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  2. School of Engineering
  3. Publikationen
  4. Publikationen School of Engineering
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dc.contributor.authorIturrate, Iñaki-
dc.contributor.authorChavarriaga, Ricardo-
dc.contributor.authorMillán, José del R.-
dc.date.accessioned2020-07-20T08:05:14Z-
dc.date.available2020-07-20T08:05:14Z-
dc.date.issued2020-03-
dc.identifier.isbn978-0-444-63934-9de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/20278-
dc.description.abstractBrain-computer interfaces (BCIs) are systems that translate brain activity patterns into commands that can be executed by an artificial device. This enables the possibility of controlling devices such as a prosthetic arm or exoskeleton, a wheelchair, typewriting applications, or games directly by modulating our brain activity. For this purpose, BCI systems rely on signal processing and machine learning algorithms to decode the brain activity. This chapter provides an overview of the main steps required to do such a process, including signal preprocessing, feature extraction and selection, and decoding. Given the large amount of possible methods that can be used for these processes, a comprehensive review of them is beyond the scope of this chapter, and it is focused instead on the general principles that should be taken into account, as well as discussing good practices on how these methods should be applied and evaluated for proper design of reliable BCI systems.de_CH
dc.language.isoende_CH
dc.publisherElsevierde_CH
dc.relation.ispartofHandbook of Clinical Neurology ; 168de_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectArtifactde_CH
dc.subjectBrain-computer interfacede_CH
dc.subjectBrain–machine interfacede_CH
dc.subjectClassificationde_CH
dc.subjectCross-validationde_CH
dc.subjectFeaturede_CH
dc.subjectFilteringde_CH
dc.subjectInformation transfer ratede_CH
dc.subjectMachine learningde_CH
dc.subjectPerformance evaluationde_CH
dc.subjectRegressionde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleGeneral principles of machine learning for brain-computer interfacingde_CH
dc.typeBuchbeitragde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1016/B978-0-444-63934-9.00023-8de_CH
dc.identifier.pmid32164862de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end328de_CH
zhaw.pages.start311de_CH
zhaw.parentwork.editorMillan, José del R-
zhaw.parentwork.editorRamsay, Nick F.-
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedMachine Perception and Cognitionde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Iturrate, I., Chavarriaga, R., & Millán, J. d. R. (2020). General principles of machine learning for brain-computer interfacing. In J. d. R. Millan & N. F. Ramsay (Eds.), Handbook of Clinical Neurology ; 168 (pp. 311–328). Elsevier. https://doi.org/10.1016/B978-0-444-63934-9.00023-8
Iturrate, I., Chavarriaga, R. and Millán, J.d.R. (2020) ‘General principles of machine learning for brain-computer interfacing’, in J.d.R. Millan and N.F. Ramsay (eds) Handbook of Clinical Neurology ; 168. Elsevier, pp. 311–328. Available at: https://doi.org/10.1016/B978-0-444-63934-9.00023-8.
I. Iturrate, R. Chavarriaga, and J. d. R. Millán, “General principles of machine learning for brain-computer interfacing,” in Handbook of Clinical Neurology ; 168, J. d. R. Millan and N. F. Ramsay, Eds. Elsevier, 2020, pp. 311–328. doi: 10.1016/B978-0-444-63934-9.00023-8.
ITURRATE, Iñaki, Ricardo CHAVARRIAGA und José del R. MILLÁN, 2020. General principles of machine learning for brain-computer interfacing. In: José del R MILLAN und Nick F. RAMSAY (Hrsg.), Handbook of Clinical Neurology ; 168. Elsevier. S. 311–328. ISBN 978-0-444-63934-9
Iturrate, Iñaki, Ricardo Chavarriaga, and José del R. Millán. 2020. “General Principles of Machine Learning for Brain-Computer Interfacing.” In Handbook of Clinical Neurology ; 168, edited by José del R Millan and Nick F. Ramsay, 311–28. Elsevier. https://doi.org/10.1016/B978-0-444-63934-9.00023-8.
Iturrate, Iñaki, et al. “General Principles of Machine Learning for Brain-Computer Interfacing.” Handbook of Clinical Neurology ; 168, edited by José del R Millan and Nick F. Ramsay, Elsevier, 2020, pp. 311–28, https://doi.org/10.1016/B978-0-444-63934-9.00023-8.


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