Dataset Information

A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers.

ABSTRACT: 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.

SUBMITTER: Fridolfsson J

PROVIDER: S-EPMC6210008 | biostudies-other | 2018 Oct

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers.

Fridolfsson Jonatan J Börjesson Mats M Arvidsson Daniel D

Sensors (Basel, Switzerland) 20181011 10

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: ...[more]

PMID: 30314272

Similar Datasets

Project description:Background:Measuring physical activity (PA) and sedentary time (ST) by self-report or device as well as assessing related health factors may alter those behaviors. Thus, in intervention trials assessments may bias intervention effects. The aim of our study was to examine whether leisure-time PA, transport-related PA, and overall ST measured via self-report vary after assessments and whether a brief tailored letter intervention has an additional effect. Methods:Among a sample of subjects with no history of myocardial infarction, stroke, or vascular intervention, a number of 175 individuals participated in a study comprising multiple repeated assessments. Of those, 153 were analyzed (mean age 54.5 years, standard deviation?=?6.2; 64% women). At baseline, participants attended a cardiovascular examination (standardized measurement of blood pressure and waist circumference, blood sample taking) and wore an accelerometer for seven days. At baseline and after 1, 6, and 12 months, participants completed the International Physical Activity Questionnaire. A random subsample received a tailored counseling letter intervention at month 1, 3, and 4. Changes in PA and ST from baseline to 12-month follow-up were analyzed using random-effects modelling. Results:From baseline to 1-month assessment, leisure-time PA did not change (Incidence rate ratio?=?1.13, p?=?.432), transport-related PA increased (Incidence rate ratio?=?1.45, p?=?.023), and overall ST tended to decrease (b?=?-?1.96, p?=?.060). Further, overall ST decreased from month 6 to month 12 (b?=?-?0.52, p?=?.037). Time trends of the intervention group did not differ significantly from those of the assessment-only group. Conclusions:Results suggest an effect of measurements on PA and ST. Data of random-effects modelling results revealed an increase of transport-related PA after baseline to 1-month assessment. Decreases in overall ST may result from repeated assessments. A brief tailored letter intervention seemed to have no additional effect. Thus, measurement effects should be considered when planning intervention studies and interpreting intervention effects. Trial registration:ClinicalTrials.gov NCT02990039. Registered 7 December 2016. Retrospectively registered.

Dataset Information

A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers.

Publications

A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets