Naše nejvýznamnější odborné publikace

Abstract: Smoking, excessive drinking, overeating and physical inactivity are well-established risk factors decreasing human physical performance. Moreover, epidemiological work has identified modifiable lifestyle factors, such as poor diet and physical and cognitive inactivity that are associated with the risk of reduced cognitive performance. Definition, collection and annotation of human reaction times and suitable health related data and metadata provides researchers with a necessary source for further analysis of human physical and cognitive performance. The collection of human reaction times and supporting health related data was obtained from two groups comprising together 349 people of all ages - the visitors of the Days of Science and Technology 2016 held on the Pilsen central square and members of the Mensa Czech Republic visiting the neuroinformatics lab at the University of West Bohemia. Each provided dataset contains a complete or partial set of data obtained from the following measurements: hands and legs reaction times, color vision, spirometry, electrocardiography, blood pressure, blood glucose, body proportions and flexibility. It also provides a sufficient set of metadata (age, gender and summary of the participant's current life style and health) to allow researchers to perform further analysis. This article has two main aims. The first aim is to provide a well annotated collection of human reaction times and health related data that is suitable for further analysis of lifestyle and human cognitive and physical performance. This data collection is complemented with a preliminarily statistical evaluation. The second aim is to present a procedure of efficient acquisition of human reaction times and supporting health related data in non-lab and lab conditions.

Abstract: P300 brain-computer interfaces (BCIs) have been gaining attention in recent years. To achieve good performance and accuracy, it is necessary to optimize both feature extraction and classification algorithms. This article aims at verifying whether supervised learning models based on self-organizing maps (SOM) or adaptive resonance theory (ART) can be useful for this task. For feature extraction, the state-of-the-art Windowed means paradigm was used. For classification, proposed classifiers were compared with state-of-the-art classifiers used in BCI research, such as Bayesian Linear Discriminant Analysis, or shrinkage LDA. Publicly available datasets from 15 healthy subjects were used for the experiments. The results indicated that SOM-based models yield better results than ART-based models. The best performance was achieved by the LASSO model that was comparable to state-of-the-art BCI classifiers. Further possibilities for improvements are discussed

Abstract: Mobile devices have already been designed for many applications. Smartphones and tablet computers are modern, widespread and affordable solutions used for various purposes. Nowadays mobile devices are widely used in telemedicine. It is usually assumed, that the device is owned and used by a single person. We focus on security concerns and constraints from a different point of view ? when the device is shared. In this paper, we are proposing a novel approach to prevent leakage of patient's confidential data when the device is used by multiple patients at the hospital's clinic or department. We present a prototype application and discuss its use case and designed workflow

Abstract: Deep learning has emerged as a new branch of machine learning in recent years. Some of the related algorithms have been reported to beat state-of-the-art approaches in many applications. The main aim of this paper is to verify one of the deep learning algorithms, specifically a stacked autoencoder, to detect the P300 component. This component, as a specific brain response, is widely used in the systems based on brain-computer interface. A simple brain-computer interface experiment more than 200 school-age participants was performed to obtain large datasets containing the P300 component. After feature extraction the collected data were split into the training and testing sets. State-of-the art BCI classifiers (such as LDA, SVM, or Bayesian LDA) were applied to the data and then compared with the results of stacked autoencoders.

Abstract: The purpose of this study is to investigate the feasibility of applying openEHR (an archetype-based approach for electronic health records representation) to modeling data stored in EEGBase, a portal for experimental electroencephalography/eventrelated potential (EEG/ERP) data management. The study evaluates re-usage of existing openEHR archetypes and proposes a set of new archetypes together with the openEHR templates covering the domain. The main goals of the study are to (i) link existing EEGBase data/metadata and openEHR archetype structures and (ii) propose a new openEHR archetype set describing the EEG/ERP domain since this set of archetypes currently does not exist in public repositories

Abstract: Medical treatment of sudden and especially chronic diseases has become more expensive. People suffering from a variety of diseases had been traditionally treated in hospitals for a long time. Fortunately, the current situation has been changing also thanks to relatively cheap body sensors and development of systems for home treatment. It brings inconsiderable cost savings and improves patients? comfort. On the other hand, it puts demands on the used technical infrastructure and home treatment system developers who must solve integration of different systems. A crucial point is a definition of unified data formats facilitating transfer and storage of data to/in remote databases. There are standards and APIs such as Zigbee, Bluetooth low energy or ANT+ that define a protocol for data transfer. However, they do not define a suitable format for long term data storing. In this paper, data coming from ANT+ sensors have been studied and metadata related to all kinds of body sensors and raw data and metadata specific to individual sensors have been defined. Then a framework organizing data and metadata obtained from ANT+ sensors into an open and general data format suitable for long term storage of sensor data is introduced. Finally, a sample use-case showing the transfer of data from a sensor into a data storage is presented.

Abstract: Developmental coordination disorder (DCD) is described as a motor skill disorder characterized by a marked impairment in the development of motor coordination abilities that significantly interferes with performance of daily activities and/or academic achievement. Since some electrophysiological studies suggest differences between children with/without motor development problems, we prepared an experimental protocol and performed electrophysiological experiments with the aim of making a step toward a possible diagnosis of this disorder using the event-related potentials (ERP) technique. The second aim is to properly annotate the obtained raw data with relevant metadata and promote their long-term sustainability. Results: The data from 32 school children (16 with possible DCD and 16 in the control group) were collected. Each dataset contains raw electroencephalography (EEG) data in the BrainVision format and provides sufficient metadata (such as age, gender, results of the motor test, and hearing thresholds) to allow other researchers to perform analysis. For each experiment, the percentage of ERP trials damaged by blinking artifacts was estimated. Furthermore, ERP trials were averaged across different participants and conditions, and the resulting plots are included in the manuscript. This should help researchers to estimate the usability of individual datasets for analysis. Conclusions: The aim of the whole project is to find out if it is possible to make any conclusions about DCD from EEG data obtained. For the purpose of further analysis, the data were collected and annotated respecting the current outcomes of the International Neuroinformatics Coordinating Facility Program on Standards for Data Sharing, the Task Force on Electrophysiology, and the group developing the Ontology for Experimental Neurophysiology. The data with metadata are stored in the EEG/ERP Portal.

Abstract: Guess the number is a simple P300-based brain-computer interface experiment. Its aim is to ask the measured participant to pick a number between 1 and 9. Then, he or she is exposed to corresponding visual stimuli and experimenters try to guess the number thought while they are observing event-related potential waveforms on-line. 250 school-age children participated in the experiments that were carried out in elementary and secondary schools in the Czech Republic. Electroencephalographic data from three EEG channels (Fz, Cz, Pz) and stimuli markers were stored. Additional metadata about the participants were collected (gender, age, laterality, the number thought by the participant, the guess of the experimenters, and various interesting additional information). Consequently, we offer the largest publicly available odd-ball paradigm collection of datasets to neuroscientific and brain-computer interface community.

Abstract: Unwillingness of many people to assume responsibilities for a personal health, fitness and wellness seems to be widespread. This can be partially remedied by individualized exercise and wellness program that integrates the basic knowledge domains: lifestyle, sports and fitness, and nutrition and personal/environmental health. However, collection, management and analysis of data and metadata related to these domains is demanding and time consuming task. Moreover, the appropriate annotation of raw data is crucial for their next processing. To promote such a program a software infrastructure for collection, storage, management, analysis and interpretation of health related data and metadata has been proposed and part of this infrastructure has been developed and tested outside laboratory conditions. This software prototype allows experimenters to collect various heterogeneous health related data in a highly organized and efficient way. Data are then evaluated and users can view relevant information related to their health and fitness.

