73 resultados para computer application

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Introduction Language is the most important mean of communication and plays a central role in our everyday life. Brain damage (e.g. stroke) can lead to acquired disorders of lan- guage affecting the four linguistic modalities (i.e. reading, writing, speech production and comprehension) in different combinations and levels of severity. Every year, more than 5000 people (Aphasie Suisse) are affected by aphasia in Switzerland alone. Since aphasia is highly individual, the level of difficulty and the content of tasks have to be adapted continuously by the speech therapists. Computer-based assignments allow patients to train independently at home and thus increasing the frequency of ther- apy. Recent developments in tablet computers have opened new opportunities to use these devices for rehabilitation purposes. Especially older people, who have no prior experience with computers, can benefit from the new technologies. Methods The aim of this project was to develop an application that enables patients to train language related tasks autonomously and, on the other hand, allows speech therapists to assign exercises to the patients and to track their results online. Seven categories with various types of assignments were implemented. The application has two parts which are separated by a user management system into a patient interface and a therapist interface. Both interfaces were evaluated using the SUS (Subject Usability Scale). The patient interface was tested by 15 healthy controls and 5 patients. For the patients, we also collected tracking data for further analysis. The therapist interface was evaluated by 5 speech therapists. Results The SUS score are xpatients = 98 and xhealthy = 92.7 (median = 95, SD = 7, 95% CI [88.8, 96.6]) in case of the patient interface and xtherapists = 68 in case of the therapist interface. Conclusion Both, the patients and the healthy subjects, attested high SUS scores to the patient interface. These scores are considered as "best imaginable". The therapist interface got a lower SUS score compared to the patient interface, but is still considered as "good" and "usable". The user tracking system and the interviews revealed that there is room for improvements and inspired new ideas for future versions.

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`Evolution of mylonitic microfabrics' (EMM) is an interactive Filemaker Pro 3.0 application that documents a series of see-through deformation experiments on polycrystalline norcamphor. The application comprises computer animations, graphics and text explanations designed to give students and researchers insight into the interaction and dynamic nature of small-scale, mylonitic processes like intracrystalline glide, dynamic recrystallization and strain localization (microshearing). EMM shows how mylonitic steady state is achieved at different strain rates and temperatures. First, rotational mechanisms like glide-induced vorticity, subgrain rotation recrystallization and rigid-body rotation bring grains' crystal lattices into orientations that are favorable for intracrystalline glide. In a second stage, selective elimination of grains whose lattices are poorly oriented for glide involves grain boundary migration. This strengthens the texture. Temperature and strain rate affect both the relative activity of different strain accommodation mechanisms and the rate of microfabric change. Steady-state microfabrics are characterized by stable texture, grain size and shape-preferred orientations of grains and domains. This involves the cyclical generation and elimination of dynamically recrystallized grains and microshear zones.

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Percutaneous nephrolithotomy (PCNL) for the treatment of renal stones and other related renal diseases has proved its efficacy and has stood the test of time compared with open surgical methods and extracorporal shock wave lithotripsy. However, access to the collecting system of the kidney is not easy because the available intra-operative image modalities only provide a two dimensional view of the surgical scenario. With this lack of visual information, several punctures are often necessary which, increases the risk of renal bleeding, splanchnic, vascular or pulmonary injury, or damage to the collecting system which sometimes makes the continuation of the procedure impossible. In order to address this problem, this paper proposes a workflow for introduction of a stereotactic needle guidance system for PCNL procedures. An analysis of the imposed clinical requirements, and a instrument guidance approach to provide the physician with a more intuitive planning and visual guidance to access the collecting system of the kidney are presented.

