Cargando…
Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand
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...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4527117/ https://www.ncbi.nlm.nih.gov/pubmed/26251724 http://dx.doi.org/10.1186/s13102-015-0010-0 |
_version_ | 1782384527924002816 |
---|---|
author | Aittasalo, Minna Vähä-Ypyä, Henri Vasankari, Tommi Husu, Pauliina Jussila, Anne-Mari Sievänen, Harri |
author_facet | Aittasalo, Minna Vähä-Ypyä, Henri Vasankari, Tommi Husu, Pauliina Jussila, Anne-Mari Sievänen, Harri |
author_sort | Aittasalo, Minna |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4527117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45271172015-08-07 Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand Aittasalo, Minna Vähä-Ypyä, Henri Vasankari, Tommi Husu, Pauliina Jussila, Anne-Mari Sievänen, Harri BMC Sports Sci Med Rehabil Research Article 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. BioMed Central 2015-08-07 /pmc/articles/PMC4527117/ /pubmed/26251724 http://dx.doi.org/10.1186/s13102-015-0010-0 Text en © Aittasalo et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Aittasalo, Minna Vähä-Ypyä, Henri Vasankari, Tommi Husu, Pauliina Jussila, Anne-Mari Sievänen, Harri Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand |
title | Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand |
title_full | Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand |
title_fullStr | Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand |
title_full_unstemmed | Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand |
title_short | Mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand |
title_sort | mean amplitude deviation calculated from raw acceleration data: a novel method for classifying the intensity of adolescents’ physical activity irrespective of accelerometer brand |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4527117/ https://www.ncbi.nlm.nih.gov/pubmed/26251724 http://dx.doi.org/10.1186/s13102-015-0010-0 |
work_keys_str_mv | AT aittasalominna meanamplitudedeviationcalculatedfromrawaccelerationdataanovelmethodforclassifyingtheintensityofadolescentsphysicalactivityirrespectiveofaccelerometerbrand AT vahaypyahenri meanamplitudedeviationcalculatedfromrawaccelerationdataanovelmethodforclassifyingtheintensityofadolescentsphysicalactivityirrespectiveofaccelerometerbrand AT vasankaritommi meanamplitudedeviationcalculatedfromrawaccelerationdataanovelmethodforclassifyingtheintensityofadolescentsphysicalactivityirrespectiveofaccelerometerbrand AT husupauliina meanamplitudedeviationcalculatedfromrawaccelerationdataanovelmethodforclassifyingtheintensityofadolescentsphysicalactivityirrespectiveofaccelerometerbrand AT jussilaannemari meanamplitudedeviationcalculatedfromrawaccelerationdataanovelmethodforclassifyingtheintensityofadolescentsphysicalactivityirrespectiveofaccelerometerbrand AT sievanenharri meanamplitudedeviationcalculatedfromrawaccelerationdataanovelmethodforclassifyingtheintensityofadolescentsphysicalactivityirrespectiveofaccelerometerbrand |