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Phase Estimation of Nonlinear State-space Model of the Circadian Pacemaker Using Level Set Kalman Filter and Raw Wearable Data

June 10 @ 1:00 pm - 2:00 pm KST

B378 Seminar room, IBS, 55 Expo-ro Yuseong-gu
Daejeon, 34126 Korea, Republic of

Speaker

Minki Lee
University of Michigan

Abstract:

Circadian rhythm is a robust internal 24 hours timekeeping mechanism maintained by the master circadian pacemaker Suprachiasmatic Nuclei (SCN). Numerous mathematical models have been proposed to capture SCN’s timekeeping mechanism and predict the circadian phase. There has been an increased demand for applying these models to the various unexplored data sets. One potential application is on data from commercially available wearable devices, which provide the noninvasive measurements of physiological proxies, such as activity and heart rate. Using these physiological proxies, we can estimate the circadian phase of the central and peripheral circadian pacemakers. Here, we propose a new framework for estimating the circadian phase using wearable data and the Level Set Kalman Filter on the nonlinear state-space model of the human circadian pacemaker. Analysis of over 200,000 days of wearable data from over 3,000 subjects using our framework successfully identified misalignment in central and peripheral pacemakers with a significantly smaller uncertainty than previous methods.

Details

Date:
June 10
Time:
1:00 pm - 2:00 pm KST
Event Category:

Venue

B378 Seminar room, IBS
55 Expo-ro Yuseong-gu
Daejeon, 34126 Korea, Republic of

Organizer

Jae Kyoung Kim
Email:
jaekkim@kaist.ac.kr
IBS 의생명수학그룹 Biomedical Mathematics Group
기초과학연구원 수리및계산과학연구단 의생명수학그룹
대전 유성구 엑스포로 55 (우) 34126
IBS Biomedical Mathematics Group (BIMAG)
Institute for Basic Science (IBS)
55 Expo-ro Yuseong-gu Daejeon 34126 South Korea
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