Abstract: Attention of drivers is very important for road safety and it is worth observing even in laboratory conditions during a simulated drive. This paper deals with design of an experiment investigating driver?s attention, validation of collected data, and first preprocessing and processing steps used within data analysis. Brain activity is considered as a primary biosignal and is measured and analyzed using the techniques and methods of electroencephalography and event related potentials. Respiration is considered as a secondary biosignal that is captured together with brain activity. Validation of collected data using a stacked autoencoder is emphasized as an important step preceding data analysis.

Abstract: Using a combination of unsupervised pre-training and subsequent fine-tuning, deep neural networks have become one of the most reliable classification methods. The aim of the experiments subsequently presented was to verify if deep learning-based models can also perform well for single trial P300 classification with possible application to P300-based brain-computer interfaces. The P300 data used were recorded in the EEG/ERP laboratory at the Department of Computer Science and Engineering, University of West Bohemia, and are publicly available. Stacked autoencoders were implemented and compared with some of the currently most reliable state-of-the-art methods, such as LDA and multi-layer perceptron. The parameters of stacked autoencoders were optimized empirically. Subsequently, fine-tuning using backpropagation was performed. The architecture of the neural network was 209-130-100-50-20-2. The classifiers were trained on a dataset merged from four subjects and subsequently tested on different 11 subjects without further training. The trained SAE achieved 69.2% accuracy that was higher (p < 0.01) than the accuracy of MLP (64.9%) and LDA (65.9%). The recall of 58.8% was slightly higher when compared with MLP (56.2%) and LDA (58.4%).

Abstract: This paper will introduce problem of statistics of quasi-periodic signal in relation to detection of the vocal cords pathology from audio recording. Distribution function of period lengths and its relation to distribution function of immediate frequencies is defined and application on vocal cord diagnostic by classification of periods and frequencies to common (normal) and anomalous is devised.

Abstract: Patient data or description burned-in image and stored in the DICOM file format is problematic for any secondary use of imaging examinations. It is necessary to identify and remove all burned-in text with private health information.

Abstract: Diabetes mellitus is one of the most frequent civilization diseases. It is characterized with elevated blood glucose level. Elevated blood glucose level damages multiple organs with an increased risk of death, mainly due to hypo- or hyperglycemic shock. Eventually, diabetic patient becomes dependent on insulin to maintain normal blood glucose level. Over-dosage of insulin can lead to death in a short period. Therefore, patient and his physician must be aware of patient?s blood glucose level. Patient does sporadic measuring of blood glucose level using a finger-stick. From time to time, the patient additionally wears a contin-uous glucose monitoring system. Such a system measures glucose level in subcutaneous tissue ? it does not measure blood glucose level. As these two glucose levels are not necessarily the same, a model of glucose dynamics is needed to calculate blood glucose level from subcutaneous tissue glucose level. In this paper, we present a modification of the Honey Bee Mating Optimization algorithm to determine parameters of glucose-dynamics model. The proposed modification intro duces effect of aging into the mating process. We demonstrate that aging improves parameter determination, especially when escaping local extreme of a fitness function.

Abstract: This study deals with new findings about vocal folds kinematics acquired by using High?Speed Video camera. The parameters usually applied to measuring vocal folds kinematics are supplemented with new ones which are based on detection of glottis and determination of its main axis. Parameters of glottis symmetry and parameters of motion of glottis center point against its main axis are illustrated on selected case reports.

Abstract: There are a lot of sensors for monitoring human health and/or fitness level on the market. They facilitate collection of data from the human body and advanced devices even facilitate data transfer to remote servers where the collected data are further processed. While health data, obtained e.g. from accelerometers or chest straps, are collected rather frequently, brain electrophysiology data, obtained from surface electrodes, are still collected relatively rarely. However, integration and correlation of brain signals with other sensory data would be very interesting for next research of physical and mental health. Although capturing brain signals in real environment still faces technological difficulties, current development of common infrastructure seems to be useful. Then this article deals with various architectures and data formats used for storage and transfer of sensory data and their possible integration with existing neuroinformatics approaches. As a solution we introduced a terminology describing data from a limited collection of sensors. The terminology is implemented in the odML format and integrated in a proof-of-concept Android application. Data transfer, storage and visualisation as well as integration with a remote neuroinformatics resource are presented.

Abstract: Diabetes is a silent disease. It is the 8th most common cause of death that does not hurt until it is too late and the disease has developed. Technology plays a vital role in managing diabetes and educating patients about importance of the treatment. The patient must be able to manage his blood glucose level. However, blood glucose level is measured sporadically as it causes important discomfort to the patient. Measuring glucose level in subcutaneous tissue is minimally invasive technique and thus considerably comfortable, but this level may be different from blood glucose level. We implemented a recently proposed method of blood glucose level calculation from the continuously measured subcutaneous tissue glucose level. Then, we developed a web portal that makes this method accessible to any doctor?s office and any diabetic patient. To the best of our knowledge, we are the very first web portal that does this. In this paper, we describe the portal.

Abstract: The growing electrophysiology research leads to the collection of large amounts of experimental data and consequently to the broader application, eventually development of analytic methods, algorithms, and workflows. Then appropriate metadata definition and related data description is critical for long term storage and later identification of experimental data. Although a detailed description of electrophysiology data has not become a commonly used procedure so far, publicly available and well described data have started to appear in professional journals. The next reasonable step is to shift attention to the analysis of electrophysiology data. Since the analysis of this kind of data is rather complex, identification and appropriate description of used methods, algorithms and workflows would help reproducibility of the research in the field. This description would also allow developing automatic or semi-automatic systems for data analysis or constructing complex workflows in a more user friendly way. Based on these assumptions authors present a custom ontology for description of analytic methods and workflows in electrophysiology that is proposed to be discussed within the scientific community.

Abstract: We developed a new model of glucose dynamics. The model calculates blood glucose level as a function of transcapillary glucose transport. In previous studies, we validated the model with animal experiments. We used analytical method to determine model parameters. In this study, we validate the model with subjects with type 1 diabetes. In addition, we combine the analytic method with meta-differential evolution. To validate the model with human patients, we obtained a data set of type 1 diabetes study that was coordinated by Jaeb Center for Health Research. We calculated a continuous blood glucose level from continuously measured interstitial fluid glucose level. We used 6 different scenarios to ensure robust validation of the calculation. Over 96% of calculated blood glucose levels fit A+B zones of the Clarke Error Grid. No data set required any correction of model parameters during the time course of measuring. We successfully verified the possibility of calculating a continuous blood glucose level of subjects with type 1 diabetes. This study signals a successful transition of our research from an animal experiment to a human patient. Researchers can test our model with their data on-line at https://diabetes.zcu.cz.

Abstract: This paper will consider a framework for simulation of musculoskeletal system via mass-spring system as the target application. The framework uses a mass-spring systems to simulate the muscle fibres of each muscle and an additional triangle model to visually represent the surface of the muscles. This requires establishing some relationship between the two models so that when some nodes of the mass-spring model move, i.e. the object deforms, this deformation is correctly carried over to the visualization. Mean Value Coordinates are often used for this purpose. In this paper, we will present a simpler method that produces deformation that is visually similar to that by the Mean Value Coordinates while consuming less memory and time.

Abstract: The work presents the concept of a new personal electronic health record (EHR) system. The system is based on openEHR standards/framework. A fundamental part of openEHR is domain description by two layer modelling - reference data models and archetypes. Archetypes are building blocks of the EHR system, which provide structure and semantics for stored data. As common ontologies and terminologies, even archetypes are based on reusability. Although the public archetype repositories (clinical knowledge managers, CKM) contain hundreds of archetypes from various domains, the electrophysiology domain is not described yet. The work is focused on the development of the archetypes dealing with the electroencephalography domain.

