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Towards a software architecture for neurophysiological experiments

Type
conference paper
Date Issued
2019
Author(s)
Ioannou, Constantina
;
Kindler, Ekkart
;
Bækgaard, Per
;
Saqid, Shazia
;
Weber, Barbara  
Abstract (De)
Despite their wide adoption for conducting experiments in numerous domains, neurophysiological measurements often are time consuming and challenging to interpret because of the inherent complexity of deriving measures from raw signal data and mapping measures to theoretical constructs. While significantefforts have been undertaken to support neurophysiological experiments, the existing software solutions are non-trivial to use because often these solutions aredomain specific or their analysis processes are opaque to the researcher. This paper proposes an architecture for a software platform that supports experimentswith multi-modal neurophysiological tools through extensible, transparent and repeatable data analysis and enables the comparison between data analysis processes to develop more robust measures. The identified requirements and the proposed architecture are intended to form a basis of a software platform capable of conducting experiments using neurophysiological tools applicable to various domains.
Language
English
Keywords
Neurophysiological tools
Software architecture
Neurophysiological experiments
HSG Classification
contribution to scientific community
Event Title
Proceedings of the NeuroIS Retreat 2019
Event Location
Vienna, Austria
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/99326
Subject(s)

computer science

Division(s)

ICS - Institute of Co...

SCS - School of Compu...

Eprints ID
258715
File(s)
Thumbnail Image
Name

NeuroIS.pdf

Size

354.34 KB

Format

Adobe PDF

Checksum (MD5)

d4b021adb8af3d67b2d6c495a5acfcc8

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