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1.
The purpose of the current study was to determine metabolic thresholds and subsequent activity intensity cutoff points for the ActiGraph GT1M with various epochs spanning from 5 to 60 sec in young children. Twenty-two children, aged 4 to 9 years, performed 10 different activities including locomotion and play activities. Energy expenditure was measured with indirect calorimetry. Thresholds and cutoff points were determined through receiver operating characteristic curves. The lower metabolic threshold was 6.19 kcal·kg?1·h?1 for moderate and 9.28 kcal·kg?1·h?1 for vigorous intensity. The cutoff points for the GT1M accelerometer appear to be lower than those for the previous model (7164). For 5-sec epochs, a cutoff point of 143 counts resulted for moderate intensity and of 208 counts for vigorous intensity activity. Whether short or long epochs were chosen when collecting data to determine cutoff points, does not appear to have an influence on the resulting cutoff values. Similarly, comparable results are seen when analyses are based on locomotion only as opposed to a wide range of activities including children's play.  相似文献   

2.
This aim of this study was to compare the new Actigraph (GT1M) with the widely used Model 7164. Seven days of free-living physical activity were measured simultaneously using both the Model 7164 and GT1M in 30 Indian adolescents (mean age 15.8 years, s = 0.6). The GT1M was on average 9% lower per epoch than model 7164, thus a correction factor of 0.91 is suggested for comparison between the two monitors. The differences between monitors increased in magnitude with intensity of activity (P < 0.001) but remained randomly distributed (r = 0.01, P = 0.96). No significant difference was observed between monitors for time spent in moderate (P = 0.31) and vigorous (P = 0.34) physical activity when using the same epoch length. The Model 7164 classified less time as sedentary (P < 0.001) and more time as light-intensity activity (P < 0.001) than the GT1M. In conclusion, data from the GT1M can be compared with historical data using average counts per minute with a correction factor, and the two models might be comparable for assessing time spent in moderate to vigorous physical activity in children when using the same epoch length.  相似文献   

3.
Abstract

This aim of this study was to compare the new Actigraph (GT1M) with the widely used Model 7164. Seven days of free-living physical activity were measured simultaneously using both the Model 7164 and GT1M in 30 Indian adolescents (mean age 15.8 years, s = 0.6). The GT1M was on average 9% lower per epoch than model 7164, thus a correction factor of 0.91 is suggested for comparison between the two monitors. The differences between monitors increased in magnitude with intensity of activity (P < 0.001) but remained randomly distributed (r = 0.01, P = 0.96). No significant difference was observed between monitors for time spent in moderate (P = 0.31) and vigorous (P = 0.34) physical activity when using the same epoch length. The Model 7164 classified less time as sedentary (P < 0.001) and more time as light-intensity activity (P < 0.001) than the GT1M. In conclusion, data from the GT1M can be compared with historical data using average counts per minute with a correction factor, and the two models might be comparable for assessing time spent in moderate to vigorous physical activity in children when using the same epoch length.  相似文献   

4.
目的:探讨儿童体力活动水平与健康体适能之间的相关性。方法:对大连市3所小学7~9岁儿童,运用ActiGraph GT9X Link型三轴加速度计进行体力活动水平测量,选取平均每天中等及以上运动强度的时间和平均每天消耗的卡路里2项指标,并完成相应的健康体适能指标测试,包括身体成分、柔韧性、心肺耐力、肌力和肌耐力。结果:平均每天中等及以上运动强度的时间越长,身体成分中体重指数越低,肌耐力测试中卷腹的次数越多,心肺耐力测试中20m折返跑往返的次数越多。结论:增加儿童平均每天中等及以上运动强度的时间,有助于提高儿童健康体适能水平,但是儿童平均每天消耗的卡路里与健康体适能水平之间没有显著的相关性。  相似文献   

5.
Abstract

The aim of this study was to compare the outputs of three commonly used uniaxial Actigraph models (Actitrainer, 7164 and GT1M) under both free-living and controlled laboratory conditions. Ten adults (mean age = 24.7±1.1 years) wore the three Actigraph models simultaneously during one of day free-living and during a progressive exercise protocol on a treadmill at speeds between 1.5 and 5.5 miles per hour (mph). During free-living the three Actigraph models produced comparable outputs in moderate, vigorous and moderate-to-vigorous physical activity (MVPA) with effect sizes typically <0.2, but lower comparability was seen in sedentary and light categories, as well as in total step counts (effect sizes often >0.30). In controlled conditions, acceptable comparability between the three models was seen at all treadmill speeds, the exception being walking at 1.5 mph (mean effect size = 0.48). It is concluded that care should be taken if different Actigraph models are to be used to measure and compare light physical activity, step counts and walking at very low speeds. However, using any of these three different Actigraph models to measure and compare levels of MVPA in free-living adults seems appropriate.  相似文献   