Abstract: In this study, text-based, computer-aided prosodic analysis and measurements of connected speech were combined in order to model perceptual evaluation of the German Roughness-Breathiness-Hoarseness (RBH) scheme. 58 connected speech samples (43 women and 15 men; 48.7 ? 17.8 years) containing the German version of the text ?The North Wind and the Sun? were evaluated perceptually by 19 speech and voice therapy students according to the RBH scale. For the human-machine correlation, Support Vector Regression with measurements of the vocal fold cycle irregularities (CFx) and the closed phases of vocal fold vibration (CQx) of the Laryngograph and 33 features from a prosodic analysis module were used to model the listeners? ratings. The best human-machine results for roughness were obtained from a combination of six prosodic features and CFx (? = 0.71, ? = 0.57). These correlations were approximately the same as the interrater agreement among human raters (? = 0.65, ? = 0.61). CQx was one of the substantial features of the hoarseness model. For hoarseness and breathiness, the human-machine agreement was substantially lower. Nevertheless, the automatic analysismethod can serve as the basis for a meaningful objective support for perceptual analysis.

Abstract: Experiments in electrophysiology produce a lot of unstructured metadata collected in electrophysiology databases. The data are usually accessed through a web interface implemented on the top of data model respecting given data format. A lot of experiments are conducted outside the laboratory where access to these databases is not always available. The usage of mobile devices such as tablets or smart phones seems to be a practical solution, but users would welcome the same structured user interface such as they know from a common computer. When user interfaces of electrophysiology databases are tailored to a unique data struc- ture, they cannot be easily reused on a mobile device. As a solution, a mapping of a general data structure to a graphical template is proposed. This mapping is implemented in a framework that generates a template representing the database structure. The parsing process is driven by supplemented annotations added to the code. Next, an Android tool visualizing a graphical layout generated from the template is developed. A use case study is presented on a database of EEG/ERP experiments.

Abstract: The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

Abstract: The intent of this paper is a summary of implemented and planned the necessary steps leading to the development of software LISA (Liver Surgery Analyser). Clinically tested software offering in the preoperative phase, radiologists and surgeons called virtual liver resection to facilitate decisions on the type and design of the possible curative treatment.

Abstract: Stimulation device for neuroinformatic and reactometric experiments is developed as an external hardware device providing a visual stimulation, acoustic stimulation or combination of these. The aim of this stimulation is to evoke the corresponding brain response (visual, acoustic evoked or event related potentials). Stimulator is also able to process the response from measuring subjects and evaluate the reaction time. Simultaneously with the stimuli presentation the device also generates the synchronization pulses for external EEG or other measuring devices. These pulses are important for processing and analysis of evoked potentials. Stimulation device can be used in all experiments relating to reactometry, measuring evoked response in electrophysiology, neuroinformatics or brain-computer interface systems.

Abstract: During research based on experimental work vast amounts of data and associated metadata are usually produced. This is also the case of experimental work using the techniques of electroencephalography and event related potentials. The collected data and associated metadata have to be stored, analyzed, and eventually shared among research groups. Besides storing data and metadata from experiments, it is often beneficial to collect additional information from other sources related to the kind of experiment performed. These information sources are mostly scientific and technical publications, manuals describing the used infrastructure, and topical discussions appearing on the web. This article deals with selection and use of a semantic repository for such information sources. Development of a simple prototype ontology is shortly presented and a tool that facilitates construction of ontologies on the KIM platform is described. Sets of test documents are used to verify the functionality of the tool.

Abstract: Attention of drivers is a key factor of road safety. Since inattentive drivers cause a considerable number of accidents, it is worth to examine the causes and course of driver's attention even in laboratory conditions during a simulated drive. This paper deals with the experiment in which the methods of electroencephalography and event related potentials are used under various conditions to investigate driver's attention. Eleven participants, university students, were stimulated with audio signals during monotonous drive in four experimental sessions. The hypothesis is that the peak latency of the P3 component increases in time as the driver is more tired from monotonous drive, daytime and sleep deprivation. The background of the used methods, experimental design, participants, data processing, results and final discussion are presented in this paper.

Abstract: The study deals with investigation and comparison of the auditory attention performance of children with developmental coordination disorder (DCD) and normally developing children (NDC) using cognitive evoked potentials (ERPs) in passive conditions. ERPs data showed that children with DCD have less ability to detect small physical differences between acoustic stimuli (no MMN response in DCD children) and have a reduced attentional engagement and stimulus evaluation of salient stimuli (a reduction of P3 amplitude in DCD children). The results of our study suggest that children with DCD do not only suffer from a visuospatial attention deficit as previous studies reported but also have auditory attention deficit.

Abstract: A diabetic patient occasionally undergoes a detailed monitoring of their glucose levels. Over the course of a few days, a monitoring system provides a detailed track of their interstitial fluid glucose levels measured in their subcutaneous tissue. A discrepancy in the blood and interstitial fluid glucose levels is unimportant because the blood glucose levels are not measured continuously. Approximately five blood glucose level samples are taken per day, and the interstitial fluid glucose level is usually measured every 5 min. An increased frequency of blood glucose level sampling would cause discomfort for the patient; thus, there is a need for methods to estimate blood glucose levels from the glucose levels measured in subcutaneous tissue. The Steil-Rebrin model is widely used to describe the relationship between blood and interstitial fluid glucose dynamics. However, we measured glucose level patterns for which the Steil-Rebrin model does not hold. Therefore, we based our research on a different model that relates present blood and interstitial fluid glucose levels to future interstitial fluid glucose levels. Using this model, we derived an improved model for calculating blood glucose levels. In the experiments conducted, this model outperformed the Steil-Rebrin model while introducing no additional requirements for glucose sample collection. In subcutaneous tissue, 26.71% of the calculated blood glucose levels had absolute values of relative differences from smoothed measured blood glucose levels less than or equal to 5% using the Steil-Rebrin model. However, the same difference interval was encountered in 63.01% of the calculated blood glucose levels using the proposed model. In addition, 79.45% of the levels calculated with the Steil-Rebrin model compared with 95.21% of the levels calculated with the proposed model had 20% difference intervals.

Abstract: This paper presents a methodology for interactive muscle simulation. The fibres of individual muscles are represented by particles connected by springs, thus creating a deformable model of the muscle. In order to be able to describe human musculoskeletal system, contact between pairs of muscles as well as muscles and bones must be accounted for. Therefore, collision detection and response mechanism which allows both types of contact (soft body vs. rigid body and soft vs. soft body) is presented. The solution is a part of a project dedicated to improvement of the effectiveness of osteoporosis prediction and treatment.

Abstract: EEG/ERP (electroencephalography, event-related potential) laboratories produce experimental data and metadata. Authors' research group has contributed to the building of a neuroinformatics infrastructure by developing and integrating data management and analytic tools for EEG/ERP research - the EEG/ERP Portal. With the development of the Portal and the increasing amount of data/metadata, a proper full text search mechanism for efficient information retrieval is necessary to improve the user experience. The presented solution combines search over data/metadata stored in an electrophysiological database and in the LinkedIn social network. Open source search engines, criteria, suitable engine selection, and index design are presented. Integration of the full-text solution to the EEG/ERP Portal is described.

