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AbstractIntroduction: Sleep Bruxism (SB) is a non-functional rhythmic movement of the mandible with multifactorial aetiology and complex diagnose. It has been the subject of various studies over the past decades and it is considered a result of actions of the Central Nervous System modulated by Autonomous Nervous System. In this work, we test the hypothesis that SB subjects present a typical and defined neurobehavioral pattern that can be distinct from that of non-bruxers subjects and can be measured during wakefulness. Methods Fifteen sleep bruxers (experimental-group EG) and fifteen non-bruxers (control-group CG) took part in the experiments. To verify the presence and severity of SB, clinical examinations, anamneses and questionnaires, including Visual Analogic Scale - faces (VAS-f) and State-Trait Anxiety Inventory (STAI) were applied. To legitimate the diagnoses of SB, a disposable instrument (Bitestrip®) to assess the masseter activity during sleep was employed. All subjects were submitted to a set of experiments for measuring various visual evoked responses during the presentation of visual stimuli (pleasant, unpleasant and neutral images). Events in Visual Evoked Potential (VEP) were used to compare the neural responses of both CG and EG. Results VAS-f showed EG with higher perception of stress than CG (trait: p=0.05), and lower quality of life for (state: p=0.007). STAI I and II showed significant differences of anxiety between CG and EG (p=0.013 and p=0.004, respectively), being EG the highest. The EG Bitestrip scores confirmed that 100% of subjects were sleep bruxers. Significant differences were found between EG and CG for events associated with emotional (pleasant and unpleasant) images in the first 250 ms after stimulation. In general, EG subjects showed higher amplitude and shorter latency of VEP events. Conclusion It is possible to distinguish between SB and non-bruxers subjects during wakefulness, based on differences in amplitude and latency of cortical event related potentials elicited by visual stimulation. SB subjects show greater amplitudes in specific events in frontal areas when non-pleasant images are shown. Latencies tend to be anticipated in SB compared to CG subjects.
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Introduction: Individuals with mobility impairments associated with lower limb disabilities often face enormous challenges to participate in routine activities and to move around various environments. For many, the use of wheelchairs is paramount to provide mobility and social inclusion. Nevertheless, they still face a number of challenges to properly function in our society. Among the many difficulties, one in particular stands out: navigating in complex internal environments (indoors). The main objective of this work is to propose an architecture based on Mobile Augmented Reality to support the development of indoor navigation systems dedicated to wheelchair users, that is also capable of recording CAD drawings of the buildings and dealing with accessibility issues for that population. Methods Overall, five main functional requirements are proposed: the ability to allow for indoor navigation by means of Mobile Augmented Reality techniques; the capacity to register and configure building CAD drawings and the position of fiducial markers, points of interest and obstacles to be avoided by the wheelchair user; the capacity to find the best route for wheelchair indoor navigation, taking stairs and other obstacles into account; allow for the visualization of virtual directional arrows in the smartphone displays; and incorporate touch or voice commands to interact with the application. The architecture is proposed as a combination of four layers: User interface; Control; Service; and Infrastructure. A proof-of-concept application was developed and tests were performed with disable volunteers operating manual and electric wheelchairs. Results The application was implemented in Java for the Android operational system. A local database was used to store the test building CAD drawings and the position of fiducial markers and points of interest. The Android Augmented Reality library was used to implement Augmented Reality and the Blender open source library handled the basis for implementing directional navigation arrows. OpenGL ES provided support for various graphics and mathematical transformations for embedded systems, such as smartphones. Experiments were performed in an academic building with various labs, classrooms and male and female bathrooms. Two disable volunteers using wheelchairs showed no difficulties to interact with the application, either by entering touch or voice commands, and to navigate within the testing environment with the help of the navigational arrows implemented by the augmented reality modules. Conclusion The novel features implemented in the proposed architecture, with special emphasis on the use of Mobile Augmented Reality and the ability to identify the best routes free of potential hazards for wheelchair users, were capable of providing significant benefits for wheelchair indoor navigation when compared to current techniques described in the literature.
