays; in part thanks to the pressure the society is putting on the development of a particular kind of services (Smart metering, Smart Grids, eHealth, etc.), and by the recent business forecasts that situate some players, like Telecom Operators (which are desperately seeking for new opportunities), at the forefront pushing for some interrelated technologies like Machine--‐to--‐Machine (M2M) communications. Under this context, an important number of research activities are currently taking place worldwide at different levels: sensor network communications, information processing, big--‐ data storage, semantics, service level architectures, etc. All of them, isolated, are arriving to a level of maturity that envision the achievement of Internet of Things (IoT) more than a dream, a tangible goal. However, the aforementioned services cannot wait to be developed until the holistic research actions bring complete solutions. It is important to come out with intermediate results that avoid vertical solutions tailored for particular deployments. In the present work, we focus on the creation of a Service--‐level platform intended to facilitate, from one side the integration of heterogeneous and geographically disperse Sensors and Actuator Networks (SANs), and from the other the development of horizontal services using them and the information they provide. This enabler will be used for horizontal service development and for IoT experimentation. Prior to the definition of the platform, we have realized an important study targeting not just research works and projects, but also standardization topics. The results can be summarized in the following assertions: a) Open Geospatial Consortium (OGC®) Sensor Web Enablement (SWE™) data models today represent the most complete solution to describe SANs and observations. b) OGC interfaces, despite the limitations that require changes and extensions, could be used as the bases for accessing sensors and data. c) Next Generation Networks (NGN) offer a good substrate that facilitates the integration of SANs and the development of services. Consequently a new Service Layer platform, called Ubiquitous Sensor Networks (USN), has been defined in this Thesis trying to contribute to fill in the previous gaps. The main highlights of the proposed USN Platform are: a) From an architectural point of view, it follows a two--‐layer approach (Enabler and Gateway) similar to other enablers that run on top of NGN (like the OMA Presence). b) Data models and interfaces are based on the OGC SWE standards. c) It is integrated in NGN but it can be used without it over open IP infrastructures. d) Main functions are: Sensor Discovery, Observation Storage, Publish--‐Subscribe--‐Notify, homogeneous remote execution, security, data dictionaries handling, monitoring facilities, authorization support, protocol conversion utilities, synchronous and asynchronous interactions, streaming support and basic resource arbitration. vi In order to demonstrate the functionalities that the proposed USN Platform can offer to future IoT scenarios, some experimental results have been addressed in three real--‐life small--‐scale proofs--‐of concepts (Smart Metering, Smart Places and Environmental monitoring) and a study for semantics (in--‐vehicle information system). Furthermore we also present the current use of the proposed USN Platform as an Enabler to develop experimentation and real services in the SmartSantander EU project (that aims at integrating around 20.000 IoT devices).