6.
This study investigated the effects of epoch length and cut point selection on adolescent physical activity intensity quantification using vertical axis and vector magnitude (VM) measurement with the ActiGraph GT3X+ accelerometer. Four hundred and nine adolescents (211 males; 198 females) aged 12–16 years of age wore accelerometers during waking hours. The GT3X+ acceleration counts were reintegrated into 1, 5, 15, 30 and 60 s epoch lengths for both vertical axis and VM counts. One cut point was applied to vertical axis counts and three different cut points were applied to VM counts for each epoch length. Significant differences (P < 0.01) in mean total counts per day were observed between vertical axis and VM counts, and between epoch lengths for VM only. Differences in physical activity levels were observed between vertical and VM cut points, and between epoch lengths across all activity intensities. Our findings illustrate the magnitude of differences in physical activity outcomes that occur between axis measurement, cut points and epoch length. The magnitude of difference across epoch length must be considered in the interpretation of accelerometer data and seen as a confounding variable when comparing physical activity levels between studies.  相似文献   

7.
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   

8.
Our study investigated the performance of proximity sensor-based wear-time detection using the GT9X under laboratory and free-living settings. Fifty-two volunteers (23.2 ± 3.8 y; 23.2 ± 3.7 kg/m2) participated in either a laboratory or free-living protocol. Lab participants wore and removed a wrist-worn GT9X on 3–5 occasions during a 3-hour directly observed activity protocol. The 2-day free-living protocol used an independent temperature sensor and self-report as the reference to determine if wrist and hip-worn GT9X accurately determined wear (i.e., sensitivity) and non-wear (i.e., specificity). Free-living estimates of wear/non-wear were also compared to Troiano 2007 and Choi 2012 wear/non-wear algorithms. In lab, sensitivity and specificity of the wrist-worn GT9X in detecting total minutes of wear-on and off was 93% and 49%, respectively. The GT9X detected wear-off more often than wear-on, but with a greater margin of error (4.8 ± 11.6 vs. 1.4 ± 1.4 min). In the free-living protocol, wrist and hip-worn GT9X’s yielded sensitivity and specificity of 72 and 90% and 84 and 92%, respectively. GT9X estimations had inferior sensitivity but superior specificity to Troiano 2007 and Choi 2012 algorithms. Due to inaccuracies, it may not be advisable to singularly use the proximity-sensor-based wear-time detection method to detect wear-time.  相似文献   

9.
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   

10.
Accelerometry is the gold standard for field-based physical activity assessment in children; however, the plethora of devices, data reduction procedures, and cut-points available limits comparability between studies. This study aimed to compare physical activity variables from the ActiGraph GT3X+ and Actical accelerometers in children under free-living conditions. A cross-sectional study of 379 children aged 9–11 years from Ottawa (Canada) was conducted. Children wore the ActiGraph GT3X+ and Actical accelerometers on the hip simultaneously for 7 consecutive days (24-h protocol). Moderate-to-vigorous (MVPA), vigorous (VPA), moderate (MPA), and light (LPA) physical activity, as well as sedentary time, (SED) were derived using established data reduction protocols. Excellent agreement between devices was observed for MVPA (ICC = 0.73–0.80), with fair to good agreement for MPA, LPA and SED, and poor agreement for VPA. Bland-Altman plots showed excellent agreement for MVPA, LPA, and SED, adequate agreement for MPA, and poor agreement for VPA. MVPA derived from the Actical was 11.7% lower than the ActiGraph GT3X+. The ActiGraph GT3X+ and Actical are comparable for measuring children’s MVPA. However, comparison between devices for VPA, MPA, LPA, and SED are highly dependent on data reduction procedures and cut-points, and should be interpreted with caution.  相似文献   

11.
In football, kicking with high ball velocity can increase scoring opportunities and reduce the likelihood of interception. Efficient energy transfer from foot to ball during impact is important to attain a high ball velocity. It is considered impact efficiency can be increased by reducing the change in ankle plantarflexion during foot–ball impact. However, conflicting evidence exists, questioning its effectiveness as a coaching cue. The aim of the present study was to systematically analyse joint stiffness, foot velocity and impact location with a mechanical kicking machine to determine if change in ankle plantarflexion during foot–ball impact and ball velocity are influenced. Sagittal plane data of the shank, foot and ball were measured using high-speed video (4,000 Hz). Increasing joint stiffness reduced change in ankle plantarflexion and increased ball velocity from a greater effective mass. Increasing foot velocity increased change in ankle plantarflexion and increased ball velocity. Distal impact locations increased change in ankle plantarflexion and reduced ball velocity as coefficient of restitution decreased. These results identify that change in ankle plantarflexion is a dependent variable during foot–ball impact and does not directly influence ball velocity. Coaches can assess ankle motion during impact to provide feedback to athletes on their impact efficiency.  相似文献   

