<div class="csl-bib-body">
<div class="csl-entry">Lohninger, T. (2021). <i>Impact of a driven right leg electrode to reduce signal noise in a low-cost EEG</i> [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.69408</div>
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dc.identifier.uri
https://doi.org/10.34726/hss.2021.69408
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/18693
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dc.description.abstract
The EEG is a powerful and yet easy to use tool to measure the brain activity of a person. It can help analyzing reactions in the patient’s brain with a high temporal resolution and without the danger that comes with the exposure to radiation or strong magnetic fields as it is the case for several other methods found in this field of research. Due to the relatively low hardware costs and the potential to build one without the need of access to high precision manufacturing facilities the EEG is of special interest in private research activities.The aim of this thesis is to shine light on the theoretical aspects of building an EEG and the obstacles that present themselves while doing so. Furthermore, once the EEG is built, the influence of the use of a driven right leg electrode on the signal quality is shown and compared with use of a digital signal filter. This method of noise filtering is expected to produce meaningful improvements while conducting measurements. The knowledge gained from this experiment will not only provide a useful insight on creating stable measuring conditions but can also serve as a valuable foundation for further research done on the use of the EEG as a brain machine interface.
en
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
EEG
en
dc.subject
noise
en
dc.subject
filter
en
dc.title
Impact of a driven right leg electrode to reduce signal noise in a low-cost EEG
en
dc.type
Thesis
en
dc.type
Hochschulschrift
de
dc.rights.license
In Copyright
en
dc.rights.license
Urheberrechtsschutz
de
dc.identifier.doi
10.34726/hss.2021.69408
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dc.contributor.affiliation
TU Wien, Österreich
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dc.rights.holder
Thomas Lohninger
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dc.publisher.place
Wien
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tuw.version
vor
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tuw.thesisinformation
Technische Universität Wien
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dc.contributor.assistant
Fellner, Andreas
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tuw.publication.orgunit
E101 - Institut für Analysis und Scientific Computing