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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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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