A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers

ActiGraph is the most common accelerometer in physical activity research, but it has measurement errors due to restrictive frequency filtering. This study investigated biomechanically how different frequency filtering of accelerometer data affects assessment of activity intensity and age-group diffe...

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Main Authors: Jonatan Fridolfsson, Mats Börjesson, Daniel Arvidsson
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/18/10/3399
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spelling doaj-ae5e5390b8fd4d039553680347f2bb242020-11-24T21:28:03ZengMDPI AGSensors1424-82202018-10-011810339910.3390/s18103399s18103399A Biomechanical Re-Examination of Physical Activity Measurement with AccelerometersJonatan Fridolfsson0Mats Börjesson1Daniel Arvidsson2Center for Health and Performance, Department of Food and Nutrition, and Sport Science, University of Gothenburg, 40530 Gothenburg, SwedenCenter for Health and Performance, Department of Food and Nutrition, and Sport Science, University of Gothenburg, 40530 Gothenburg, SwedenCenter for Health and Performance, Department of Food and Nutrition, and Sport Science, University of Gothenburg, 40530 Gothenburg, SwedenActiGraph is the most common accelerometer in physical activity research, but it has measurement errors due to restrictive frequency filtering. This study investigated biomechanically how different frequency filtering of accelerometer data affects assessment of activity intensity and age-group differences when measuring physical activity. Data from accelerometer at the hip and motion capture system was recorded during treadmill walking and running from 30 subjects in three different age groups: 10, 15, and >20 years old. Acceleration data was processed to ActiGraph counts with original band-pass filter at 1.66 Hz, to counts with wider filter at either 4 or 10 Hz, and to unfiltered acceleration according to “Euclidian norm minus one” (ENMO). Internal and external power, step frequency, and vertical displacement of center of mass (VD) were estimated from the motion capture data. Widening the frequency filter improved the relationship between higher locomotion speed and counts. It also removed age-group differences and decreased within-group variation. While ActiGraph counts were almost exclusively explained by VD, the counts from the 10 Hz filter were explained by VD and step frequency to an equal degree. In conclusion, a wider frequency filter improves assessment of physical activity intensity by more accurately capturing individual gait patterns.http://www.mdpi.com/1424-8220/18/10/3399ActiGraphaxivityfilteringchildrenadults
collection DOAJ
language English
format Article
sources DOAJ
author Jonatan Fridolfsson
Mats Börjesson
Daniel Arvidsson
spellingShingle Jonatan Fridolfsson
Mats Börjesson
Daniel Arvidsson
A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers
Sensors
ActiGraph
axivity
filtering
children
adults
author_facet Jonatan Fridolfsson
Mats Börjesson
Daniel Arvidsson
author_sort Jonatan Fridolfsson
title A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers
title_short A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers
title_full A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers
title_fullStr A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers
title_full_unstemmed A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers
title_sort biomechanical re-examination of physical activity measurement with accelerometers
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2018-10-01
description ActiGraph is the most common accelerometer in physical activity research, but it has measurement errors due to restrictive frequency filtering. This study investigated biomechanically how different frequency filtering of accelerometer data affects assessment of activity intensity and age-group differences when measuring physical activity. Data from accelerometer at the hip and motion capture system was recorded during treadmill walking and running from 30 subjects in three different age groups: 10, 15, and >20 years old. Acceleration data was processed to ActiGraph counts with original band-pass filter at 1.66 Hz, to counts with wider filter at either 4 or 10 Hz, and to unfiltered acceleration according to “Euclidian norm minus one” (ENMO). Internal and external power, step frequency, and vertical displacement of center of mass (VD) were estimated from the motion capture data. Widening the frequency filter improved the relationship between higher locomotion speed and counts. It also removed age-group differences and decreased within-group variation. While ActiGraph counts were almost exclusively explained by VD, the counts from the 10 Hz filter were explained by VD and step frequency to an equal degree. In conclusion, a wider frequency filter improves assessment of physical activity intensity by more accurately capturing individual gait patterns.
topic ActiGraph
axivity
filtering
children
adults
url http://www.mdpi.com/1424-8220/18/10/3399
work_keys_str_mv AT jonatanfridolfsson abiomechanicalreexaminationofphysicalactivitymeasurementwithaccelerometers
AT matsborjesson abiomechanicalreexaminationofphysicalactivitymeasurementwithaccelerometers
AT danielarvidsson abiomechanicalreexaminationofphysicalactivitymeasurementwithaccelerometers
AT jonatanfridolfsson biomechanicalreexaminationofphysicalactivitymeasurementwithaccelerometers
AT matsborjesson biomechanicalreexaminationofphysicalactivitymeasurementwithaccelerometers
AT danielarvidsson biomechanicalreexaminationofphysicalactivitymeasurementwithaccelerometers
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