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La termografía infrarroja (TI) es una técnica no invasiva y de bajo coste que permite, con el simple acto de tomar una fotografía, el registro sin contacto de la energía que irradia el cuerpo humano (Akimov & Son’kin, 2011, Merla et al., 2005, Ng et al., 2009, Costello et al., 2012, Hildebrandt et al., 2010). Esta técnica comenzó a utilizarse en el ámbito médico en los años 60, pero debido a los malos resultados como herramienta diagnóstica y la falta de protocolos estandarizados (Head & Elliot, 2002), ésta se dejó de utilizar en detrimento de otras técnicas más precisas a nivel diagnóstico. No obstante, las mejoras tecnológicas de la TI en los últimos años han hecho posible un resurgimiento de la misma (Jiang et al., 2005, Vainer et al., 2005, Cheng et al., 2009, Spalding et al., 2011, Skala et al., 2012), abriendo el camino a nuevas aplicaciones no sólo centradas en el uso diagnóstico. Entre las nuevas aplicaciones, destacamos las que se desarrollan en el ámbito de la actividad física y el deporte, donde recientemente se ha demostrado que los nuevos avances con imágenes de alta resolución pueden proporcionar información muy interesante sobre el complejo sistema de termorregulación humana (Hildebrandt et al., 2010). Entre las nuevas aplicaciones destacan: la cuantificación de la asimilación de la carga de trabajo físico (Čoh & Širok, 2007), la valoración de la condición física (Chudecka et al., 2010, 2012, Akimov et al., 2009, 2011, Merla et al., 2010), la prevención y seguimiento de lesiones (Hildebrandt et al., 2010, 2012, Badža et al., 2012, Gómez Carmona, 2012) e incluso la detección de agujetas (Al-Nakhli et al., 2012). Bajo estas circunstancias, se acusa cada vez más la necesidad de ampliar el conocimiento sobre los factores que influyen en la aplicación de la TI en los seres humanos, así como la descripción de la respuesta de la temperatura de la piel (TP) en condiciones normales, y bajo la influencia de los diferentes tipos de ejercicio. Por consiguiente, este estudio presenta en una primera parte una revisión bibliográfica sobre los factores que afectan al uso de la TI en los seres humanos y una propuesta de clasificación de los mismos. Hemos analizado la fiabilidad del software Termotracker, así como su reproducibilidad de la temperatura de la piel en sujetos jóvenes, sanos y con normopeso. Finalmente, se analizó la respuesta térmica de la piel antes de un entrenamiento de resistencia, velocidad y fuerza, inmediatamente después y durante un período de recuperación de 8 horas. En cuanto a la revisión bibliográfica, hemos propuesto una clasificación para organizar los factores en tres grupos principales: los factores ambientales, individuales y técnicos. El análisis y descripción de estas influencias deben representar la base de nuevas investigaciones con el fin de utilizar la TI en las mejores condiciones. En cuanto a la reproducibilidad, los resultados mostraron valores excelentes para imágenes consecutivas, aunque la reproducibilidad de la TP disminuyó ligeramente con imágenes separadas por 24 horas, sobre todo en las zonas con valores más fríos (es decir, zonas distales y articulaciones). Las asimetrías térmicas (que normalmente se utilizan para seguir la evolución de zonas sobrecargadas o lesionadas) también mostraron excelentes resultados pero, en este caso, con mejores valores para las articulaciones y el zonas centrales (es decir, rodillas, tobillos, dorsales y pectorales) que las Zonas de Interés (ZDI) con valores medios más calientes (como los muslos e isquiotibiales). Los resultados de fiabilidad del software Termotracker fueron excelentes en todas las condiciones y parámetros. En el caso del estudio sobre los efectos de los entrenamientos de la velocidad resistencia y fuerza en la TP, los resultados muestran respuestas específicas según el tipo de entrenamiento, zona de interés, el momento de la evaluación y la función de las zonas analizadas. Los resultados mostraron que la mayoría de las ZDI musculares se mantuvieron significativamente más calientes 8 horas después del entrenamiento, lo que indica que el efecto del ejercicio sobre la TP perdura por lo menos 8 horas en la mayoría de zonas analizadas. La TI podría ser útil para cuantificar la asimilación y recuperación física después de una carga física de trabajo. Estos