Abstract Number:
3554
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Margaret Banker (1), Peter Song (2)
Institutions:
(1) Northwestern Feinberg School of Medicine, N/A, (2) University of Michigan, N/A
Co-Author:
First Author:
Presenting Author:
Abstract Text:
Accelerometry data collected by high-capacity sensors present a primary data type in smart mobile health. I holistically summarize an individual subject's activity profile using Occupation Time curves (OTCs). Being a functional predictor, OTCs describe the percentage of time spent at or above a continuum of activity count levels. The resulting functional curve is informative to capture time-course individual variability of physical activities both on the underlying functional variables of interest, as well as the specific health outcomes. I leverage the OTC curves to develop a longitudinal functional framework with repeated wearable data to understand the influence of serially measured functional accelerometer data on longitudinal health outcomes. I develop a new one-step method that can simultaneously conduct fusion via change-point detection and parameter estimation through a new L0 constraint formulation, invoking Quadratic Inference Functions (QIF), with an aim to detect physical activity intensity windows and assess their population-average effects on children health outcomes.
Keywords:
L0 regularization|changepoint detection|accelerometer|functional data analysis| |
Sponsors:
Biometrics Section
Tracks:
Longitudinal/Correlated Data
Can this be considered for alternate subtype?
No
Are you interested in volunteering to serve as a session chair?
Yes
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.
I understand