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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.

EEGbase - portal for management of electrophysiological experiments

MOUČEK, R., JEŽEK, P., KRAUZ, J., ŠTĚBETÁK, J., PROKOP, T., RINKES, J., BYDŽOVSKÝ, M., BRŮHA, P. EEGbase - portal for management of electrophysiological experiments. 2015.
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EEGbase is a web portal for long-term storage, annotation, management and sharing of data and metadata from electrophysiological experiments. It is an essential upgrade of previous research prototype and is intended for further commercialization. After free registration the portal allows users to work in a user-defined groups. It uses standard terminology for domain description. However, the template system allows the definition of custom metadata for each experimental scenario. Experiments carried out according to the same or similar experimental scenarios and granted under the same license can be grouped into packages of experiments. Users can assign licenses and sales prices to their experiments and packages of experiments and then provide them to other entities. The portal was developed within the project Pre-seed CZ.1.05/3.1.00/14.0298 Technological verification of the results of research and development I. The project repository is available at https://github.com/INCF/eeg-database. The portal is available at http://eegdatabase.kiv.zcu.cz/. It currently offers more than 700 experiments.

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