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PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
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X-WR-CALNAME:Biomedical Mathematics Group
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
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TZID:Asia/Seoul
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TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20200101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20211223T163000
DTEND;TZID=Asia/Seoul:20211223T173000
DTSTAMP:20260503T053357
CREATED:20211222T220000Z
LAST-MODIFIED:20211220T121513Z
UID:5357-1640277000-1640280600@www.ibs.re.kr
SUMMARY:Methods for characterizing circadian physiology from wearables
DESCRIPTION:Abstract \nNon-invasive data collection in real-world settings with wearables provides a new opportunity for characterizing daily physiology. However\, accurate and efficient characterization remains an open problem because the complex autoregressive noise of the data makes it challenging to use a simple and efficient method for inference of clock proxies\, least squares method. In this talk\, we will introduce a simple approximation that alters the noise structure and thus enables one to use the least squares method. We will show its usefulness for real-time personalized fever detection in cancer patients.
URL:https://www.ibs.re.kr/bimag/event/2021-12-23-2/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
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