scholarly journals A Biomechanical Re-Examination of Physical Activity Measurement with Accelerometers

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3399 ◽  
Author(s):  
Jonatan Fridolfsson ◽  
Mats Börjesson ◽  
Daniel Arvidsson
Keyword(s):  
Physical Activity ◽  
Motion Capture ◽  
Group Differences ◽  
Band Pass Filter ◽  
Accelerometer Data ◽  
Age Group ◽  
Frequency Filtering ◽  
Frequency Filter ◽  
Step Frequency ◽  
Activity Intensity

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.

scholarly journals Effects of Frequency Filtering on Intensity and Noise in Accelerometer-Based Physical Activity Measurements

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2186 ◽  
Author(s):  
Jonatan Fridolfsson ◽  
Mats Börjesson ◽  
Christoph Buck ◽  
Örjan Ekblom ◽  
Elin Ekblom-Bak ◽  
...  
Keyword(s):  
Physical Activity ◽  
Band Pass Filter ◽  
Accelerometer Data ◽  
Frequency Filtering ◽  
Free Living ◽  
Pass Filter ◽  
Cut Points ◽  
Activity Measurements ◽  
Low Pass ◽  
Band Pass

In objective physical activity (PA) measurements, applying wider frequency filters than the most commonly used ActiGraph (AG) filter may be beneficial when processing accelerometry data. However, the vulnerability of wider filters to noise has not been investigated previously. This study explored the effect of wider frequency filters on measurements of PA, sedentary behavior (SED), and capturing of noise. Apart from the standard AG band-pass filter (0.29–1.63 Hz), modified filters with low-pass component cutoffs at 4 Hz, 10 Hz, or removed were analyzed. Calibrations against energy expenditure were performed with lab data from children and adults to generate filter-specific intensity cut-points. Free-living accelerometer data from children and adults were processed using the different filters and intensity cut-points. There was a contribution of acceleration related to PA at frequencies up to 10 Hz. The contribution was more pronounced at moderate and vigorous PA levels, although additional acceleration also occurred at SED. The classification discrepancy between AG and the wider filters was small at SED (1–2%) but very large at the highest intensities (>90%). The present study suggests an optimal low-pass frequency filter with a cutoff at 10 Hz to include all acceleration relevant to PA with minimal effect of noise.

scholarly journals Reexamination of Accelerometer Calibration with Energy Expenditure as Criterion: VO2net Instead of MET for Age-Equivalent Physical Activity Intensity

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3377 ◽  
Author(s):  
Daniel Arvidsson ◽  
Jonatan Fridolfsson ◽  
Christoph Buck ◽  
Örjan Ekblom ◽  
Elin Ekblom-Bak ◽  
...  
Keyword(s):  
Physical Activity ◽  
Age Groups ◽  
Accelerometer Data ◽  
Physical Activity Intensity ◽  
Free Living ◽  
Activity Intensity ◽  
Age Related ◽  
Younger Age ◽  
Metabolic Equivalent Of Task ◽  
Adolescents And Adults

Accelerometer calibration for physical activity (PA) intensity is commonly performed using Metabolic Equivalent of Task (MET) as criterion. However, MET is not an age-equivalent measure of PA intensity, which limits the use of MET-calibrated accelerometers for age-related PA investigations. We investigated calibration using VO2net (VO2gross − VO2stand; mL⋅min−1⋅kg−1) as criterion compared to MET (VO2gross/VO2rest) and the effect on assessment of free-living PA in children, adolescents and adults. Oxygen consumption and hip/thigh accelerometer data were collected during rest, stand and treadmill walk and run. Equivalent speed (Speedeq) was used as indicator of the absolute speed (Speedabs) performed with the same effort in individuals of different body size/age. The results showed that VO2net was higher in younger age-groups for Speedabs, but was similar in the three age-groups for Speedeq. MET was lower in younger age-groups for both Speedabs and Speedeq. The same VO2net-values respective MET-values were applied to all age-groups to develop accelerometer PA intensity cut-points. Free-living moderate-and-vigorous PA was 216, 115, 74 and 71 min/d in children, adolescents, younger and older adults with VO2net-calibration, but 140, 83, 74 and 41 min/d with MET-calibration, respectively. In conclusion, VO2net calibration of accelerometers may provide age-equivalent measures of PA intensity/effort for more accurate age-related investigations of PA in epidemiological research.

scholarly journals Age and Physical Activity among Canadian Women and Men: Findings from Longitudinal National Survey Data

