Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Model‐Free Inference Of Information Flow Among Physiological Signals In Type 1 Diabetes Subjects Using Multivariate Transfer Entropy

dc.contributor.authorHettiarachchi, Chirath
dc.contributor.authorDaskalaki, Eleni
dc.contributor.authorMalagutti, Nicolo
dc.contributor.authorNolan, Christopher
dc.contributor.authorSuominen, Hanna
dc.contributor.editorGarg, Satish K.
dc.coverage.spatialvirtual
dc.date.accessioned2024-07-16T04:57:52Z
dc.date.available2024-07-16T04:57:52Z
dc.date.created2-5 June
dc.date.issued2021
dc.date.updated2024-01-07T07:16:11Z
dc.description.abstractThe complexity and inter-subject variability of the glucoregulatory system calls for the integration of additional physiological signals in the daily management of glycaemia in Type 1 Diabetes (T1D). The aim of this study was to explore the Information Flow (IF) among different physiological signals in T1D subjects
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1520-9156
dc.identifier.urihttps://hdl.handle.net/1885/733713949
dc.language.isoen_AUen_AU
dc.publisherMary Ann Liebert Inc.
dc.relation.ispartofseries14th International Conference on Advanced Technologies and Treatments for Diabetes
dc.rights© Mary Ann Liebert, Inc.
dc.rights.licenseCreative Commons Attribution 4.0 International CC BY License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceDiabetes Technology and Therapeutics
dc.titleModel‐Free Inference Of Information Flow Among Physiological Signals In Type 1 Diabetes Subjects Using Multivariate Transfer Entropy
dc.typeConference paper
dcterms.accessRightsOpen Access
local.bibliographicCitation.issueS2
local.bibliographicCitation.lastpageA-99
local.bibliographicCitation.startpageA-99
local.contributor.affiliationHettiarachchi, Chirath, RSCH Research & Innovation Portfolio, ANU
local.contributor.affiliationDaskalaki, Eleni, College of Engineering, Computing and Cybernetics, ANU
local.contributor.affiliationMalagutti, Nicolo, College of Engineering, Computing and Cybernetics, ANU
local.contributor.affiliationNolan, Christopher, College of Health and Medicine, ANU
local.contributor.affiliationSuominen, Hanna, College of Engineering, Computing and Cybernetics, ANU
local.contributor.authoruidHettiarachchi, Chirath, u7041472
local.contributor.authoruidDaskalaki, Eleni, u1085378
local.contributor.authoruidMalagutti, Nicolo, u4738997
local.contributor.authoruidNolan, Christopher, u1820721
local.contributor.authoruidSuominen, Hanna, u4872279
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor460103 - Applications in life sciences
local.identifier.absfor320602 - Medical biotechnology diagnostics (incl. biosensors)
local.identifier.ariespublicationu6662439xPUB50
local.identifier.doi10.1089/dia.2021.2525.abstracts
local.publisher.urlhttps://www.liebertpub.com/doi/10.1089/dia.2021.2525.abstracts
local.type.statusPublished Version
publicationvolume.volumeNumber23

Downloads

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Model‐Free Inference Of Information Flow.pdf
Size:
45.78 KB
Format:
Adobe Portable Document Format