Abstract: The event-related potentials technique is widely used in cognitive neuroscience research. The P300 waveform has been explored in many research articles because of its wide applications, such as lie detection or brain-computer interfaces (BCI). However, very few datasets are publicly available. Therefore, most researchers use only their private datasets for their analysis. This leads to minimally comparable results, particularly in brain-computer research interfaces. Here we present electroencephalography/event-related potentials (EEG/ERP) data. The data were obtained from 20 healthy subjects and was acquired using an odd-ball hardware stimulator. The visual stimulation was based on a three-stimulus paradigm and included target, non-target and distracter stimuli. The data and collected metadata are shared in the EEG/ERP Portal

Abstract: Software tool was needed to verify a model predicting interstitial fluid glucose level, while conducting an experiment. With the tool, several tasks execute concurrently to effectively utilize available processors. Implementing the tool implied addressing such aspects of parallel computing which possibly have a broader impact. In this paper, I present an experience with implementing Lamport-clock ordered event scheme to control a parallel program employing a task-stealing scheduler, while eliminating the possibility of accidentally masking a synchronization error. For a program based on Intel Threading Building Blocks library, I devised a scheme to control task execution with events. These events are ordered using the concept of Lamport Clock. As the causal ordering of events is complete , program?s behavior can be reconstructed for additional debugging. In the implementation devised, recording theevents induces no additional synchronization operations that could accidentally mask a synchronization error. The work is presented in a context of glucose level prediction that originates from a glucose-transporter research.

Abstract: In this paper we present a novel approach of an automatic computation of muscle control curves. It is based on skeletonization of a triangular surface mesh representing the muscle. Automatically determined control curves are then connected to the skeleton of the human body model so as to govern the deformation of the muscle surface when the skeleton moves. The method, which was implemented in C++ using VTK framework, was integrated into the human body framework being developed at our institution and tested on the walking lower limbs. The results show that the control curves produced by the method have a positive effect on the deformation and, therefore, are preferred to manually defined lines of action that are used as control curves in the human body framework at present.

Abstract: Large amounts of EEG/ERP (electroencephalography, event-related potential) data are produced by scientific laboratories. For complex analysis, data are processed by a set of methods sequentially or in parallel. These processes are known as workflows. However, various input/output formats of used methods involve difficulties while putting methods in a pipe. Simple syntactic rules comparing formats of input/output are already used by workflow engines. In electrophysiology, it is necessary to extend these rules due to variety of methods. Therefore, extension of syntactic rules between subsequent methods in a workflow is presented in this paper. The proposed solution allows creating more complex workflows in the domain of electrophysiology.

Abstract: Many efforts are devoted to provide a unified solution for maintaining data from electrophysiological experiments. Because large data collections of heterogeneous nature are obtained, neuroinformatics databases must be robust and flexible. Current database systems are of two types. The first one uses a fixed schema while the second one is schema free. This paper discusses usage of a NoSQL database, MongoDB, for electrophysiological experiments and investigates transformation of existing electroencephalography (EEG) and event-related potentials (ERP) database records in Oracle into MongoDB. Two perspectives, flexibility and performance are discussed. A final approach that profits from combination of both concepts, is also discussed.

Abstract: We adopt an ontology-driven information system design for research purposes. It is adaptable and extensible solution in the situation where the main features are the lack of a stable data model and changing and varying requests. We use ontology-driven design primarily as a collaboration tool for the research. Members directly collaborate and use this information system to ease them tasks with management of source/raw data, software applications and research results for its whole life-time. A different heterogeneous data kinds and a large volume data sets could be stored and shared together with its description meta data between research teams and its members in an uniform manner. It leads to an opportunity to process a stored data using proper methods and tools in a parallel and distributed computing environment. All achieved results are automatically stored and supplemented by an ontology-driven description meta data.

Abstract: This paper describes improvement of the Hilbert-Huang transform (HHT) for detection of ERP components in the EEG signal. Time-frequency domain methods, such as the wavelet transform or matching pursuit, are commonly for this task. We used a modified Hilbert-Huang transform that allows the processing of quasi-stationary signals such as EEG. The essential part of the HHT is an Empirical Mode Decomposition (EMD) that decomposes signal into intrinsic mode functions (IMFs). We designed additional stopping criteria for better selection of IMFs in the EMD. These IMFs positively affect later computed instantaneous attributes and increase classification success. We tested the influence of additional stopping criteria on classification reliability using the real EEG data acquired in our laboratory. Our results demonstrated that we were able to detect the P3 component by using the HHT with additional stopping criteria more successfully than by using the original implementation of modified HHT, continuous wavelet transform and matching pursuit.

Abstract: Relatively recently it has become apparent that providing human kind with a better healthcare requires personalised, predictive and integrative medicine, for which the building of Virtual Physiological Human (VPH) framework accessible via virtual patient avatar is necessary. Real-time modelling and visual exploration of such a complex avatar is a challenging task. In this paper, we propose a real-time method for automatic modelling of an arbitrarily large number of muscle fibres in the volume of a muscle represented by its surface mesh. The method is based on an iterative morphing of predefined fibres template into the muscle volume exploiting harmonic scalar field computed on the surface of muscle. Experiments with muscles of thighs and pelvis show that the method produces realistic shapes of fibres. Our sequential VTK-based C++ implementation is capable of producing 64 fine fibres within a muscle of 10K triangles in less than 170 ms on commodity hardware making the method suitable for VPH purposes as well as for interactive educational medical software.

Abstract: Event-related potentials (ERPs) and especially the P300 component have been gaining attention in braincomputer interface design and neurobiological research. The detection of the P300 component in electroencephalographic signal is challenging since its signal-to-noise ratio is very low. Instead of using traditional supervised pattern recognition, this paper discusses using unsupervised neural networks for the P300 classification purposes. To validate the proposed approach, a method for the P300 detection based on matching pursuit and self-organizing maps is proposed and evaluated. The results may be applied to the design of brain-computer interfaces.

Abstract: As in other areas of experimental science, operation of electrophysiological laboratory, design and performance of electrophysiological experiments, collection, storage and sharing of experimental data and metadata, analysis and interpretation of these data, and publication of results are time consuming activities. If these activities are well organized and supported by a suitable infrastructure, work efficiency of researchers increases significantly. This article deals with the main concepts, design, and development of software and hardware infrastructure for research in electrophysiology. The described infrastructure has been primarily developed for the needs of neuroinformatics laboratory at the University of West Bohemia, the Czech Republic. However, from the beginning it has been also designed and developed to be open and applicable in laboratories that do similar research. After introducing the laboratory and the whole architectural concept the individual parts of the infrastructure are described. The central element of the software infrastructure is a web-based portal that enables community researchers to store, share, download and search data and metadata from electrophysiological experiments. The data model, domain ontology and usage of semantic web languages and technologies are described. Current data publication policy used in the portal is briefly introduced. The registration of the portal within Neuroscience Information Framework is described. Then the methods used for processing of electrophysiological signals are presented. The specific modifications of these methods introduced by laboratory researches are summarized; the methods are organized into a laboratory workflow. Other parts of the software infrastructure include mobile and offline solutions for data/metadata storing and a hardware stimulator communicating with an EEG amplifier and recording software.

Abstract: The Windowed means paradigm is a method for slow-changing cortical potentials feature extraction, most importantly in reaction to events. It has been successfully used for various brain-computer interfaces. The objective of this paper was to evaluate if this paradigm is also appropriate for P300 brain-computer interfaces. The modified method was tested on five healthy subjects. The optimal selection of parameters was discussed. The Windowed means paradigm was successful for the P300 detection on the testing data-set.

Abstract: The aim of this article is 3D analysis of the temporomandibular joint patient, who underwent surgery, during which the right TMJ was resected along with the ramus of mandible and consequently the joint was reconstructed with subtotal replacement.

