A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring
Open accessAbstract
Characteristics of physical activity are indicative of one’s mobility level, latent chronic diseases and aging process. Accelerometers have been widely accepted as useful and practical sensors for wearable devices to measure and assess physical activity. This paper reviews the development of wearable accelerometry-based motion detectors. The principle of accelerometry measurement, sensor properties and sensor placements are first introduced. Various research using accelerometry-based wearable motion detectors for physical activity monitoring and assessment, including posture and movement classification, estimation of energy expenditure, fall detection and balance control evaluation, are also reviewed. Finally this paper reviews and compares existing commercial products to provide a comprehensive outlook of current development status and possible emerging technologies.
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- Authors
- Yang, C.-C., & Hsu, Y.-L.
- Affiliations
- Yuan Ze University (TW)
- Corresponding author
- Hsu, Yeh-Liang
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2010-08-20
- Volume
- 10
- Issue
- 8
- Pages
- 7772-7788
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC3231187
- OpenAlex
- W2083539525
- Cited by
- 1,058
- References
- 91
- Citations by year
- 2026: 43 · 2025: 51 · 2024: 51 · 2023: 55 · 2022: 59 · 2021: 71 · 2020: 117 · 2019: 83 · 2018: 113 · 2017: 88 · 2016: 80 · 2015: 67 · 2014: 69 · 2013: 60 · 2012: 32
- FWCI
- 4.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- accelerometer, wearable devices, physical activity monitoring, motion detection, posture recognition, movement classification, energy expenditure estimation, fall detection, balance control, sensor placement
- MeSH terms
- Acceleration, Energy Metabolism, Equipment Design, Humans, Motor Activity, Reproducibility of Results, Exercise, Monitoring, Ambulatory, Wireless Technology
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