2000 ◽  
Vol 8 (1) ◽  
pp. 1-19 ◽  
Author(s):  
James Curtis ◽  
Philip White ◽  
Barry McPherson
Keyword(s):  
Physical Activity ◽  
Inverse Relationship ◽  
Leisure Time ◽  
Age Groups ◽  
Group Differences ◽  
Activity Levels ◽  
Age Group ◽  
Activity Involvement ◽  
Age Cohorts ◽  
Age Cohort

This study reports on age-group differences in leisure-time sport and physical activity involvement among a large sample of Canadians interviewed at 2 points during the 1980s. Comparisons are made for 5 age cohorts, for men and women, and without and with multivariate controls. The results contradict the usual finding of an inverse relationship between age and level of physical activity. On measures of (a) activity necessary to produce health benefits and (b) energy expenditure. Canadians over 65 were as active as, or more active than, their younger counterparts, and their activities did not decline over the 7 years between interviews. The extent of change varied by age and across women and men. Among women, increases in involvement were greatest in the middle-aged. Among men, the greatest increase was in the oldest age groups. For both genders, the youngest age cohort showed the smallest change over time, and there was evidence of slight declines in activity levels among young men.

scholarly journals Validity of the Global Physical Activity Questionnaire (GPAQ) in Adult Latinas

2012 ◽  
Vol 9 (5) ◽  
pp. 698-705 ◽  
Author(s):  
Tracy Hoos ◽  
Nancy Espinoza ◽  
Simon Marshall ◽  
Elva M. Arredondo
Keyword(s):  
Physical Activity ◽  
Self Report ◽  
Accelerometer Data ◽  
Post Intervention ◽  
Activity Intensity ◽  
Time Work ◽  
Global Physical Activity Questionnaire ◽  
Work Commute ◽  
The Impact ◽  
Multilevel Intervention

Background:Valid and reliable self-report measures of physical activity (PA) are needed to evaluate the impact of interventions aimed at increasing the levels of PA. However, few valid measures for assessing PA in Latino populations exist.Objective:The purpose of this study is to determine whether the GPAQ is a valid measure of PA among Latinas and to examine its sensitivity to intervention change. Intervention attendance was also examined.Methods:Baseline and postintervention data were collected from 72 Latinas (mean age = 43.01; SD = 9.05) who participated in Caminando con Fe/Walking with Faith, a multilevel intervention promoting PA among church-going Latinas. Participants completed the GPAQ and were asked to wear the accelerometer for 7 consecutive days at baseline and again 6 months later. Accelerometer data were aggregated into 5 levels of activity intensity (sedentary, light, moderate, moderate-vigorous, and vigorous) and correlated to self-reported mean minutes of PA across several domains (leisure time, work, commute and household chores).Results:There were significant correlations at postintervention between self-reported minutes per week of vigorous LTPA and accelerometer measured vigorous PA (r = .404, P < .001) as well as significant correlations of sensitivity to intervention change (post intervention minus baseline) between self-reported vigorous LTPA and accelerometer-measured vigorous PA (r = .383, P < .003) and self-reported total vigorous PA and accelerometer measured vigorous PA (r = .363, P < .003).Conclusions:The findings from this study suggest that the GPAQ may be useful for evaluating the effectiveness of programs aimed at increasing vigorous levels of PA among Latinas.

scholarly journals Ability of RT3 Accelerometer Cut Points to Detect Physical Activity Intensity in Ambulatory Children With Cerebral Palsy

2014 ◽  
Vol 31 (4) ◽  
pp. 310-324 ◽  
Author(s):  
Jennifer Ryan ◽  
Michael Walsh ◽  
John Gormley
Keyword(s):  
Physical Activity ◽  
Cerebral Palsy ◽  
Vigorous Physical Activity ◽  
Accelerometer Data ◽  
Physical Activity Intensity ◽  
Cut Points ◽  
Cut Point ◽  
Activity Intensity ◽  
Metabolic Equivalents ◽  
Children With Cerebral Palsy

This study investigated the ability of published cut points for the RT3 accelerometer to differentiate between levels of physical activity intensity in children with cerebral palsy (CP). Oxygen consumption (metabolic equivalents; METs) and RT3 data (counts/min) were measured during rest and 5 walking trials. METs and corresponding counts/min were classified as sedentary, light physical activity (LPA), and moderate to vigorous physical activity (MVPA) according to MET thresholds. Counts were also classified according to published cut points. A published cut point exhibited an excellent ability to classify sedentary activity (sensitivity = 89.5%, specificity = 100.0%). Classification accuracy decreased when published cut points were used to classify LPA (sensitivity = 88.9%, specificity = 79.6%) and MVPA (sensitivity = 70%, specificity = 95–97%). Derivation of a new cut point improved classification of both LPA and MVPA. Applying published cut points to RT3 accelerometer data collected in children with CP may result in misclassification of LPA and MVPA.