Abstract: At least 1% of the general population have an aneurysm (or possibly more) in their cerebral blood vessels. If an aneurysm ruptures, it kills the patient in up to 60% of cases. In order to choose the optimal treatment, clinicians have to monitor the development of the aneurysm in time. Nowadays, aneurysms are typically identified manually, which means that the monitoring is often imprecise since the identification is observer dependent. As a result, the number of misdiagnosed cases may be large. This paper proposes a fast semi-automatic method for the identification of aneurysms which is based on the analysis of the skeleton of blood vessels. Provided that the skeleton is accurate, the results achieved by our method have been deemed acceptable by expert clinicians.

Abstract: Detection of infarction core areas at patiens with ischemic stroke using computed tomography Cere-bral Blood Volume (CBV) or Perfused Blood Volume (PBV) maps. This article presents an automated method reaching better specificity allowing measuring of the infarction core volume which can serve as another criteria for physicians helping them with thrombolytical treatment indication decisions.

Abstract: According to the statistics of car accident causes [11] given by Police of the Czech Republic, about 17.5 % of all car accidents are caused by lack of dedication to driving, including microsleep. A lot of car factories develop systems for fatigue prediction and microsleep detection. These systems are usually based on eye movement tracking or steering wheel movement analysis. But both these methods detect consequences of fatigue. From road safety point of view, it would be useful to be able to detect fatigue itself before it affects dedication to driving. We know there could be a correlation between cognitive eventrelated potential (ERP) waveform latency and the rate of attention ? the longest the latency is, the more tired the measured subject is. This paper deals with determination of latency of a cognitive ERP waveform from outputs of two algorithms we use for its detection and which we have the best experience with.

Abstract: We have to deal with some crucial difficulties when more teams collaborate in a couple of research areas at the same time. These difficulties complicates our long-term medical research and its sustainability. Each researcher use quite different data, use different tools and develops its own advanced methods for data processing. Without a commonly accepted rules there were a lot of misunderstanding, data loss or even software methods loss. Research Information System is primarily used for members collaboration and managing source data, software and research results for its life-time.

Abstract: Increasing requirements on data sharing in the domain of electrophysiology lead to proposing new terminologies and data models. A current trend is to describe data by ontologies and semantic web resources. However, classic technologies and models cannot be replaced in a short time. Due to this, dependencies between various data models should be explicitly described and properties, which the models have in common, should be unified. This work summarizes the current state in data modeling. It describes various ways to model and store data and transformation mechanisms between data models. It deals with well-known concepts (relational and object oriented model) as well as with emerging concepts (ontologies). Finally, the hierarchical metadata model consisting of levels with different expressive power is introduced.

Abstract: This paper describes a method that represents a muscle by a realistic chaff of muscle fibres that are automatically generated in the volume defined by the surface mesh of the muscle which itself automatically wraps around bones as they move. Our C++ implementation can decompose the volume into muscle fibres, which is done by a slice-by-slice morphing of predefined fibres template into the muscle volume, and visualise the result in only about 1000 ms on commodity hardware. Hence, the method is fast enough to be suitable for interactive educational medical software. Although a biomechanical assessment has yet to be done, we believe that the method could be used also in clinical biomechanical applications to extract information on the current muscle lever arm and fibre path and, thanks to its rapid processing speed, it might be an attractive alternative to current methods.

Abstract: This study suggests an approach for the comparison and evaluation of particular compartments with modest experimental setup costs. A glucose level prediction model was used to evaluate the compartment's glucose transport rate across the blood capillary membrane and the glucose utilization rate by the cells. The glucose levels of the blood, subcutaneous tissue, skeletal muscle tissue, and visceral fat were obtained in experiments conducted on hereditary hypertriglyceridemic rats. After the blood glucose level had undergone a rapid change, the experimenter attempted to reach a steady blood glucose level by manually correcting the glucose infusion rate and maintaining a constant insulin infusion rate. The interstitial fluid glucose levels of subcutaneous tissue, skeletal muscle tissue, and visceral fat were evaluated to determine the reaction delay compared with the change in the blood glucose level, the interstitial fluid glucose level predictability, the blood capillary permeability, the effect of the concentration gradient, and the glucose utilization rate. Based on these data, the glucose transport rate across the capillary membrane and the utilization rate in a particular tissue were determined. The rates obtained were successfully verified against positron emission tomography experiments. The subcutaneous tissue exhibits the lowest and the most predictable glucose utilization rate, whereas the skeletal muscle tissue has the greatest glucose utilization rate. In contrast, the visceral fat is the least predictable and has the shortest reaction delay compared with the change in the blood glucose level. The reaction delays obtained for the subcutaneous tissue and skeletal muscle tissue were found to be approximately equal using a metric based on the time required to reach half of the increase in the interstitial fluid glucose level.

Abstract: As a part of research on glucose transporters, I already proposed a hypothesis that the change of the blood glucose level includes information about the estimated rate with which the hypothalamus expects the blood glucose level to return to normal range, by means of regulatory mechanisms of glucose homeostasis. As the interstitial glucose level change reflects the blood glucose level change, I proposed a method to estimate the blood-to-interstitial glucose level delay prior formulating the hypothesis. For the estimation, measured glucose levels can be either approximated or interpolated. Each method has its pros and cons. However, the estimated delay converges into narrower bounds, as more glucose levels are measured, if the measured glucose levels are interpolated. In this paper, I present further details on the interpolation method which were not presented in previously published papers.

Abstract: A lot of laboratories deal with management of experimental data. When experiments are conducted inside the laboratory, their results and their data/metadata are immediately stored using a common computer connected to the Internet. On the other hand, situations when the computer is not available, are frequent. It includes e. g. work outside the laboratory or discussions during scientific meetings. This work describes an android-based system developed to enable management of experiments outside the laboratory. Collected experiments are synchronized with a system intended for a long term storage and management of experimental data/metadata - the EEG/ERP Portal.

Abstract: Large amounts of EEG/ERP (electroencephalography, event-related potential) data, various data formats and non-standardized domain description lead to incompatible results and interpretations of EEG/ ERP experimental data/metadata and to difficult communication between interested laboratories. Authors' research group has solved these problems and has contributed to the building of a neuroinformatics infrastructure by developing and integrating data management and analytic tools for EEG/ERP research. The model of the software and hardware infrastructure for electrophysiology, and the context and architecture of the developed EEG/ERP Portal, serving to manage, share and process EEG/ERP experiments, are presented. Other additional tools are briefly described.

Abstract: In this paper we present an interpolation method that was derived from the muscle deformation algorithm computed on the gradient domain deformation technique. The method uses linear constraints to preserve the local shape of the muscle and the non-linear volume constraints to preserve the volume of the mesh. The Gauss-Newton method with Lagrange multipliers is used as the main computation algorithm and the interpolation approach serves especially to smooth up deformation steps. Thanks to the interpolation of main bones movement positions by several temporally interpositions, the large distances are optimized and the muscles of the musculoskeletal model are deformed in a more realistic way. The method was implemented in C++ language, using VTK framework and was integrated into the human body framework. Despite the fact that the current implementation is not optimised, all muscles tested were processed in a few minutes on commodity hardware, which is much faster in comparison with the traditional FEM approaches.

Abstract: The P300 component is an event-related potential associated with the process of decision making. Its accurate detection in electroencephalographic signal is essential for P300-based brain-computer interfaces. This paper proposes a new method for the P300 detection based on discrete wavelet transform. Its benefits were tested with five healthy subjects using voting classification algorithm. The accuracy of 74.4% was achieved for single trials and over 90% accuracy for averaging.

