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Sedentary Behavior Estimation with Hip-worn Accelerometer Data: Segmentation, Classification and Thresholding. (arXiv:2207.01809v1 [cs.LG])
cs.LG updates on arXiv.org arxiv.org
Cohort studies are increasingly using accelerometers for physical activity
and sedentary behavior estimation. These devices tend to be less error-prone
than self-report, can capture activity throughout the day, and are economical.
However, previous methods for estimating sedentary behavior based on hip-worn
data are often invalid or suboptimal under free-living situations and
subject-to-subject variation. In this paper, we propose a local Markov
switching model that takes this situation into account, and introduce a general
procedure for posture classification and sedentary behavior …
arxiv behavior classification data lg segmentation thresholding