scholarly journals A Comparison of Preschoolers’ Physical Activity Indoors versus Outdoors at Child Care

2018 ◽  
Vol 15 (11) ◽  
pp. 2463 ◽  
Author(s):  
Pooja Tandon ◽  
Brian Saelens ◽  
Chuan Zhou ◽  
Dimitri Christakis
Keyword(s):  
Physical Activity ◽  
Child Care ◽  
Preschool Age ◽  
Accelerometer Data ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Preschool Age Children ◽  
Gps Devices ◽  
Outdoor Location ◽  
Indoor And Outdoor

The aims of this study were to quantify and examine differences in preschoolers’ indoor and outdoor sedentary time and physical activity intensity at child care using GPS devices and accelerometers. We conducted an observational study of 46 children (mean age 4.5 years, 30 boys, 16 girls) from five child care centers who wore accelerometers and GPS devices around their waists for five days during regular child care hours. GPS signal-to-noise ratios were used to determine indoor vs. outdoor location. Accelerometer data were categorized by activity intensity. Children spent, on average, 24% of child care time outdoors (range 12–37% by site), averaging 74 min daily outdoors (range 30–119 min), with 54% of children spending ≥60 min/day outdoors. Mean accelerometer activity counts were more than twice as high outdoors compared to indoors (345 (95) vs. 159 (38), (p < 0.001)), for girls and boys. Children were significantly less sedentary (51% of time vs. 75%) and engaging in more light (18% vs. 13%) and moderate-to-vigorous (MVPA) (31% vs. 12%) activity when outdoors compared to indoors (p < 0.001). To achieve a minute of MVPA, a preschooler needed to spend 9.1 min indoors vs. 3.8 min outdoors. Every additional 10 min outdoors each day was associated with a 2.9 min increase in MVPA (2.7 min for girls, 3.0 min for boys). Preschool-age children are twice as active and less sedentary when outdoors compared to indoors in child care settings. To help preschoolers achieve MVPA recommendations and likely attain other benefits, one strategy is to increase the amount of time they spend outdoors and further study how best to structure it.

scholarly journals Employing Machine Learning to Estimate Hallmark Measures of Physical Activities from Wrist-worn Devices Across Age Groups

2021 ◽  
Author(s):  
Mamoun T. Mardini ◽  
Chen Bai ◽  
Amal A. Wanigatunga ◽  
Santiago Saldana ◽  
Ramon Casanova ◽  
...  
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Energy Expenditure ◽  
Age Groups ◽  
Physical Activities ◽  
Accelerometer Data ◽  
Activity Type ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Score Range

Wrist-worn fitness trackers and smartwatches are proliferating with an incessant attention towards health tracking. Given the growing popularity of wrist-worn devices across all age groups, a rigorous evaluation for recognizing hallmark measures of physical activities and estimating energy expenditure is needed to compare their accuracy across the lifespan. The goal of the study was to build machine learning models to recognize physical activity type (sedentary, locomotion, and lifestyle) and intensity (low, light, and moderate), identify individual physical activities, and estimate energy expenditure. The primary aim of this study was to build and compare models for different age groups: young [20-50 years], middle (50-70 years], and old (70-89 years]. Participants (n = 253, 62% women, aged 20-89 years old) performed a battery of 33 daily activities in a standardized laboratory setting while wearing a portable metabolic unit to measure energy expenditure that was used to gauge metabolic intensity. Tri-axial accelerometer collected data at 80-100 Hz from the right wrist that was processed for 49 features. Results from random forests algorithm were quite accurate in recognizing physical activity type, the F1-Score range across age groups was: sedentary [0.955 – 0.973], locomotion [0.942 – 0.964], and lifestyle [0.913 – 0.949]. Recognizing physical activity intensity resulted in lower performance, the F1-Score range across age groups was: sedentary [0.919 – 0.947], light [0.813 – 0.828], and moderate [0.846 – 0.875]. The root mean square error range was [0.835 – 1.009] for the estimation of energy expenditure. The F1-Score range for recognizing individual physical activities was [0.263 – 0.784]. Performances were relatively similar and the accelerometer data features were ranked similarly between age groups. In conclusion, data features derived from wrist worn accelerometers lead to high-moderate accuracy estimating physical activity type, intensity and energy expenditure and are robust to potential age-differences.

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