resultados podrían ser muy útiles para entender mejor el complejo sistema de termorregulación humano, y por lo tanto, para utilizar la TI de una manera más objetiva, precisa y profesional con visos a mejorar las nuevas aplicaciones termográficas en el sector de la actividad física y el deporte Infrared Thermography (IRT) is a safe, non-invasive and low-cost technique that allows the rapid and non-contact recording of the irradiated energy released from the body (Akimov & Son’kin, 2011; Merla et al., 2005; Ng et al., 2009; Costello et al., 2012; Hildebrandt et al., 2010). It has been used since the early 1960’s, but due to poor results as diagnostic tool and a lack of methodological standards and quality assurance (Head et al., 2002), it was rejected from the medical field. Nevertheless, the technological improvements of IRT in the last years have made possible a resurgence of this technique (Jiang et al., 2005; Vainer et al., 2005; Cheng et al., 2009; Spalding et al., 2011; Skala et al., 2012), paving the way to new applications not only focused on the diagnose usages. Among the new applications, we highlighted those in physical activity and sport fields, where it has been recently proven that a high resolution thermal images can provide us with interesting information about the complex thermoregulation system of the body (Hildebrandt et al., 2010), information than can be used as: training workload quantification (Čoh & Širok, 2007), fitness and performance conditions (Chudecka et al., 2010, 2012; Akimov et al., 2009, 2011; Merla et al., 2010; Arfaoui et al., 2012), prevention and monitoring of injuries (Hildebrandt et al., 2010, 2012; Badža et al., 2012, Gómez Carmona, 2012) and even detection of Delayed Onset Muscle Soreness – DOMS- (Al-Nakhli et al., 2012). Under this context, there is a relevant necessity to broaden the knowledge about factors influencing the application of IRT on humans, and to better explore and describe the thermal response of Skin Temperature (Tsk) in normal conditions, and under the influence of different types of exercise. Consequently, this study presents a literature review about factors affecting the application of IRT on human beings and a classification proposal about them. We analysed the reliability of the software Termotracker®, and also its reproducibility of Tsk on young, healthy and normal weight subjects. Finally, we examined the Tsk thermal response before an endurance, speed and strength training, immediately after and during an 8-hour recovery period. Concerning the literature review, we proposed a classification to organise the factors into three main groups: environmental, individual and technical factors. Thus, better exploring and describing these influence factors should represent the basis of further investigations in order to use IRT in the best and optimal conditions to improve its accuracy and results. Regarding the reproducibility results, the outcomes showed excellent values for consecutive images, but the reproducibility of Tsk slightly decreased with time, above all in the colder Regions of Interest (ROI) (i.e. distal and joint areas). The side-to-side differences (ΔT) (normally used to follow the evolution of some injured or overloaded ROI) also showed highly accurate results, but in this case with better values for joints and central ROI (i.e. Knee, Ankles, Dorsal and Pectoral) than the hottest muscle ROI (as Thigh or Hamstrings). The reliability results of the IRT software Termotracker® were excellent in all conditions and parameters. In the part of the study about the effects on Tsk of aerobic, speed and strength training, the results of Tsk demonstrated specific responses depending on the type of training, ROI, moment of the assessment and the function of the considered ROI. The results showed that most of muscular ROI maintained warmer significant Tsk 8 hours after the training, indicating that the effect of exercise on Tsk last at least 8 hours in most of ROI, as well as IRT could help to quantify the recovery status of the athlete as workload assimilation indicator. Those results could be very useful to better understand the complex skin thermoregulation behaviour, and therefore, to use IRT in a more objective, accurate and professional way to improve the new IRT applications for the physical activity and sport sector.

