Evolution of accelerometer methods for physical activity research
Open accessAbstract
The technology and application of current accelerometer-based devices in physical activity (PA) research allow the capture and storage or transmission of large volumes of raw acceleration signal data. These rich data not only provide opportunities to improve PA characterisation, but also bring logistical and analytic challenges. We discuss how researchers and developers from multiple disciplines are responding to the analytic challenges and how advances in data storage, transmission and big data computing will minimise logistical challenges. These new approaches also bring the need for several paradigm shifts for PA researchers, including a shift from count-based approaches and regression calibrations for PA energy expenditure (PAEE) estimation to activity characterisation and EE estimation based on features extracted from raw acceleration signals. Furthermore, a collaborative approach towards analytic methods is proposed to facilitate PA research, which requires a shift away from multiple independent calibration studies. Finally, we make the case for a distinction between PA represented by accelerometer-based devices and PA assessed by self-report.
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Wrist placement has taken precedence over ankle placement in commercial wearables owing to increased compliance and convenience.
“However, wrist placement has taken precedence over ankle placement in commercial wearables owing to increased compliance and convenience8.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [8]
The wrist placement site and a waterproof case increased wear times and provided a valid assessment of sleep duration and quality.
“The wrist placement site and a waterproof case increased wear times, and had the added benefit of providing a valid assessment of sleep duration and quality [30].”
From Step Counting: A Review of Measurement Considerations and Health-Related Applications (2017) · cites this paper as [30]
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- Authors
- Troiano, R. P., McClain, J. J., Brychta, R. J., & Chen, K. Y.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- Troiano, Richard P
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2014-04-29
- Volume
- 48
- Issue
- 13
- Pages
- 1019-1023
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- PMC
- PMC4141534
- OpenAlex
- W2108707936
- Cited by
- 968
- References
- 37
- Citations by year
- 2026: 52 · 2025: 76 · 2024: 93 · 2023: 90 · 2022: 98 · 2021: 91 · 2020: 99 · 2019: 108 · 2018: 76 · 2017: 70 · 2016: 66 · 2015: 42 · 2014: 7
- FWCI
- 7.25
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- British Journal of Sports Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institutes of Health (Z99 CA999999)
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Keywords
- accelerometer, physical activity measurement, physical activity energy expenditure, signal feature extraction, calibration, big data processing, data storage and transmission, research methodology evolution
- MeSH terms
- Diffusion of Innovation, Humans, Nutrition Surveys, Exercise, Monitoring, Ambulatory, Consensus, Self Report, Accelerometry
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