Analytical Validation of Wrist-Worn Accelerometer-Based Step-Count Methods during Structured and Free-Living Activities.

ABSTRACT:

Introduction

Wrist-worn accelerometers can capture stepping behavior passively, continuously, and remotely. Methods utilizing peak detection, threshold crossing, and frequency analysis have been used to detect steps from wrist-worn accelerometer data, but it remains unclear how different approaches perform across a range of walking speeds and free-living activities. In this study, we evaluated the performance of four open-source methods for deriving step counts from wrist-worn accelerometry data, when applied to data from a range of structured locomotion and free-living activities. In addition, we assessed how modifying the parameters of these methods would affect their performance.

Methods

Twenty-one participants (ages 20-33) wore an ActiGraph CentrePoint Insight Watch (Act

SUBMITTER: Marcotte RT 

PROVIDER: S-EPMC11771982 | biostudies-literature | 2025 Jan-Dec

REPOSITORIES: biostudies-literature