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Current trends in the fields of artifical intelligence and expert systems are moving towards the exciting possibility of reproducing and simulating human expertise and expert behaviour into a knowledge base, coupled with an appropriate, partially ‘intelligent’, computer code. This paper deals with the quality level prediction in concrete structures using the helpful assistance of an expert system, QL-CONST1, which is able to reason about this specific field of structural engineering. Evidence, hypotheses and factors related to this human knowledge field have been codified into a knowledge base. This knowledge base has been prepared in terms of probabilities of the presence of either hypotheses or evidence and the conditional presence of both. Human experts in the fields of structural engineering and the safety of structures gave their invaluable knowledge and assistance to the construction of the knowledge base. Some illustrative examples for, the validation of the expert system behaviour are included.

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This paper addresses initial efforts to develop a navigation system for ground vehicles supported by visual feedback from a mini aerial vehicle. A visual-based algorithm computes the ground vehicle pose in the world frame, as well as possible obstacles within the ground vehicle pathway. Relying on that information, a navigation and obstacle avoidance system is used to re-plan the ground vehicle trajectory, ensuring an optimal detour. Finally, some experiments are presented employing a unmanned ground vehicle (UGV) and a low cost mini unmanned aerial vehicle (UAV).

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The penalty corner is one of the most important goal plays in field hockey. The drag-flick is used less by women than men in a penalty corner. The aim of this study was to describe training-induced changes in the drag-flick technique in female field hockey players. Four female players participated in the study. The VICON optoelectronic system (Oxford Metrics, Oxford, UK) measured the kinematic parameters of the drag-flick with six cameras sampling at 250 Hz, prior to and after training. Fifteen shots were captured for each subject. A Wilcoxon test assessed the differences between pre-training and post-training parameters. Two players received specific training twice a week for 8 weeks; the other two players did not train. The proposed drills improved the position of the stick at the beginning of the shot (p<0.05), the total distance of the shot (p<0.05)and the rotation radius at ball release (p<0.01). It was noted that all players had lost speed of the previous run. Further studies should include a larger sample, in order to provide more information on field hockey performance.

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This paper describes the language identification (LID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. We show that techniques originally developed for LID on telephone speech (e.g., for the NIST language recognition evaluations) remain effective on the noisy RATS data, provided that careful consideration is applied when designing the training and development sets. In addition, we show significant improvements from the use of Wiener filtering, neural network based and language dependent i-vector modeling, and fusion.

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Transport climate change impacts have become a worldwide concern. The use of Intelligent Transport Systems (ITS) could contribute to a more effective use of resources in toll road networks. Management of toll plazas is central to the reduction of greenhouse gas (GHG) emissions, as it is there that bottlenecks and congestion occur. This study focuses on management strategies aimed at reducing climate change impacts of toll plazas by managing toll collection systems. These strategies are based on the use of different collection system technologies – Electronic Toll Collection (ETC) and Open Road Tolling (ORT) – and on queue management. The carbon footprint of various toll plazas is determined by a proposed integrated methodology which estimates the carbon dioxide (CO2) emissions of the different operational stages at toll plazas (deceleration, service time, acceleration, and queuing) for the different toll collection systems. To validate the methodology, two main-line toll plazas of a Spanish toll highway were evaluated. The findings reveal that the application of new technologies to toll collection systems is an effective management strategy from an environmental point of view. The case studies revealed that ORT systems lead to savings of up to 70% of CO2 emissions at toll plazas, while ETC systems save 20% comparing to the manual ones. Furthermore, queue management can offer a 16% emissions savings when queue time is reduced by 116 seconds. The integrated methodology provides an efficient environmental management tool for toll plazas. The use of new technologies is the future of the decarbonization of toll plazas.

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Purpose – The purpose of this paper is to introduce the design of a training tool intended to improve deminers' technique during close-in detection tasks. Design/methodology/approach – Following an introduction that highlights the impact of mines and improvised explosive devices (IEDs), and the importance of training for enhancing the safety and the efficiency of the deminers, this paper considers the utilization of a sensory tracking system to study the skill of the hand-held detector expert operators. With the compiled information, some critical performance variables can be extracted, assessed, and quantified, so that they can be used afterwards as reference values for the training task. In a second stage, the sensory tracking system is used for analysing the trainee skills. The experimentation phase aims to test the effectiveness of the elements that compose the sensory system to track the hand-held detector during the training sessions. Findings – The proposed training tool will be able to evaluate the deminers' efficiency during the scanning tasks and will provide important information for improving their competences. Originality/value – This paper highlights the need of introducing emerging technologies for enhancing the current training techniques for deminers and proposes a sensory tracking system that can be successfully utilised for evaluating trainees' performance with hand-held detectors.

