Scientific article

English

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling

ContributorsPhillips, Nicholas

; Collet, Tinh-Hai

Published inCell reports. Methods, vol. 3, no. 8, 100545

Publication date2023-08

First online date2023-10-12

Keywords

Bayesian inference
Kalman filter
Biosensors
Circadian rhythms
Continuous glucose monitor (CGM)
Wearables

Affiliation entities

Faculté de médecine / Section de médecine clinique / Département de médecine
Faculté de médecine / Section de médecine fondamentale / Département de physiologie cellulaire et métabolisme

Research groups

Nutrition et chronobiologie (1038)

Citation (ISO format)

PHILLIPS, Nicholas, COLLET, Tinh-Hai, NAEF, Felix. Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling. In: Cell reports. Methods, 2023, vol. 3, n° 8, p. 100545. doi: 10.1016/j.crmeth.2023.100545

Article (Published version)

Supplemental data

Supplemental data

Identifiers

PID : unige:172356
DOI : 10.1016/j.crmeth.2023.100545
PMID : 37671030
PMCID : PMC10475794

Additional URL for this publicationhttps://linkinghub.elsevier.com/retrieve/pii/S2667237523001820

Datasets

Journal ISSN2667-2375

297views

142downloads

Creation12/10/2023 10:01:11

First validation19/10/2023 12:49:17

Update13/10/2025 14:15:18

Status update31/01/2025 16:16:36

Last indexation06/11/2025 19:53:06