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CC BY V4.0, Open Access
Journal article
Accurate measurement of simulated slow and altered walking activity: Apple Watch best in class wearable devices
PloS one, Vol.20(10), e0333504
2025
Abstract
Background
Wearable activity devices, widely used to monitor physical activity in non-injured populations, have shown potential in encouraging early ambulation and enhanced recovery in hospitalised patients. This study evaluated the accuracy of wearable devices in tracking step counts under simulated hospital conditions, seeking the optimal body location placement for individuals with altered gait.
Methods
This method comparison study involved healthy adults walking on a treadmill while performing slow and shuffling walking patterns. Twelve wearable devices were placed on the arm, waist, and leg, and their recorded step counts were compared to manual counts from filmed sessions, following Consumer Technology Association guidelines.
Results
The Apple Watch, particularly when worn on the waist, demonstrated the highest reliability and adaptability across walking patterns. Leg placement, which accounted for 10 of the top 20 device-position combinations, suggested that larger movement amplitudes improve step count accuracy, particularly during slow or altered gaits.
Conclusion
This study confirmed the Apple Watch to be the most accurate wearable step count device. The study provides new understanding as to the precision of commercially available devices and their placement, when aiming to improve and, or conduct research about, patient physical activity outcomes.
Details
- Title
- Accurate measurement of simulated slow and altered walking activity: Apple Watch best in class wearable devices
- Authors/Creators
- Grant Rowe - Murdoch UniversityDavid WeightAlethea Rea - Murdoch University, Centre for Terrestrial Ecosystem Science and SustainabilityJenny A Conlon - The University of Notre Dame AustraliaFiona M Wood - The University of Western AustraliaDale W Edgar - Fiona Stanley Hospital
- Publication Details
- PloS one, Vol.20(10), e0333504
- Publisher
- Public Library of Science
- Identifiers
- 991005821344507891
- Copyright
- © 2025 Rowe et al.
- Murdoch Affiliation
- School of Mathematics, Statistics, Chemistry and Physics; Centre for Terrestrial Ecosystem Science and Sustainability
- Resource Type
- Journal article
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