Cloud Infrastructure for Storing and Processing EEG and ERP Experimental Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43955129" target="_blank" >RIV/49777513:23520/19:43955129 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5220/0007746502740281" target="_blank" >http://dx.doi.org/10.5220/0007746502740281</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0007746502740281" target="_blank" >10.5220/0007746502740281</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cloud Infrastructure for Storing and Processing EEG and ERP Experimental Data

Popis výsledku v původním jazyce

Current infrastructures for experimental data, results and computational tools make a shift from locally maintained solutions to remote cloud-based infrastructures. It brings a higher availability, sustainability and performance. However, specifics of different research areas require development of customized solutions for individual research domains. For example, electroencephalography and event-related potentials (EEG/ERP) use specific devices, data formats and machine learning workflows. As a solution, a cloud-based system for the EEG/ERP domain containing a distributed data storage, a signal processing method library and a client GUI is presented. The signal processing method library is used for training of classifiers and classifying the data in the cloud-based system controlled by the GUI. The presented system was tested using a machine learning workflow based on the data stored in the system. In the workflow, various classifiers were trained and their parameters stored into the system. Finally, testing data were classified using previously trained classifiers.

Název v anglickém jazyce

Cloud Infrastructure for Storing and Processing EEG and ERP Experimental Data

Popis výsledku anglicky

Current infrastructures for experimental data, results and computational tools make a shift from locally maintained solutions to remote cloud-based infrastructures. It brings a higher availability, sustainability and performance. However, specifics of different research areas require development of customized solutions for individual research domains. For example, electroencephalography and event-related potentials (EEG/ERP) use specific devices, data formats and machine learning workflows. As a solution, a cloud-based system for the EEG/ERP domain containing a distributed data storage, a signal processing method library and a client GUI is presented. The signal processing method library is used for training of classifiers and classifying the data in the cloud-based system controlled by the GUI. The presented system was tested using a machine learning workflow based on the data stored in the system. In the workflow, various classifiers were trained and their parameters stored into the system. Finally, testing data were classified using previously trained classifiers.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

ISBN

978-989-758-368-1

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

274-281

Název nakladatele

SciTePress

Místo vydání

Setúbal

Místo konání akce

Heraklion, Crete

Datum konání akce

2. 5. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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