Exploring the ActiLife® filtration algorithm: converting raw acceleration data to counts

D. Peach
Jacqueline Van Hoomissen, University of Portland
Hannah Callender, University of Portland

Physiological Measurement, 2014, Volume 35, Issue 12, 2359-2367.

© 2014 Institute of Physics and Engineering in Medicine.

Linked version is final published version.

Abstract

Though portable accelerometers are ubiquitous in physiology and public health studies, their accuracy as objective measures of physical activity is still being examined. This paper enumerates and analyzes the various biases of the widely used ActiLife® software in reporting activity counts from ActiGraph® accelerometers. In particular, we focus on the two-stage proprietary filtration algorithm used to convert raw acceleration data, for a sampling rate of 30 Hz, to compressed 1 Hz signals; we develop simple novel methods to analyze the action of the software filter on the raw data in the frequency domain.