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Recent advances in tissue-engineered cartilage open the door to new clinical treatments of joint lesions. Common to all therapies with in-vitro-engineered autografts is the need for optimal fit of the construct to allow screwless implantation and optimal integration into the live joint. Computer-assisted surgery (CAS) techniques are prime candidates to ensure the required accuracy, while at the same time simplifying the procedure. A pilot study has been conducted aiming at assembling a new set of methods to support ankle joint arthroplasty using bioengineered autografts. Computer assistance allows planning of the implant shape on a computed tomography (CT) image, manufacturing the construct according to the plan, and interoperatively navigating the surgical tools for implantation. A rotational symmetric model of the joint surface was used to avoid segmentation of the CT image; new software was developed to determine the joint axis and make the implant shape parameterizable. A complete cycle of treatment from planning to operation was conducted on a human cadaveric foot, thus proving the feasibility of computer-assisted arthroplasty using bioengineered autografts

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Using navigation systems in general orthopaedic surgery and, in particular, knee replacement is becoming more and more accepted. This paper describes the basic technological concepts of modern computer assisted surgical systems. It explains the variation in currently available systems and outlines research activities that will potentially influence future products. In general, each navigation system is defined by three components: (1) the therapeutic object is the anatomical structure that is operated on using the navigation system, (2) the virtual object represents an image of the therapeutic object, with radiological images or computer generated models potentially being used, and (3) last but not least, the navigator acquires the spatial position and orientation of instruments and anatomy thus providing the necessary data to replay surgical action in real-time on the navigation system's screen.

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The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

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The examination of traffic accidents is daily routine in forensic medicine. An important question in the analysis of the victims of traffic accidents, for example in collisions between motor vehicles and pedestrians or cyclists, is the situation of the impact. Apart from forensic medical examinations (external examination and autopsy), three-dimensional technologies and methods are gaining importance in forensic investigations. Besides the post-mortem multi-slice computed tomography (MSCT) and magnetic resonance imaging (MRI) for the documentation and analysis of internal findings, highly precise 3D surface scanning is employed for the documentation of the external body findings and of injury-inflicting instruments. The correlation of injuries of the body to the injury-inflicting object and the accident mechanism are of great importance. The applied methods include documentation of the external and internal body and the involved vehicles and inflicting tools as well as the analysis of the acquired data. The body surface and the accident vehicles with their damages were digitized by 3D surface scanning. For the internal findings of the body, post-mortem MSCT and MRI were used. The analysis included the processing of the obtained data to 3D models, determination of the driving direction of the vehicle, correlation of injuries to the vehicle damages, geometric determination of the impact situation and evaluation of further findings of the accident. In the following article, the benefits of the 3D documentation and computer-assisted, drawn-to-scale 3D comparisons of the relevant injuries with the damages to the vehicle in the analysis of the course of accidents, especially with regard to the impact situation, are shown on two examined cases.

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A laboratory study was performed to assess the influence of beveling the margins of cavities and the effects on marginal adaptation of the application of ultrasound during setting and initial light curing. After minimal access cavities had been prepared with an 80 microm diamond bur, 80 box-only Class II cavities were prepared mesially and distally in 40 extracted human molars using four different oscillating diamond coated instruments: (A) a U-shaped PCS insert as the non-beveled control (EMS), (B) Bevelshape (Intensiv), (C) SonicSys (KaVo) and (D) SuperPrep (KaVo). In groups B-D, the time taken for additional bevel finishing was measured. The cavities were filled with a hybrid composite material in three increments. Ultrasound was also applied to one cavity per tooth before and during initial light curing (10 seconds). The specimens were subjected to thermomechanical stress in a computer-controlled masticator device. Marginal quality was assessed by scanning electron microscopy and the results were compared statistically. The additional time required for finishing was B > D > C (p < or = 0.05). In all groups, thermomechanical loading resulted in a decrease in marginal quality. Beveling resulted in higher values for "continuous" margins compared with that of the unbeveled controls. The latter showed better marginal quality at the axial walls when ultrasound was used. Beveling seems essential for good marginal adaptation but requires more preparation time. The use of ultrasonic vibrations may improve the marginal quality of unbeveled fillings and warrants further investigation.

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This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.