Personalized physical activity recommendations for people with axial spondyloarthritis using wearable activity tracker data: an exploratory study.

ABSTRACT:

Objective

Benefits of physical activity (PA) on sleep in people with axial SpondyloArthritis (axSpA) are largely unknown. Our aim is to explore the relationships between PA and sleep on both a group level and an individual level using Wearable Activity Trackers (WATs) and machine learning.

Methods

A sample of 64 axSpA participants received a WAT to monitor their PA and sleep. Participants with more than 30 days data of PA and sleep duration were included in the analyses. Spearman's correlation and the machine learning technique Subgroup Discovery were used to determine relationships between PA during the three prior days and light and deep sleep duration.

Results

Number of daily steps (n = 64) was (median (first quartile (Q1) - third quartile (Q3) )) 4026 (1915 - 6549

SUBMITTER: de Leeuw AW 

PROVIDER: S-EPMC11865101 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature