Real-time estimations of blood glucose concentrations from sweat measurements using the local density random walk model.
| Publicado en: | Medical & Biological Engineering & Computing Vol. 63; no. 11; pp. 3237 - 3251 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189590710&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189590710 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Nov2025 vid: 63 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 189590710 185724025 10.1007/s11517-025-03393-z 189590710 ppf: 3237 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Real-time estimations of blood glucose concentrations from sweat measurements using the local density random walk model. aug: au: Yin, Xiaoyu Peri, Elisabetta Pelssers, Eduard Toonder, Jaap den Mischi, Massimo affil: https://ror.org/02c2kyt77 Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Noord-Brabant, Netherlands sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
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