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1.
This study examined the validity of the Actical accelerometer step count and energy expenditure (EE) functions in healthy young adults. Forty-three participants participated in study 1. Actical step counts were compared to actual steps taken during a 200 m walk around an indoor track at self-selected pace and during treadmill walking at different speeds (0.894, 1.56 and 2.01 m · s–1) for 5 min. The Actical was also compared to three pedometers. For study 2, 15 participants from study 1 walked on a treadmill at their predetermined self-selected pace for 15 min. Actical EE was compared to EE measured by indirect calorimetry. One-way analysis of variance and t-tests were used to examine differences. There were no statistical difference between Actical steps and actual steps in self-selected pace walking and during treadmill walking at moderate and fast speeds. During treadmill walking at slow speed, the Actical step counts significantly under predicted actual steps taken. For study 2, there was no statistical difference between measured EE and Actical-recorded EE. The Actical provides valid estimates of step counts at self-selected pace and walking at constant speeds of 1.56 and 2.01 m · s–1. The Actical underestimates EE of walking at constants speeds ≥1.38 m · s–1.  相似文献   

2.
Wrist-based accelerometers are increasingly used to assess physical activity (PA) in population-based studies; however, cut-points to translate wrist-based accelerometer counts into PA intensity categories are still needed. The purpose of this study was to determine wrist-based cut-points for moderate- and vigorous-intensity ambulatory PA in adults for the Actical accelerometer. Healthy adults (n = 24) completed a four-phase treadmill exercise protocol (1.9, 3.0, 4.0 and 5.2 mph) while wearing an Actical accelerometer on their wrist. Metabolic equivalent of task (MET) levels were assessed by indirect calorimetry. Receiver operating characteristics (ROC) curves were generated to determine accelerometer counts that maximised sensitivity and specificity for classification of moderate (≥3 METs) and vigorous (>6 METs) ambulatory activity. The area under the ROC curves to discriminate moderate- and vigorous-intensity ambulatory activity were 0.93 (95% confidence interval [CI]: 0.90–0.97; P < 0.001) and 0.96 (95% CI: 0.94–0.99; P < 0.001), respectively. The identified cut-point for moderate-intensity ambulatory activity was 1031 counts per minute, which had a corresponding sensitivity and specificity of 85.6% and 87.5%, respectively. The identified cut-point for vigorous intensity ambulatory activity was 3589 counts per minute, which had a corresponding sensitivity and specificity of 88.0% and 98.7%, respectively. This study established intensity-specific cut-points for wrist-based wear of the Actical accelerometer which are recommended for quantification of moderate- and vigorous-intensity ambulatory activity.  相似文献   

3.
Abstract

Accelerometry is increasingly used as a physical activity surveillance device that can quantify the amount of time spent moving at a range of intensities. This study proposes physical activity intensity cut-points for the Actical accelerometer. Thirty-eight volunteers completed a multi-stage treadmill protocol at 3, 5, and 8 km · h?1 (2, 3.3, and 8 METs) while wearing Actical accelerometers initialized to collect data in 60-s epochs. Using a decision boundary analytical approach, moderate and vigorous physical activity intensity cut-points were derived for the Actical accelerometer. In adults (n = 26), the cut-point for moderate physical activity intensity occurred at 1535 counts per minute and the vigorous cut-point occurred at 3960 counts per minute. In children (n = 12), the cut-point for moderate physical activity intensity occurred at 1600 counts per minute and the vigorous cut-point occurred at 4760 counts per minute. Improved classification of physical activity intensity using the decision boundary cut-points was observed compared with using mean values for each protocol stage. The cut-points derived are recommended for use in adults. The cut-points derived for children confirm the findings of previous studies.  相似文献   

4.
Accurate estimation of energy expenditure (EE) from accelerometer outputs remains a challenge in older adults. The aim of this study was to validate different ActiGraph (AG) equations for predicting EE in older adults. Forty older adults (age = 77.4 ± 8.1 yrs) completed a set of household/gardening activities in their residence, while wearing an AG at the hip (GT3X+) and a portable calorimeter (MetaMax 3B – criterion). Predicted EEs from AG were calculated using five equations (Freedson, refined Crouter, Sasaki and Santos-Lozano (vertical-axis, vectormagnitude)). Accuracy of equations was assessed using root-mean-square error (RMSE) and mean bias. The Sasaki equation showed the lowest RMSE for all activities (0.47 METs) and across physical activity intensities (PAIs) (range 0.18–0.48 METs). The Freedson and Santos-Lozano equations tended to overestimate EE for sedentary activities (range: 0.48 to 0.97 METs), while EEs for moderate-to-vigorous activities (MVPA) were underestimated (range: ?1.02 to ?0.64 METs). The refined Crouter and Sasaki equations showed no systematic bias, but they respectively overestimated and underestimated EE across PAIs. In conclusion, none of the equations was completely accurate for predicting EE across the range of PAIs. However, the refined Crouter and Sasaki equations showed better overall accuracy and precision when compared with the other methods.  相似文献   

