BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20250101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20260424T100000
DTEND;TZID=Asia/Seoul:20260424T120000
DTSTAMP:20260422T110642
CREATED:20260406T092550Z
LAST-MODIFIED:20260406T103749Z
UID:12365-1777024800-1777032000@www.ibs.re.kr
SUMMARY:Foundation Models for Wearable Movement Data in Mental Health Research - Aqsa Awan
DESCRIPTION:In this tallk\, we discuss the paper “Foundation Models for Wearable Movement Data in Mental Health Research” by Franklin Y. Ruan et al.\, arXiv\, 2025. \nAbstract \nPretrained foundation models and transformer architectures have driven the success of large language models (LLMs) and other modern AI breakthroughs. However\, similar advancements in health data modeling remain limited due to the need for innovative adaptations. Wearable movement data offers a valuable avenue for exploration\, as it’s a core feature in nearly all commercial smartwatches\, well established in clinical and mental health research\, and the sequential nature of the data shares similarities to language. We introduce the Pretrained Actigraphy Transformer (PAT)\, the first open source foundation model designed for time-series wearable movement data. Leveraging transformer-based architectures and novel techniques\, such as patch embeddings\, and pretraining on data from 29\,307 participants in a national U.S. sample\, PAT achieves state-of-the-art performance in several mental health prediction tasks. PAT is also lightweight and easily interpretable\, making it a robust tool for mental health research.
URL:https://www.ibs.re.kr/bimag/event/foundation-models-for-wearable-movement-data-in-mental-health-research-aqsa-awan/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR