Lily Koffman

Walking Fingerprinting Using Wrist Accelerometry During Activities of Daily Living in NHANES We propose a method for identifying individuals based on their continuously monitored wrist-worn accelerometry during activities of daily living. The method consists of three steps: (1) using Adaptive...

New preprint about fingerprinting based on walking patterns from @lilykoff.bsky.social and our group: arxiv.org/abs/2506.17160

Minute level step counts and physical activity data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014 v1.0.0 Minute level step counts obtained from five step counting algorithms for raw accelerometry data, and minute level Activity Counts, MIMS, wear predictions, and wear flags for all participants who wore ...

We've published minute-level step counts estimated by 5 open-source algorithms from NHANES 2011-2014 on Physionet! physionet.org/content/minu...
A publicly available dataset ripe for exploration of stepping patterns, association w/ outcomes, & functional data analysis @strictlystat.bsky.social

Comparing Step Counting Algorithms for High-Resolution Wrist Accelerometry Data in NHANES 2011-2014 - PubMed Different step counting algorithms provide correlated step estimates and have similar predictive performance that is better than traditional predictors of mortality. However, they provide widely diffe...

our paper, "Comparing Step Counting Algorithms for High-Resolution Wrist Accelerometry Data in NHANES 2011-2014" is now online! the message: step count estimates varied widely by algorithm, but all were strongly associated with mortality pubmed.ncbi.nlm.nih.gov/39589008/
@strictlystat.bsky.social