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Background: Healthy diet and regular physical activity are powerful tools in reducing diabetes and cardiometabolic risk. Various international scientific and health organizations have advocated the use of new technologies to solve these problems. The PREDIRCAM project explores the contribution that a technological system could offer for the continuous monitoring of lifestyle habits and individualized treatment of obesity as well as cardiometabolic risk prevention. Methods: PREDIRCAM is a technological platform for patients and professionals designed to improve the effectiveness of lifestyle behavior modifications through the intensive use of the latest information and communication technologies. The platform consists of a web-based application providing communication interface with monitoring devices of physiological variables, application for monitoring dietary intake, ad hoc electronic medical records, different communication channels, and an intelligent notification system. A 2-week feasibility study was conducted in 15 volunteers to assess the viability of the platform. Results: The website received 244 visits (average time/session: 17 min 45 s). A total of 435 dietary intakes were recorded (average time for each intake registration, 4 min 42 s ± 2 min 30 s), 59 exercises were recorded in 20 heart rate monitor downloads, 43 topics were discussed through a forum, and 11 of the 15 volunteers expressed a favorable opinion toward the platform. Food intake recording was reported as the most laborious task. Ten of the volunteers considered long-term use of the platform to be feasible. Conclusions: The PREDIRCAM platform is technically ready for clinical evaluation. Training is required to use the platform and, in particular, for registration of dietary food intake.

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Smart Grids are advanced power networks that introduce intelligent management, control, and operation systems to address the new challenges generated by the growing energy demand and the appearance of renewal energies. In the literature, Smart Grids are presented as an exemplar SoS: systems composed of large heterogeneous and independent systems that leverage emergent behavior from their interaction. Smart Grids are currently scaling up the electricity service to millions of customers. These Smart Grids are known as Large-Scale Smart Grids. From the experience in several projects about Large-Scale Smart Grids, this paper defines Large-Scale Smart Grids as a SoS that integrate a set of SoS and conceptualizes the properties of this SoS. In addition, the paper defines the architectural framework for deploying the software architectures of Large-Scale Smart Grid SoS.

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Providing security to the emerging field of ambient intelligence will be difficult if we rely only on existing techniques, given their dynamic and heterogeneous nature. Moreover, security demands of these systems are expected to grow, as many applications will require accurate context modeling. In this work we propose an enhancement to the reputation systems traditionally deployed for securing these systems. Different anomaly detectors are combined using the immunological paradigm to optimize reputation system performance in response to evolving security requirements. As an example, the experiments show how a combination of detectors based on unsupervised techniques (self-organizing maps and genetic algorithms) can help to significantly reduce the global response time of the reputation system. The proposed solution offers many benefits: scalability, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. For these reasons, we believe that our solution is capable of coping with the dynamism of ambient intelligence systems and the growing requirements of security demands.

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AIMS: To investigate the effect of pelvic floor muscle training (PFMT) taught in a general exercise class during pregnancy on the prevention of urinary incontinence (UI) in nulliparous continent pregnant women. METHODS: This was a unicenter two armed randomized controlled trial. One hundred sixty-nine women were randomized by a central computer system to an exercise group (EG) (exercise class including PFMT) (n = 73) or a control group (CG) (n = 96). 10.1% loss to follow-up: 10 from EG and 7 from CG. The intervention consisted of 70-75 sessions (22 weeks, three times per week, 55-60 min/session including 10 min of PFMT). The CG received usual care (which included follow up by midwifes including information about PFMT). Questions on prevalence and degree of UI were posed before (week 10-14) and after intervention (week 36-39) using the International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF). RESULTS: At the end of the intervention, there was a statistically significant difference in favor of the EG. Reported frequency of UI [Never: CG: 54/60.7%, EG: 60/95.2% (P < 0.001)]. Amount of leakage [None: CG: 45/60.7%, EG: 60/95.2% (P < 0.001)]. There was also a statistically significant difference in ICIQ-UI SF Score between groups after the intervention period [CG: 2.7 (SD 4.1), EG: 0.2 (SD 1.2) (P < 0.001)]. The estimated effect size was 0.8. CONCLUSION: PFMT taught in a general exercise class three times per week for at least 22 weeks, without former assessment of ability to perform a correct contraction was effective in primary prevention of UI in primiparous pregnant women.