Current State of Commercial Wearable Technology in Physical Activity Monitoring 2015-2017
Open accessAbstract
Wearable physical activity trackers are a popular and useful method to collect biometric information at rest and during exercise. The purpose of this systematic review was to summarize recent findings of wearable devices for biometric information related to steps, heart rate, and caloric expenditure for several devices that hold a large portion of the market share. Searches were conducted in both PubMed and SPORTdiscus. Filters included: humans, within the last 5 years, English, full-text, and adult 19+ years. Manuscripts were retained if they included an exercise component of 5-min or greater and had 20 or more participants. A total of 10 articles were retained for this review. Overall, wearable devices tend to underestimate energy expenditure compared to criterion laboratory measures, however at higher intensities of activity energy expenditure is underestimated. All wrist and forearm devices had a tendency to underestimate heart rate, and this error was generally greater at higher exercise intensities and those that included greater arm movement. Heart rate measurement was also typically better at rest and while exercising on a cycle ergometer compared to exercise on a treadmill or elliptical machine. Step count was underestimated at slower walking speeds and in free-living conditions, but improved accuracy at faster speeds. The majority of the studies reviewed in the present manuscript employed different methods to assess validity and reliability of wearable technology, making it difficult to compare devices. Standardized protocols would provide guidance for researchers to evaluate research-grade devices as well as commercial devices used by the lay public.
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A recent review by Bunn et al showed that EE was generally underestimated by physical activity devices and that HR measurements were generally more accurate at rest or on a cycle ergometer as compared with treadmill.
“A recent review by Bunn et al [33] showed that EE was generally underestimated by physical activity devices and that HR measurements were generally more accurate at rest or on a cycle ergometer as compared with treadmill.”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [33]
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Assessing Heart Rate Using Consumer Technology Association Standards
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Self-citationWearable Device Validity in Determining Step Count During Hiking and Trail Running
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Revolutionizing Sport - How Technology is Changing the Sports Industry?
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A Comparison of a Smartphone App with Other GPS Tracking Type Devices Employed in Football
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Validity and Reliability of Wearable Technology Devices during Simulated Pickleball Game Play
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Self-citationUsing Consumer Wearable Devices to Profile Postoperative Complications After Pediatric Appendectomy
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- Authors
- Bunn, J., Navalta, J. W., Fountaine, C. J., & Reece, J.
- Affiliations
- Campbell University (US)
- University of Nevada, Las Vegas (US)
- University of Minnesota, Duluth (US)
- Brigham Young University–Hawaii (US)
- Venue
- International Journal of Exercise Science
- Published
- 2018
- Volume
- 11
- Issue
- 7
- Pages
- 503-515
- ISSN
- 1939-795X (ISSN-L)
- PMC
- PMC5841672
- OpenAlex
- W2786432503
- Cited by
- 194
- References
- 12
- Citations by year
- 2026: 12 · 2025: 15 · 2024: 20 · 2023: 31 · 2022: 25 · 2021: 22 · 2020: 34 · 2019: 20 · 2018: 14 · 2017: 1
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-nd
- Locations
- International journal of exercise science (publishedVersion, cc-by-nd)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- TopSCHOLAR (Western Kentucky University) (submittedVersion)
- Topics
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- wearable devices, wearable activity trackers, step count accuracy, heart rate measurement, energy expenditure, underestimation of energy expenditure, exercise intensity, walking speed, device validation, wrist-worn devices, treadmill exercise, cycle ergometry
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