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...

Descripción completa

Detalles Bibliográficos
Autores principales: Aittasalo, Minna, Vähä-Ypyä, Henri, Vasankari, Tommi, Husu, Pauliina, Jussila, Anne-Mari, Sievänen, Harri
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