Abstract: In many biomechanical problems, the availability of a suitable model for the wrapping of muscles when undergoing movement is essential for the estimation of forces produced on and by the body during motion. This is an important factor in the VPHOP project which is investigating the likelihood of fracture for osteoporotic patients undertaking a variety of movements. The weakening of their skeletons makes them particularly vulnerable to bone fracture caused by excessive loading being placed on the bones, even in simple everyday tasks. This paper provides an overview of a novel volumetric model that describes muscle wrapping around bones and other muscles during movement and which includes a consideration of how the orientations of the muscle fibres change during the motion. The method can calculate the form of wrapping of a muscle of medium size and visualize the outcome within tenths of seconds on commodity hardware, while conserving muscle volume. This makes the method suitable not only for educational biomedical software but also for clinical applications used to identify weak muscles that should be strengthened during rehabilitation or to identify bone stresses in order to estimate the risk of fractures.

Abstract: For neurophysiological data sharing, it is vital for researchers to validate their data from different perspectives. Detection of eye artifacts is especially important since the artifacts may distort the data to an unacceptable extent. Most methods for their correction either require EOG channels or they are very time consuming. This paper proposes a fast method that does not require EOG channels. It outperforms amplitudebased methods in accuracy and Independent Component Analysis in computational complexity.

Abstract: EEG/ERP (electroencephalography, event related potential) laboratories produce experimental data and metadata. Large amounts of data and various data formats lead to incompatible results and difficult communication among laboratories. Authors' research group has contributed to the building of a neuroinformatics infrastructure by developing and integrating data management and analytic tools for EEG/ERP research. In addition, a module integrated within the EEG/ERP Portal allowing to process experimental data using analytic tools is developed. An integration of the EEG/ERP Portal with other systems is ensured using web services.

Abstract: This article is focused on development of a tool supporting physicians with an appropriate treatment decisions at patients with acute ischemic stroke. The automated tools for infarction core area delineation could provide important information about the volume of the infarction core. This article describes such automated method results used on both cerebral and perfusion blood volume computed tomography maps compared with manual infarction core delineations made by two physicians.

Abstract: In our contemporary research we are trying to develop the artificial neural network (ANN) model for the prediction of outcome after the occurrence of stroke. This paper mentions some important facts about stroke as well as the urgent need for Computer Assisted Decision Support (CAMS) systems in the relation to clinical practice. The short review of related studies of ANN in medicine is included. The model input and output parameters were selected and are also described. The basic ANN design for the predictive model is mentioned together with the future directions of our research.

Abstract: Attention of drivers is a key factor of road safety. Inattentive drivers are dangerous to their surroundings and cause a considerable number of accidents. However, decline of attention, especially during long rides, is natural and it is worth to know if it can be investigated from electric activity of the brain. Since there is an evidence of relationship between attention and P3 component which is widely used in design and analysis of experiments by the method of event related potentials (ERPs), the ERP experiment based on auditory stimulation was designed and performed on tested subjects, which drove a car simulator on a monotonous track. The background of the used method, experimental design, data processing, and results of the performed experiments are described in this paper.

Abstract: This paper proposes a gradient domain deformation for wrapping surface models of muscles around bones as they move during a simulation of physiological activities. Each muscle is associated with one or more poly-lines that represent the muscle skeleton to which the surface model of the muscle is bound so that transformation of the skeleton (caused by the movement of bones) produces transformation of the vertices of the mesh subject to Laplacian linear constraints to preserve the local shape of the mesh and non-linear volume constraints to preserve the volume of the mesh. All these constraints form a system of equations that is solved using the iterative Gauss-Newton method with Lagrange multipliers. Our C++ implementation can wrap a muscle of medium size in about a couple of ms up to 400 ms on commodity hardware depending on the type of parallelization, whilst it can keep the change in volume below 0.04%. A preliminary biomechanical assessment of the proposed technique suggests that it can produce realistic results and thanks to its rapid processing speed, it might be an attractive alternative to the methods that are used in clinical practise at present.

Abstract: This paper deals with influence of mental load on drivers? attention. EEG (electroencephalography) and ERP (event related potentials) techniques are used for investigation of the level of drivers? attention. A short overview of experiments dealing with drivers? attention is given and the ERP technique and the P3 component are described. General assumptions related to P3 amplitude and P3 latency are introduced. Then experimental design and the course of the experiment are described. The resulting EEG/ERP data are analyzed and their interpretation is provided.

Abstract: "Since the evoked responses obtained by stimulation are much weaker than the continuous electroencephalographic signal, the correct signal analysis enhances stimulation-driven signal components. The paper proposes methods for event-related potential processing for brain-computer interfaces based on matching pursuit. The suggested method is compared with another simple method which is frequently used for feature extraction. A multi-layer perceptron was used for classification. The results can be used to improve the feature extraction for BCI systems."

Abstract: The most indicated imaging technique before operations is computed tomography. Preoperative deliberation requires not only its own evaluation of pathological findings, but also the overall anatomy, perfusion and volume of various anatomical parts, which must be accurately identified. There is a wide range for computer-assisted diagnosis, which should reduce and refine the assessment carried out by man and help better decide on the appropriate therapeutic procedure (resection, multiphase power, chemotherapy, ablation methods), and, among other things, reduce the number of unnecessary surgical procedures while on the other hand enabling the implementation of extensive resection. We aims to create a comprehensive system for computed imaging, which would allow the detection and analysis of focal lesions, determination of their segmental localisation, assessment of perfusion conditions and performance of a virtual resection including the establishment of volume resected and organ remaining. Such a system is not yet commercially available.

Abstract: The MetaMed is a tool for data and meta data extraction primarily from a heterogeneous medical data. It is a non-interactive command line open source application for processing a large amount of data. An extracted meta data is stored in the Resource Description Framework and is structured by OWL ontologies. It enables a semantic interoperability. Meta data as an index data prevents us to solve different file format and version of raw files again and again for a following research. It enables a better performance. Indexed data can be directly used in a user interface and querying for an appropriate raw data can be done. The MetaMed and the research information system is confirmed with research primarily focused on a cerebrovascular diseases.

Abstract: This paper describes a method that represents a muscle by a realistic chaff of muscle fibres that are automatically generated in the volume defined by the surface mesh of the muscle which itself automatically wraps around bones as they move. Our C++ implementation can decompose the volume into muscle fibres, which is done by a slice-by-slice morphing of predefined fibres template into the muscle volume, and visualise the result in only about 1000 ms on commodity hardware. Hence, the method is fast enough to be suitable for interactive educational medical software. Although a biomechanical assessment has yet to be done, we believe that the method could be used also in clinical biomechanical applications to extract information on the current muscle lever arm and fibre path and, thanks to its rapid processing speed, it might be an attractive alternative to current methods.

Abstract: The EEG/ERP (Electroencephalography/Even- Related Potentials) Portal serves for storage and management of ERP experiments. The protocols describing these experiments are designed and implemented using various software applications and/or hardware devices. Some protocols are kept in XML files and stored in the EEG/ERP portal database as LOB (Large Object) data types. Since it is important for researchers to directly find details about design of the ERP protocols in the related XML files and it is also hard to use LOB data for generating the semantic web output, storage types provided by the Oracle 11g database system were investigated and compared. Therefore a new model of storage of ERP protocols is introduced. This model is finally simplified after analysis of results of performance tests.

Abstract: There is a problem with global search and data sharing. Our research group developed the EEG/ERP (electroencephalography, event-related potentials) portal; a system for storage and management of EEG/ERP resources - data, metadata, tools and materials related to EEG/ERP experiments. The EEG/ERP portal and existing solutions of data integration are presented. Authors registered the EEG/ERP portal as a source of neuroscience data and metadata within the world known project - Neuroscience Information Framework (NIF). Developed web services for harvesting EEG/ERP scenarios and experiments within NIF are presented.

