A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults

Narayanan, Anantha; Hedayatrad, Leila; Neville, Jonathon; Mackay, Lisa; Duncan, Scott

doi:10.1249/mss.0000000000001717

Cited by 47 publications

(62 citation statements)

References 27 publications

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“…The hip- and wrist-based models achieved 91.0% and 88.4% accuracy, respectively. In a study by Stewart et al [ 17 ] a dual-accelerometry system was evaluated with both children and adults for the identification of six activity types. One device was worn at the thigh and another device worn on the lower back.…”

Section: Discussionmentioning

confidence: 99%

“…However, the size and bulky design of the ActiGraph GT3X device does not make the proposed method by Skotte et al [ 16 ] applicable for use with smaller children. In the study by Stewart et al [ 17 ], a smaller open source Axivity AX3 (Axivity, Newcastle, UK) device was used for the identification of children’s activity types using accelerometers worn at the thigh and trunk in addition to the use of a more advanced machine learning method in the data processing [ 17 ]. However, besides the use of an advanced method, the study only provided data for children 7–15 years of age and did not investigate the identification of biking.…”

Section: Introductionmentioning

confidence: 99%

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Simple Method for the Objective Activity Type Assessment with Preschoolers, Children and Adolescents

Brønd

Grøntved

Andersen³

et al. 2020

Children

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Background: The objective and accurate assessment of children’s sedentary and physical behavior is important for investigating their relation to health. The purpose of this study is to validate a simple and robust method for the identification of sitting, standing, walking, running and biking performed by preschool children, children and adolescents in the age from 3 to 16 years from a single thigh-worn accelerometer. Method: A total of 96 children were included in the study and all subjects followed a structured activity protocol performed in the subject’s normal kindergarten or school environment. Thigh acceleration was measured using the Axivity AX3 (Axivity, Newcastle, UK) device. Method development and accuracy was evaluated by equally dividing the subjects into a development and test group. Results: The sensitivity and specificity for identifying sitting and standing was above 99.3% and for walking and running above 82.6% for all age groups. The sensitivity and specificity for identifying biking was above 85.8% for children and adolescents and above 64.8% for the preschool group using running bikes. Conclusion: The accurate assessment of sitting, standing, walking, running and biking from thigh acceleration and with children in the age range of 3 to 16 is valid, although not with preschool children using running bikes.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simple Method for the Objective Activity Type Assessment with Preschoolers, Children and Adolescents

Brønd

Grøntved

Andersen³

et al. 2020

Children

View full text Add to dashboard Cite

show abstract

“…Simple cut-point approaches applied to either processed activity counts or raw acceleration signal (i.e., Euclidean Norm Minus One -ENMO) provide misleading estimates of movement behaviour because they do not account for upper limb movements during sedentary or stationary light-intensity activities [20,21]. In investigations where sitting time is of primary interest, assessments of posture with thigh mounted accelerometers, alone or in combination with other placements, should be considered [22,23]. The findings of the Steene-Johannessen study highlight the long-standing methodological issue of how to operationalise compliance with physical activity guidelines in accelerometer-based studies [24].…”

Section: Stewart G Trostmentioning

confidence: 99%

Population-level physical activity surveillance in young people: are accelerometer-based measures ready for prime time?

Trost

2020

Int J Behav Nutr Phys Act

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“…In addition, although Axivity monitors have been shown to be reliable measuring physical activity in over 100,000 participants 94 , with primary school aged children, most research uses waist-worn Actigraph accelerometers 19 95 , while the one study that used Axivity Ax3 accelerometers had them mounted with tape on the waist 96 . It is suggested that when using Axivity accelerometers in children, a dual-accelerometer system with sensors placed on the thigh and the back should be included for greater accuracy 97 . However, this may not be a viable option for school-based research in young children.…”

Section: Study Limitationsmentioning

confidence: 99%

Impact of the “Thinking while Moving in English” intervention on primary school children’s physical activity and academic outcomes: A cluster randomized controlled trial

Mavilidi¹,

Lubans²,

Miller³

et al. 2020

Preprint

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Background: The majority of children internationally are not sufficiently active. Integrating physical activity into academic lesson time may not only help increase children’s activity levels but also improve learning. The aim of this study was to assess the impact of a classroom-based physical activity intervention on primary school students’ physical activity levels and academic outcomes (i.e., on-task behavior, literacy and executive function skills). Methods: This cluster randomized controlled trial included students ( N = 283) from nine primary schools located in New South Wales, Australia. Schools were allocated to a control (n = 5 schools) or Thinking while Moving in English (TWM-E) (n = 4 schools) conditions. Teachers received professional learning (i.e. one day workshop), resources (e.g. drill ladders, lettered bean bags), and mentoring from the research team. Teachers in the TWM-E condition delivered three 40-min physically active English lessons per week for six weeks, whereas the control condition continued with the usual lessons. For both conditions, assessments occurred at baseline and post-test (six weeks). Children wore accelerometers on their wrists (Axivity) for one week during school time to measure their intensity of physical activity intensity (primary outcome). On-task behavior was assessed using a momentary time sampling procedure and expressed as a percentage of lesson time. Standardized tests were used to assess literacy skills (i.e., spelling, grammar and punctuation) and executive functioning (i.e, inhibition and task shifting). Results: No significant group differences were observed for physical activity outcomes, spelling or executive functions. Compared to the control group, the TWM-E group displayed improved on-task behavior (adjusted mean difference = 18.1% of lesson time, 95% CI [10.12 to 26.02], p < .001, d = 0.53), and improved grammar and punctuation scores (adjusted mean difference = 3.0, 95% CI [ 0.7 to 5.4], p = 0.018, d = 0.16). Conclusions: Despite minimal effect on overall physical activity levels, active lessons have important benefits for students’ on-task behavior and literacy.

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A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults

Abstract: When previous wear time compliance results are taken together with our findings, it represents a promising step forward for monitoring and understanding 24-h time-use behaviors. The next step will be to examine the generalizability of these findings in a free-living setting.

Cited by 47 publications

References 27 publications

Simple Method for the Objective Activity Type Assessment with Preschoolers, Children and Adolescents

Simple Method for the Objective Activity Type Assessment with Preschoolers, Children and Adolescents

Population-level physical activity surveillance in young people: are accelerometer-based measures ready for prime time?

Impact of the “Thinking while Moving in English” intervention on primary school children’s physical activity and academic outcomes: A cluster randomized controlled trial

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