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Defining Activity Thresholds Triggering a "Stand Hour" for Apple Watch Users: Cross-Sectional Study.

Katy Lyons¹, Alison Hau Hei Man¹, David Booth²

¹Division of Cellular and Systems Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom.

JMIR Formative Research

|June 10, 2024

Summary

The Apple Watch stand hour (SH) metric is influenced by active energy and step count. Meeting thresholds for these can increase the likelihood of recording a stand hour, promoting light physical activity.

Keywords:

Apple Watch algorithm algorithms cardiovascular disease data collection exercise light physical activity machine learning movement physical activity predict prediction predictive predictor predictors sedentary sedentary behavior smartwatch stand stand hour standing type 2 diabetes watch wearable wearables

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Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

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Published on: February 21, 2025

Area of Science:

Wearable technology and health metrics
Human movement analysis
Public health and noncommunicable disease prevention

Background:

Sedentary behavior (SB) is a major risk factor for noncommunicable diseases.
World Health Organization guidelines recommend replacing SB with light physical activity.
The Apple Watch stand hour (SH) metric's activity determinants are unclear.

Purpose of the Study:

Analyze the algorithm determining Apple Watch stand hour (SH) recordings.
Investigate activity measurements influencing SH recording.
Estimate the predictive values of SH recording factors.

Main Methods:

Cross-sectional study utilizing anonymized Apple Watch data from 20 healthy individuals.
Data extraction via a third-party app from the Apple Health app.
Statistical modeling to identify and analyze SH predictors.

Main Results:

Active energy (AE) and step count (SC) significantly influence SH recording.
Mean and median AE and SC differ between recorded and unrecorded SH.
Thresholds of 97.5 steps or 100 kJ AE increased SH recording likelihood.

Conclusions:

AE and SC are pivotal factors in the Apple Watch SH algorithm.
SH recording is influenced by multiple factors.
The SH metric represents light physical activity and can encourage SB reduction.