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dc.contributor.authorElvebakk, Ole
dc.contributor.authorTronstad, Christian
dc.contributor.authorBirkeland, Kåre I.
dc.contributor.authorJenssen, Trond Geir
dc.contributor.authorBjørgaas, Marit Ragnhild Rokne
dc.contributor.authorGulseth, Hanne Løvdal
dc.contributor.authorKalvøy, Håvard
dc.contributor.authorHøgetveit, Jan Olav
dc.contributor.authorMartinsen, Ørjan Grøttem
dc.date.accessioned2020-01-27T11:52:50Z
dc.date.available2020-01-27T11:52:50Z
dc.date.issued2019-09-02
dc.description.abstract<i>Objective</i>: Severe hypoglycemia is the most serious acute complication for people with type 1 diabetes (T1D). Approximately 25% of people with T1D have impaired ability to recognize impending hypoglycemia, and nocturnal episodes are feared.<p> <p><i>Approach</i>: We have investigated the use of non-invasive sensors for detection of hypoglycemia based on a mathematical model which combines several sensor measurements to identify physiological responses to hypoglycemia. Data from randomized single-blinded euglycemic and hypoglycemic glucose clamps in 20 participants with T1D and impaired awareness of hypoglycemia was used in the analyses.<p> <p><i>Main results</i>: Using a sensor combination of sudomotor activity at three skin sites, ECG-derived heart rate and heart rate corrected QT interval, near-infrared and bioimpedance spectroscopy; physiological responses associated with hypoglycemia could be identified with an F1 score accuracy up to 88%.<p> <p><i>Significance</i>: We present a novel model for identification of non-invasively measurable physiological responses related to hypoglycemia, showing potential for detection of moderate hypoglycemia using a wearable sensor system.en_US
dc.descriptionThis is an author-created, un-copyedited version of an article accepted for publication/published in Physiological Measurement. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at <a href=https://doi.org/10.1088/1361-6579/ab3676> https://doi.org/10.1088/1361-6579/ab3676</a>.<p> <p>Accepted manuscript version, licensed <a href=http://creativecommons.org/licenses/by-nc-nd/4.0/> CC BY-NC-ND 4.0. </a>en_US
dc.identifier.citationElvebakk O, Tronstad C, Birkeland KI, Jenssen TG, Bjørgaas MRR, Gulseth HL, Kalvøy H, Høgetveit JO, Martinsen ØG. A multiparameter model for non-invasive detection of hypoglycemia. Physiological Measurement. 2019;40(8):1-14en_US
dc.identifier.cristinIDFRIDAID 1739238
dc.identifier.doi10.1088/1361-6579/ab3676
dc.identifier.issn0967-3334
dc.identifier.issn1361-6579
dc.identifier.urihttps://hdl.handle.net/10037/17226
dc.language.isoengen_US
dc.publisherIOP Publishingen_US
dc.relation.journalPhysiological Measurement
dc.rights.accessRightsopenAccessen_US
dc.rights.holder© 2019 Institute of Physics and Engineering in Medicineen_US
dc.titleA multiparameter model for non-invasive detection of hypoglycemiaen_US
dc.type.versionacceptedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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