Abstract: Glucose is an important source of energy for cells. In clinical practice, we measure glucose level in blood and interstitial fluid. Each method has its pros and cons, and both levels correlate with each other. As the body tries to maintain the glucose level within a particular range to avoid adverse effects, it is desirable to predict future glucose levels in order to aid provided health care. We can see this desire in research, e.g. research on glukose transporters of cells. As yet another example, we can see it with diabetic patients, patients in a metabolic intensive care unit, particularly. In this paper, a glucose level prediction method is proposed.

Abstract: The Kohonen Self-organizing Feature Map (SOM) has been developed for clustering input vectors and for projection of continuous high-dimensional signal to discrete low-dimensional space. The application area, where the map can be also used, is the processing of text documents. Within the project WEBSOM, some methods based on SOM have been developed. These methods are suitable either for text documents information retrieval or for organization of large document collections. All methods have been tested on collections of English and Finnish written documents. This article deals with the application of WEBSOM methods to Czech written documents collections. The basic principles of WEBSOM methods, transformation of text information into the real components feature vector and results of documents classification are described. The Carpenter-Grossberg ART-2 neural network, usually used for adaptive vector clustering, was also tested as a document categorization tool. The results achieved by using this network are also presented.

Abstract: Study deals with attention deficit and hyperactivity disorder with connection to coordination disorder. Aim of study is to assess differences in attention according to motor development in preschool children. Sixteen children with mean age of 5,87 (SD ? 0,55) participated in study. To assess a motor development TGMD - 2 was used. The attention was measured through the electric activity of brain and analysis of evoked potentials. The results confirm assumption that children with coordination disorder to suffer from disorder in visuospatial attention and also attention deficit to acoustic stimuli. Together with worse processing and information storage it can cause of coordination disorder and problems in motor learning as well.

Abstract: Because the Semantic Web uses its technologies for presenting data/metadata on the web and common systems are based on object-oriented languages a need for suitable mapping is emerging. This paper describes the difficulties during transformation of data layer represented by object-oriented code into the semantic web structures (OWL, RDF). Since there is difference between semantic expressivity of these data representations it is necessary to fill this semantic gap. Authors investigate these differences in semantics and provide a preliminary idea to add missing semantics into the Java code using Java annotations. These annotations are consequently processed by the proposed framework. The transformation is demonstrated within the EEG/ERP Portal.

Abstract: The paper introduces a system for EEG/ERP (electroencephalography, event-related potentials) data and metadata storage and processing. Since researchers have difficulties with a suitable long-term storage and management of electrophysiology data the presented system helps them to increase both efficiency and effectiveness of their work by providing the means for the storage, management, search and sharing of EEG/ERP data. The requirements specification including the system context, system requirements, project scope, basic features, system users, and data formats and metadata structures is presented. The database structure is proposed; upload, download and interchange of EEG/ERP data and metadata using the web interface are described. The system architecture, used technologies and final realization are described. Data and metadata search and user accounts including system security management are presented. Additional tools and structures as converters of data formats and semantic web ontology are mentioned.

Abstract: The event-related potentials (ERPs) obtained by stimulation are much weaker than the continuous electroencephalographic(EEG) signal. Therefore, the correct signal analysis is vital to detect the stimulation-driven signal components. This paper proposes the combination of matching pursuit for feature extraction and ART 2 neural network for clustering. Then, clusters are filtered and interpreted according to their statistical properties as ERP components or noise. The suggested method can be used to filter the EEG/ERP signal. Furthermore, its results lead to a method that improves averaging when compared to traditional approaches.

Abstract: The musculoskeletal modelling and simulation is an essential step in the process of looking for an optimal strategy to provide patients su?ering from various musculoskeletal disorders, such as osteoporosis, with better health care. In our previous work, we proposed a deformation method suitable for clinical practise that deforms each muscle represented by a surface mesh according to assigned skeleton action lines and preserves its inner volume at the same time. It is built on combination of linear constraints for surface description together with relation of surface to control skeleton and non-linear constraint of volume preservation. It uses Gauss-Newton based iterative solver to ?nd energy minimum ful?lling these conditions. It gains extra performance from exploiting the coarse outer hull for potentially slow and numerically unstable calculations. It achieves excellent ratios of volume preservation and maintains reasonable times in hundreds of milliseconds for our typical meshes, but since each mesh is deformed independently to others, it is unable to provide deformation of multiple interacting meshes without danger of their mutual intersections. This is why a new modi?cation of the method is introduced in this paper that alters both constraint formulation and the iterative solver algorithm to ?x and prevent major intersections between mesh surfaces. It detects and prevents initial intersection in the starting pose of meshes and then prevents new intersections during the solution by constraining the modi?cation step of meshes. It however still considers importance of volume preservation and tries to minimise e?ect of changes on its maintenance. The method was implemented using C++ language and VTK framework and integrated to our human body framework. The results of application to medical data we use show that despite a few open issues, the proposed technique has its merit.

Abstract: When we are processing large quantity of a data, and/or we are computing complex tasks, computational performance of one computer is not enough. Solution is parallel processing. However proper approach to parallel programming doesn't need to well-known to medical experts or computational tool doesn't have native support for parallel programming. Our goal is to design unified interface, which allows parallel approach to our medical researchers. It must provide support for existing medical experiments and it must provide full interoperability.

Abstract: This paper deals with a suitable method for decomposition of EEG/ERP signal to waveforms which are grouped is such way that one or few groups contain ERP P3 waveforms. At the beginning, the EEG/ERP domain is briefly introduced and essential information about EEG and ERP signals is given. Then, the method for waveforms grouping based on matching pursuit algorithm with Gabor dictionary as a preprocessing method for feature extraction for ART2 neural network is explained in detail. Emphasis is placed on selection of suitable feature extraction method. Comparison of tested feature extraction methods and summarization is given at the end.

Abstract: We provide an overview of the association between vitamin D and some neurological diseases where the correlation has repeatedly been described. The majority of literature refers to cerebrovascular diseases, followed by multiple sclerosis and cognitive disorders. Vitamin D hypovitaminosis might be associated with the diseases directly or it might contribute to the disease risk factors (typically in cerebrovascular events). Vitamin D hypovitaminosis may also play a role in patients with residual functional involvement due to a neurological disorder (movement disorders, lack of self-sufficiency) and worsen functional status owing to muscle weakness, instability and falls.

Abstract: This software solves difficulties related to running of signal processing methods. Although several systems that implement signal processing methods exist, their sharing and remote calling is not satisfactorily solved. This software is a custom server-side approach that provides a powerful plug-in engine for integration of signal processing methods. The plug-in engine ensures high modularity and flexibility of the system. Since the implemented methods are accessible via the SOAP Web Service, integration with another system is available. There is also possible to use the system locally via a web browser. The set of basic methods is already implemented.

Abstract: The EEG/ERP (Electroencephalography/Even- Related Potentials) Portal serves for storage and management of ERP experiments. The protocols describing these experiments are designed and implemented using various software applications and/or hardware devices. Some protocols are kept in XML files and stored in the EEG/ERP portal database as LOB (Large Object) data types. Since it is important for researchers to directly find details about design of the ERP protocols in the related XML files and it is also hard to use LOB data for generating the semantic web output, storage types provided by the Oracle 11g database system were investigated and compared. Therefore a new model of storage of ERP protocols is introduced. This model is finally simplified after analysis of results of performance tests.

