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Development coordination disorder in children ? experimental work and data annotation

VAŘEKA, L., BRŮHA, P., MOUČEK, R., MAUTNER, P., ČEPIČKA, L., HOLEČKOVÁ, I. Development coordination disorder in children ? experimental work and data annotation. GigaScience, 2017, roč. 6, č. 4, s. 1-6. ISSN: 2047-217X
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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.

Data Format for Storing ANT Sensors Data

JEŽEK, P., MOUČEK, R. Data Format for Storing ANT Sensors Data. In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies. Setúbal: ScitePress, 2017. s. 396-400. ISBN: 978-989-758-213-4
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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.

Exercise and Wellness Health Strategy Framework Software Prototype for Rapid Collection and Storage of Heterogeneous Health Related Data

BRŮHA, P., MOUČEK, R., ŠNEJDAR, P., BOHMANN, D., KRAFT, V., ŘEHOŘ, P. Exercise and Wellness Health Strategy Framework Software Prototype for Rapid Collection and Storage of Heterogeneous Health Related Data. In Proceedings of BIOSTEC 2017 - Volume 5: HEALTHINF. Setúbal: SciTePreess, 2017. s. 477-483. ISBN: 978-989-758-213-4
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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.

Experimental Design and Collection of Brain and Respiratory Data for Detection of Driver´s Attention

MOUČEK, R., HNOJSKÝ, L., VAŘEKA, L., PROKOP, T., BRŮHA, P. Experimental Design and Collection of Brain and Respiratory Data for Detection of Driver´s Attention. In BIOSTEC 2017 Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies Volume 5: HEALTHINF. Setúbal: SciTePress, 2017. s. 441-450. ISBN: 978-989-758-213-4
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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.

Statistic of Quasi?Periodical Signal with Random Period ? First Application on Vocal Cords Oscillation

KROUPA, L., VÁVRA, F., NOVÝ, P. Statistic of Quasi?Periodical Signal with Random Period ? First Application on Vocal Cords Oscillation. In 16th CONFERENCE ON APPLIMAT MATHEMATICS APLIMAT 2017 PROCEEDINGS. Bratislava: Vydavateľstvo Spektrum STU, Bratislava, 2017. s. 905-911. ISBN: 978-80-227-4650-2
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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.

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