Book chapter
Technical Function Evaluation of Two Smart Wearables and Data Analysis Methods for Step Counts
Augmented Cognition, pp.71-88
Lecture Notes in Computer Science, Springer Nature Switzerland
01/01/2023
DOI: 10.1007/978-3-031-35017-7_6
Abstract
Smart wearable devices that capture physical activity data are increasingly used for health research and show potential for augmented cognition. These devices must be tested to understand their function before use in research and everyday life. However, there are few standards for the evaluation of step count comparisons between devices. We completed a technical function evaluation of two consumer-grade devices – Fitbit Versa 3 and generation 2 Oura Ring – against research-grade gold standard ActiGraph devices – wGT3X-BT and GT9X-Link. We compared data analysis methods to evaluate smart wearable physical activity data to inform development of standards and guidance for data analysis. Based on this effort, we suggest the use of Median Absolute Percent Difference along with Spearman’s Rho as a correlation measure and Bland-Altman plots to visualize the agreement. This combination of measures provides a multi-perspective view of step counts and can assist researchers in determining limitations and best uses for smart wearable devices.
Details
- Title: Subtitle
- Technical Function Evaluation of Two Smart Wearables and Data Analysis Methods for Step Counts
- Creators
- Katrina K. Boles - University of MissouriMalaika R. Gallimore - University of MissouriChelsea Howland - University of MissouriChuka Emezue - University of MissouriBlaine Reeder - University of Missouri
- Contributors
- Dylan D. Schmorrow (Editor)Cali M. Fidopiastis (Editor)
- Resource Type
- Book chapter
- Publication Details
- Augmented Cognition, pp.71-88
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-031-35017-7_6
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Publisher
- Springer Nature Switzerland; Cham
- Language
- English
- Date published
- 01/01/2023
- Academic Unit
- Nursing; Center for Social Science Innovation
- Record Identifier
- 9984696655802771
Metrics
31 Record Views