Abstract: The dissertation focuses on the matters of interface between the human brain and computer (Brain Computer interface) that enables direct communication of a human being with a computer, at this time only in direction from the human towards the computer. The theoretical part of the dissertation covers current matters of direct communication between the human and the computer through the electroencephalography (EEG), processing methods of evoked potentials and possibilities of adaptation and their respective usage in the field of BCI systems. The second part of the work encompasses the proposal and verification of the original adaptation method for the BCI system. To reach this aim a system concept was proposed which was further replenished by various aspects improving its features and results. The author proved in his work that the adaptation represents a way to the creation of the BCI system capable of good understanding of a random subject, who begins to operate the developed system.

Abstract: The book describes many aspects of the reliability of interactions among drivers and their vehicles; this reliability attracts the interest of researchers in many countries for a long time. The field of driver-car interaction reliability involves extremly wide spectrum of aspects concerning many areas of science and technology. Therefore a well cooperated group of specialists of 11 Czech universities, research institutes and industrial companies was estabilished with the aim to solve the main problems of the interaction reliability between road vehicle and its driver. The knowledge reached in this area are presented in this book and it will be very useful for all people who will continue in this research.

Abstract: This article proposes automated approach for whole brain infarction core delineation while using only non-contrast computed tomography and computed tomography angiography. The main aim is to provide additional information measuring infarction core volume while exceeding certain level is contraindication of early recanalization. Process of generation of Perfusion Blood Volume maps is described first followed by description of process of infarction core delineation. Verification of correctness is based on comparison against follow-up examinations. Discussion and future works summarizes weaknesses of the method and steps for improvement.

Abstract: Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burned-in annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.

Abstract: The paper deals with ERP (Event related potentials) components detection using wavelet transform (both continuous and discrete form), matching pursuit algorithm and Hilbert-Huang transform. The EEG/ERP domain is shortly introduced and essential information about EEG and ERP signals is given. The wavelet transform, matching pursuit algorithm, and Hilbert-Huang transform are introduced and their suitability for ERP components detection is described. Experimental results obtained by using these algorithms for P3 component detection are summarized.

Abstract: The paper deals with ERP (Event related potentials) components detection using wavelet transform and matching pursuit algorithm. The EEG/ERP domain is shortly introduced and essential information about EEG and ERP signals is given. The wavelet transform, matching pursuit algorithms and its modification are introduced and their suitability for ERP components detection is described. Experimental results obtained by using these algorithms for P3 component detection are summarized.

Abstract: The pancreas, liver and hypothalamus have a regulatory function in the glucose homeostasis. As the blood glucose level changes, these compartments react and the level changes again. Subsequently, the interstitial glucose level changes with some delay. I propose a hypothesis that the change of the blood glucose level includes information about the estimated rate with which the hypothalamus expects the blood glucose level to return to normal range by means of regulatory mechanisms. Also, I propose a method to estimate the blood-to-interstitial glucose level delay. With this delay, it was possible to relate the present blood glucose level and future interstitial glucose level with such coefficients, which do not seem to change over the time of the experiment to a significant extent. Perhaps, it is a parameterization of the regulatory processes, which could be possibly encoded within hypothalamus set-points.

Abstract: Several modifications of the Hilbert-Huang transform are presented in this paper. Modifications were designed to restrain the over/undershoot effect oc- curring when envelopes are being calculated. My modifications contribute to better estimation of additional extrema and improve the results acquired from processing the EEG signal (even when it is contamined with artifacts). They make the empirical mode decomposition faster and the decomposed IMFs cor- responds more with the original EEG signal.

Abstract: This preliminary paper deals with influence of mental load on driver?s attention. EEG (electroencephalography) and ERP (Event related potentials) techniques are used for investigation of the level of driver?s attention. A short overview of experiments dealing with drivers? attention is given and the ERP technique and the P3 component are described. General assumptions related to P3 amplitude and P3 latency are introduced. Then experimental design is described. At present the resulting EEG/ERP data are analyzed and their interpretation will be provided during congress presentation and in the final version of the paper.

Abstract: This paper deals with the processing of signals from EEG/ERP experiments. Selected methods for EEG/ERP signal processing are shortly presented. Since these methods are usually implemented for various platforms and within various tools, a new designed and developed software system, which allows users running them uniformly, is presented. The methods are added and processed as plug-ins. It ensures a high modularity and flexibility of the system. The main system components (JERPA, JUIGLE) are introduced and shortly described.

Abstract: Brain research is currently a rapidly growing scientific field. Large amounts of data, various data formats and non-standardized domain descriptions lead to incompatible results and interpretations of neuroscientific data and to difficult communication between laboratories and scientific teams. Neuroinformatics, a newly established scientific field, provides integration across all levels and scales of neuroscience. Our research group has contributed to the building of a neuroinformatics infrastructure by developing and integrating data management and analytic tools for EEG/ERP (electroencephalography, event-related potential) research.

Abstract: The cerebrovascular diseases research are based on real patient's data received from a collaborating centre. The goal of research is to take advantage of heterogeneous medical data relationships. Medical data relationships leads to get more data mining facilities in studying of dependencies and crucial values of parameters in a huge volume of real imaging examinations with clinical and therapeutic data. There are lot of difficulties and security issues when providing research on medical data. All real patient's identifiers must be removed for privacy reasons. A research team does not necessity know the patient identity information. We keep limited characteristics only and can be accessible to patient's medical doctors. These characteristics are useful to provide us analysis and statistics results. The aggregated results are publicly available.

Abstract: The paper shortly describes EEG/ERP domain and the system for storage and management of data and metadata from EEG/ERP experiments. The system has been developed using common technologies and data structures (object oriented code, relational database). A registration of the system as a recognized data source requires representation of its data and metadata by semantic web resources. A short overview of differences between common data structures and semantic web representations is given and possible approaches to automated transformation of data and metadata from common data structures are mentioned. The existing semantic web frameworks and tools, widely tested for our purposes, are listed. Finally, the integration of selected tools and the software solution for automated transformation from the relational database to a semantic web representation is described.

Abstract: Generally, the interoperability is the key feature to any widely used application or an information system. A system build on the basis of semantic data interpretation can also lead to an easy extensible and adaptable system, in the future. Otherwise, you have to deal with a lack of agreed terminologies or codes between standards e.g. DASTA vs. HL7, different coding structures and even variety of file formats or inconsistent database table schema. The most of these difficulties can be solved by the semantically interoperable system. We present our implementation strategy and meta data extraction methods for a research information system with an heterogeneous medical data. The medical data can have different origin, type, file format and even its version. We discuss the research information system that we primarily use for cerebrovascular brain diseases research.

Abstract: This paper deals with the software infrastructure for EEG/ERP (electroencephalography, event related potentials) research. The requirements for building this infrastructure have arisen from laboratory needs, unavailability of appropriate software tools and incompatibility of previously used commercial solutions. The standardization of EEG/ERP data formats and construction of complex and publicly open software infrastructure is also supported by International Neuroinformatics Coordinating Facility (INCF) since these efforts can significantly accelerate brain research. The presented software infrastructure includes the web based EEG/ERP portal as the central data storage for data/metadata obtained in EEG/ERP experiments and JERPA software as the desktop software tool for computationally demanding operations. Supporting libraries (e.g. library of signal processing methods), developed and integrated to EEG/ERP portal and/or JERPA software, are briefly described.

Abstract: This paper deals with difficulties occurring during transformation of schema and data from an object-oriented code to a semantic web representation (RDF, OWL). The authors describe differences in semantic expressivity between the object-oriented approach and the semantic web approach and look for the ways to fill this semantic gap. Then some existing approaches with their difficulties are introduced and a preliminary idea using Java annotations is proposed. Java annotations add missing semantic information into Java code, which is consequently processed by the proposed framework and serialized into output semantic web structure (OWL).