Search Results

You are looking at 1 - 7 of 7 items for :

  • "posture allocation" x
Clear All
Restricted access

Xanne Janssen, Dylan P. Cliff, John J. Reilly, Trina Hinkley, Rachel A. Jones, Marijka Batterham, Ulf Ekelund, Soren Brage and Anthony D. Okely

This study examined the classification accuracy of the activPAL, including total time spent sedentary and total number of breaks in sedentary behavior (SB) in 4- to 6-year-old children. Forty children aged 4–6 years (5.3 ± 1.0 years) completed a ~150-min laboratory protocol involving sedentary, light, and moderate- to vigorous-intensity activities. Posture was coded as sit/lie, stand, walk, or other using direct observation. Posture was classified using the activPAL software. Classification accuracy was evaluated using sensitivity, specificity and area under the receiver operating characteristic curve (ROC-AUC). Time spent in each posture and total number of breaks in SB were compared using paired sample t-tests. The activPAL showed good classification accuracy for sitting (ROC-AUC = 0.84) and fair classification accuracy for standing and walking (0.76 and 0.73, respectively). Time spent in sit/lie and stand was overestimated by 5.9% (95% CI = 0.6−11.1%) and 14.8% (11.6−17.9%), respectively; walking was underestimated by 10.0% (−12.9−7.0%). Total number of breaks in SB were significantly overestimated (55 ± 27 over the course of the protocol; p < .01). The activPAL performed well when classifying postures in young children. However, the activPAL has difficulty classifying other postures, such as kneeling. In addition, when predicting time spent in different postures and total number of breaks in SB the activPAL appeared not to be accurate.

Restricted access

Dinesh John, Dixie L. Thompson, Hollie Raynor, Kenneth Bielak, Bob Rider and David R. Bassett


To determine if a treadmill-workstation (TMWS) increases physical activity (PA) and influences anthropometric, body composition, cardiovascular, and metabolic variables in overweight and obese office-workers.


Twelve (mean age= 46.2 ± 9.2 years) overweight/obese sedentary office-workers (mean BMI= 33.9 ± 5.0 kg·m-2) volunteered to participate in this 9-month study. After baseline measurements of postural allocation, steps per day, anthropometric variables, body composition, cardiovascular, and metabolic variables, TMWS were installed in the participants’ offices for their use. Baseline measurements were repeated after 3 and 9 months. Comparisons of the outcome variables were made using repeated-measures ANOVAs or nonparametric Friedman’s Rank Tests.


Between baseline and 9 months, significant increases were seen in the median standing (146−203 min·day-1) and stepping time (52−90 min·day-1) and total steps/day (4351−7080 steps/day; P < .05). Correspondingly, the median time spent sitting/lying decreased (1238−1150 min·day-1; P < .05). Using the TMWS significantly reduced waist (by 5.5 cm) and hip circumference (by 4.8 cm), low-density lipoproteins (LDL) (by 16 mg·dL-1), and total cholesterol (by 15 mg·dL-1) during the study (P < .05).


The additional PA energy expenditure from using the TMWS favorably influenced waist and hip circumferences and lipid and metabolic profiles in overweight and obese office-workers.

Restricted access

Stephanie L. Stockwell, Lindsey R. Smith, Hannah M. Weaver, Daniella J. Hankins and Daniel P. Bailey

cardiometabolic risk in children may be a result of measuring sedentary time using accelerometers that are unable to detect postural allocation. Therefore, standing time could be misclassified as sitting. 8 , 14 , 15 , 17 , 18 This is problematic as it may lead to overestimations of sedentary time and

Restricted access

Scott E. Crouter, Paul R. Hibbing and Samuel R. LaMunion

were based on direct observation of the activity during minutes 5–7 of each activity. Posture allocation was a secondary focus within the larger study, thus we chose to only collect posture data for a short period when the activity was most stable. Data from minutes 5–7 of each activity were included

Restricted access

Mynor Rodriguez-Hernandez, Jeffrey S. Martin, David D. Pascoe, Michael D. Roberts and Danielle W. Wadsworth

controlled for during the laboratory conditions to mimic “real-world” conditions. Although the accelerometer is an acceptable measure of physical activity and SED, it does not measure changes in postural allocation. Finally, menstrual cycle was not controlled in this trial. This may affect the results of the

Restricted access

Miguel A. de la Cámara, Sara Higueras-Fresnillo, Verónica Cabanas-Sánchez, Kabir P. Sadarangani, David Martinez-Gomez and Óscar L. Veiga

influence healthy aging. 29 , 30 New monitoring systems for determining postural allocation (ie, sitting, reclining, lying, and standing) as the ActivPAL or the Intelligent Device for Energy Expenditure and Activity (IDEEA) could provide more precise estimates of SB, and they can be useful for validating

Restricted access

Amber Watts, Mauricio Garnier-Villarreal and Paul Gardiner

monitors, reviewed the activity logs with study staff, filled out questionnaires, conducted cardiorespiratory (VO 2 max) testing, and were compensated for their participation. Measures The activPAL ™ is an accelerometer-based posture and activity assessment device that quantifies postural allocation