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Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand
Open accessAbstract
BACKGROUND: Using raw acceleration data to assess the intensity of physical activity enables direct comparisons between studies using different accelerometer brands. Mean amplitude deviation (MAD in mg) calculated from resultant tri-axial raw acceleration signal was recently shown to perform best in classifying the intensity of physical activity in adults irrespective of the accelerometer brand. This study compared MAD values and cut-points between two different accelerometers in adolescents. METHODS: Twenty voluntary participants (10 girls and 10 boys) of average age of 14 wore two accelerometers (Actigraph GTX3, Pensacola FL, USA and Hookie AM13, Espoo, Finland) and heart rate monitors (M61, Polar Electro Oy, Kempele, Finland) while completing ten 2-min patterns of typical activities ranging from sedentary behaviour to light, moderate and vigorous-intensity locomotion. Bland-Altman method examined the agreement of MAD values between the accelerometers. Correlation coefficient between individual heart rates and MAD values indicated the validity of pattern-based intensity classification. Generalized ordinal logistic regression determined the intensity-specific MAD cut-points for both accelerometers. RESULTS: MAD values varied from 3 mg (lying supine) to 1609 mg (running). Hookie gave higher values than Actigraph in accelerations exceeding 700 mg. The correlation coefficient between MAD values and heart rates was 0.96 for Hookie and 0.97 for Actigraph. Respectively, the MAD cut-points were 29 and 27 (light), 338 and 330 (moderate), and 604 and 558 (vigorous). CONCLUSIONS: MAD values and cut-points of Hookie and Actigraph showed excellent agreement. Analysing raw accelerometer data with MAD values may enable the comparison of accelerometer results between different studies also in adolescents.
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“A recent study showed that the standard deviation of the 3D acceleration norm resembles intensity of physical activity of 2 widely used commercial acceleration-based activity trackers with reasonable consensus [29].”
From Mobile Sensing and Support for People With Depression: A Pilot Trial in the Wild (2016) · cites this paper as [29]
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Metadata
- Authors
- Aittasalo, M., Vähä-Ypyä, H., Vasankari, T., Husu, P., Jussila, A.-M., & Sievänen, H.
- Affiliations
- Urho Kaleva Kekkonen Institute (FI)
- Corresponding author
- Aittasalo, Minna
- Venue
- BMC Sports Science, Medicine and Rehabilitation
- Published
- 2015-08-07
- Volume
- 7
- Issue
- 1
- Pages
- 18-18
- ISSN
- 2052-1847 (ISSN-L)
- PMC
- PMC4527117
- OpenAlex
- W1689929051
- Cited by
- 126
- References
- 21
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 13 · 2023: 14 · 2022: 20 · 2021: 21 · 2020: 8 · 2019: 11 · 2018: 11 · 2017: 8 · 2016: 7 · 2015: 1
- FWCI
- 6.62
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Sports Science Medicine and Rehabilitation (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Tekes
- Pirkanmaan Sairaanhoitopiiri
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Keywords
- physical activity intensity classification, adolescents, ActiGraph, heart rate monitors, cut points, sedentary behavior, high-intensity exercise
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