ABSTRACT
Este trabalho apresenta uma abordagem computacional para recomendar exercícios fisioterápicos a partir das análises da amplitude de movimento capturada em tempo real por meio de um sensor de movimento (MS-KinectTM). Com intuíto de se obter uma recomendação de novos exercícios com base no histórico do paciente durante o tratamento de uma patologia. Os dados do movimento capturado são processados e analisados, fornecendo uma segunda opnião ao terapeuta sobre o caso. Para avaliar a aplicabilidade e viabilidade do sistema, foi aplicado um teste com 20 sujeitos em tratamento da dor lombar (lombalgia mecânica), e o conjunto de dados foi análisado por outros 5 fisioterapeutas que sugeriram exercícios, catalogados na base de dados do sistema. Foi utilizado um método agrupamento de dados sobre as amplitudes de movimento em relação ao índice de incapacidade de movimento e as medidas antropométricas dos sujeitos. E novamente outro técnica de inteligência computacional para recomendar os novos exercícios. Nas conclusões evidencia-se com certo grau de certeza a viabilidade do sistema e sua sugestão de aplicação das técnicas nele contida para recomendação de outros tratamento de patologias de disfunções musculares...
This paper presents a computational approach to recommend physical therapy from the analysis of the range of motion captured in real time by means of a motion sensor (MS-KinectTM). With goal to obtain a recommendation of new exercises based on the history of the patient during the treatment of a condition. The captured motion data is processed and analyzed, providing a second opinion the therapist about the case. To evaluate the applicability and feasibility of the system, we applied a test with 20 subjects in treatment of low back pain (mechanical low back pain), and the data set was parsed by other 5 physiotherapists who suggested exercises cataloged in the database system. A method of grouping data on range of motion in relation to the disability index of motion and anthropometric measurements of the subjects was used. Again another technique of computational intelligence to recommend the new exercises. In conclusion, it is evident with some degree of certainty the viability of the system and its application techniques contained therein for recommending other treatment of diseases of muscle disorders...
Este artículo presenta un enfoque computacional para recomendar la terapia física a partir del análisis de la amplitud de movimiento capturado en tiempo real por medio de un sensor de movimiento (MS-KinectTM). Con el objetivo de obtener una recomendación de nuevos ejercicios basados en la historia de la paciente durante el tratamiento de una condición. Los datos de captura de movimiento es procesada y analizada, que proporciona una segunda opinión el terapeuta sobre el caso. Para evaluar la aplicabilidad y viabilidad del sistema, se aplicó una prueba con 20 sujetos en el tratamiento del dolor lumbar (lumbalgia mecánica), y el conjunto de datos se ha analizado por otros 5 fisioterapeutas que sugirieron ejercicios catalogados en el sistema de base de datos. Se utilizó un método de agrupación de datos en el rango de movimiento en relación con el índice de discapacidad de movimiento y las medidas antropométricas de los sujetos. Y también otra técnica de inteligencia computacional para recomendar los nuevos ejercicios. En conclusión, es evidente con algún grado de certeza la viabilidad del sistema y su sugerencia de aplicar las técnicas contenidas recomendación para el tratamiento de otros trastornos de disfunciones musculares en el mismo...
Subject(s)
Humans , Male , Female , Adolescent , Middle Aged , Young Adult , Low Back Pain/therapy , Physical and Rehabilitation Medicine , Computer Systems , Decision Making , Observational StudyABSTRACT
Este trabalho mostra uma avaliação heurística da interface do Sistema de Captura de Movimentos (MoCap) realizado por profissionais de saúde (fisioterapeutas) no intuito de promover a melhoria contínua do software bem como elucidar como as técnicas de rastreio de movimentos com a tecnologia de Realidade Aumentada pode trazer uma vantagem estratégica para pequenas clínicas. Também são levantadas as deficiências desta tecnologia e proposto algumas práticas que podem mitiga-las.
This paper shows a heuristic interface evaluation of Motion Capture System (MoCap) conducted by physiotherapists in order to promote continuous improvement of the software as well as elucidate the techniques of tracking movements with the Augmented Reality technology can provide a strategic advantage to small clinics. Also raised are the shortcomings of this technology and proposed some practices that can mitigate them.
En este trabajo se muestra una evaluación heurística de la interfaz del sistema de captura de movimiento (Mocap) llevada a cabo por profesionales de la salud (fisioterapeutas) con el fin de promover la mejora continua de los programas, así como dilucidar las técnicas de rastreo de movimientos con la tecnología de Realidad Aumentada puede proporcionar una ventaja estratégica para pequeñas clínicas. También se planteó son las deficiencias de esta tecnología y propuso algunas prácticas que pueden mitigarlos.