5.
Abstract

The ActiGraph activity monitors have developed and newer versions of the ActiGraph accelerometers (GT1M, GT3X and GT3X +) are now available, including changes in hardware and software compared to the old version (AM7164). This is problematic as most of the validation and calibration work includes the AM7164. The aims of the study were to validate the ActiGraph GT1M during level and graded walking and to assess the potential underestimation of physical activity during cycling. Data were obtained from 20 participants during treadmill walking and ergometer cycling. Energy expenditure was measured via indirect calorimetry and used as the criterion method. Activity counts were highly correlated with energy expenditure during level walking (R2 = 0.82) and graded walking at 5% and 8% (R2 = 0.82 and R2 = 0.67, respectively). There was no linear relationship between activity counts and energy expenditure during cycling. The average activity counts for all data points during cycling was 1,157 counts per minute (CPM) (SD = 974), and mean energy expenditure was 5.0 metabolic equivalents. The GT1M is a valid tool for assessing walking across a wide range of speeds and gradients. However, there is no relationship between activity counts and energy expenditure during cycling and physical activity is underestimated by ≈73% during cycling compared to walking.  相似文献   

6.
This study compared the energy expenditure (EE) levels during object projection skill performance (OPSP) as assessed by indirect calorimetry and accelerometry. Thirty-four adults (female n = 18) aged 18–30 (23.5 ± 2.5 years) performed three, 9-min sessions of kicking, over-arm throwing, and striking performed at 6-, 12-, and 30-sec intervals. EE was estimated (METS) using indirect calorimetry (COSMED K4b2) and hip-worn accelerometry (ActiGraph GT3X+). EE using indirect calorimetry demonstrated moderate-intensity physical activity (3.4 ± 0.7 METS––30-sec interval, 5.8 ± 1.2 METS––12-sec interval) to vigorous intensity physical activity (8.3 ± 1.7 METS––6-sec interval). However, accelerometry predicted EE suggested only light-intensity physical activity (1.7 ± 0.2 METS––30-sec interval, 2.2 ± 0.4 METS––12-sec interval, 2.7 ± 0.6 METS––6-sec interval). Hip-worn, ActiGraph GT3X+ accelerometers do not adequately capture physical activity intensity levels during OPSP, regardless of differences in skill performance intervals.  相似文献   

7.
This study aimed at translating the physical activity (PA) guideline (180 min of total PA per day) into a step count target in preschoolers. 535 Flemish preschoolers (mean age: 4.41 ± 0.58) wore an ActiGraph accelerometer (GT1M, GT3X and GT3X+) – with activated step count function – for four consecutive days. The step count target was calculated from the accelerometer output using a regression equation, applying four different cut-points for light-to-vigorous PA: Pate, Evenson, Reilly, and Van Cauwenberghe. The present analysis showed that 180 min of total PA per day is equivalent to the following step count targets: 5,274 steps/day using the Pate cut-point, 4,653 steps/day using the Evenson cut-point, 11,379 steps/day using the Reilly cut-point and 13,326 steps/day using the Van Cauwenberghe cut-point. Future studies should focus on achieving consensus on which cut-points to use in preschoolers before a definite step count target in preschoolers can be proposed. Until then, we propose to use a provisional step count target of 11,500 steps/day as this step count target is attainable, realistic and helpful in promoting preschoolers’ PA.  相似文献   

8.
ABSTRACT

This study validated sedentary behaviour (SB), moderate-to-vigorous physical activity (MVPA) and vigorous physical activity (VPA) accelerometer cut-points in 5–7-year-old children. Participants (n = 49, 55% girls) wore an ActiGraph GT9X accelerometer, recording data at 100 Hz downloaded in 1 s epochs, on both wrists and the right hip during a standardised protocol and recess. Cut-points were generated using ROC analysis with direct observation as a criterion. Subsequently, cut-points were optimised using Confidence intervals equivalency analysis and then cross-validated in a cross-validation group. SB cut-points were 36 mg (Sensitivity (Sn) = 79.8%, Specificity (Sp) = 56.8%) for non-dominant wrist, 39 mg (Sn = 75.4%, Sp = 70.2%) for dominant wrist and 20 mg (Sn = 78%, Sp = 50.1%) for hip. MVPA cut-points were 189 mg (Sn = 82.6%, Sp = 78%) for non-dominant wrist, 181 mg (Sn = 79.1%, Sp = 76%) for dominant wrist and 95 mg (Sn = 79.3%, Sp = 75.6%) for hip. VPA cut-points were 536 mg (Sn = 75.1%, Sp = 68.7%) for non-dominant wrist, 534 mg (Sn = 67.6%, Sp = 95.6%) for dominant wrist and 325 mg (Sn = 78.2%, Sp = 96.1%) for hip. All placements demonstrated adequate levels of accuracy for SB and PA assessment.  相似文献   

9.
Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7–16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.  相似文献   

10.
ABSTRACT

Accelerometer cut points are an important consideration for distinguishing the intensity of activity into categories such as moderate and vigorous. It is well-established in the literature that these cut points depend on a variety of factors, including age group, device, and wear location. The Actigraph GT9X is a newer model accelerometer that is used for physical activity research, but existing cut points for this device are limited since it is a newer device. Furthermore, there is not existing data on cut points for the GT9X at the ankle or foot locations, which offers some potential benefit for activities that do not involve arm and/or core motion. A total of N = 44 adults completed a four-stage treadmill protocol while wearing Actigraph GT9X sensors at four different locations: foot, ankle, wrist, and hip. Metabolic Equivalent of Task (MET) levels assessed by indirect calorimetry along with Receiver Operating Characteristic (ROC) curves were used to establish cut points for moderate and vigorous intensity for each wear location of the GT9X. Area under the ROC curves indicated high discrimination accuracy for each case.  相似文献   

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