12.
Predicting activity energy expenditure using the Actical activity monitor   总被引：1，自引：0，他引：1  
This study developed algorithms for predicting activity energy expenditure (AEE) in children (n = 24) and adults (n = 24) from the Actical activity monitor. Each participant performed 10 activities (supine resting, three sitting, three house cleaning, and three locomotion) while wearing monitors on the ankle, hip, and wrist; AEE was computed from oxygen consumption. Regression analysis, used to create AEE prediction equations based on Actical output, varied considerably for both children (R2 = .45-.75; p < .001) and adults (R2 = .14-.85; p < .008). Most of the resulting algorithms accurately predicted accumulated AEE and time within light, moderate, and vigorous intensity categories (p > .05). The Actical monitor may be useful for predicting AEE and time variables at the ankle, hip, or wrist locations.  相似文献   

13.
Abstract

Adolescents' objectively assessed physical activity (PA) patterns during specific segments of the day remain unclear. In order to develop a clearer understanding this study examined country and gender differences in moderate to vigorous physical activity (MVPA) levels during specific segments of weekdays and weekend days, and explored the contribution of each segment to PA guidelines. Morpho-demographic, socio-economic and PA data were collected from a sample of 829 French and Spanish adolescents (45.0% Spanish; 55.2% females; 14.33±.73 years). Actigraph GT3X accelerometers were worn for seven days to assess adolescents' MVPA for three segments of weekdays (school-travel-time, school-time, and non-school-time), and weekend days (morning-time, afternoon-time and night-time). Data were analysed using multilevel modelling. The most active segments were non-school-time (29.2±17.5 min) and school-time (25.8±14.2 min) during weekdays, and morning-time (28.2±25.8 min) on weekend days. Except for school-time, Spanish adolescents were more significantly active than French adolescents during all segments. Significant gender differences were found in all segments. Country differences highlight the need to recognise cultural contexts that influence adolescents' PA. Common European-wide strategies may be insufficient to increase MVPA levels if cultural variability is not considered. Spanish and French PA intervention programmes should target girls and low-active boys during non-school-time and weekends.  相似文献   

14.
Current interest in promoting physical activity in the school environment necessitates an inexpensive, accurate method of measuring physical activity in such settings. Additionally, it is recognized that physical activity must be of at least moderate intensity in order to yield substantial health benefits. The purpose of the study, therefore, was to determine the validity of the New Lifestyles NL-1000 (New Lifestyles, Inc., Lee's Summit, Missouri, USA) accelerometer for measuring moderate-to-vigorous physical activity in school settings, using the Actigraph GT1M (ActiGraph, Pensacola, Florida, USA) as the criterion. Data were collected during a cross-country run (n = 12), physical education (n = 18), and classroom-based physical activities (n = 42). Significant and meaningful intraclass correlations between methods were found, and NL-1000 estimates of moderate-to-vigorous physical activity were not meaningfully different from GT1M-estimated moderate-to-vigorous physical activity. The NL-1000 therefore shows promising validity evidence as an inexpensive, convenient method of measuring moderate-to-vigorous physical activity in school settings.  相似文献   

15.
In the collision between a striking implement and ball, the term “sweet spot” represents the impact location producing best results. In football kicking, it is not known if a sweet spot exists on the foot because no method to measure impact location in three-dimensional space exists. Therefore, the aims were: (1) develop a method to measure impact location on the foot in three-dimensional space; (2) determine if players impacted the ball with a particular location; (3) determine the relationship between impact location with kick performance; (4) discuss if a sweet spot exists on the foot. An intra-individual analysis was performed on foot-ball impact characteristics of ten players performing 30 Australian football drop punt kicks toward a target. (1) A method to measure impact location was developed and validated. (2) The impact locations were normally distributed, evidenced by non-significant results of the Shapiro-Wilk test (p > 0.05) and inspection of histograms, meaning players targeted a location on their foot. (3) Impact location influenced foot-ball energy transfer, ball flight trajectory and ankle plantar/dorsal flexion. (4) These results indicate a sweet spot exists on the foot for the Australian football drop punt kick. In conclusion, the impact location is an important impact characteristic.  相似文献   

16.
The purpose of this study was to determine the reliability of the Actigraph GT1M (Pensacola, FL, USA) accelerometer activity count and step functions. Fifty GT1M accelerometers were initialized to collect simultaneous acceleration counts and steps data using 15-sec epochs. All reliability testing was completed using a mechanical shaker plate to perform six different test conditions in Experiment 1 and 18 test conditions in Experiment 2. The overall intra- and inter-instrument reliability of the GT1M was CVintra = 2.9% and CVinter = 3.5% for counts and CVintra = 1.1% and CVinter = 1.2% for steps. No batch effects were evident in the 50 GT1Ms. The Actigraph GT1M accelerometer demonstrated good reliability for measuring both counts and steps. However, the ability of the GT1M to consistently detect acceleration at a given acceleration and frequency condition varied widely. Future studies clarifying the filtering limitations and the threshold necessary to detect the occurrence of movement are warranted.  相似文献   

17.
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   

18.
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   

19.
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20.
Calibration of two objective measures of physical activity for children   总被引：9，自引：7，他引：2  
A calibration study was conducted to determine the threshold counts for two commonly used accelerometers, the ActiGraph and the Actical, to classify activities by intensity in children 5 to 8 years of age. Thirty-three children wore both accelerometers and a COSMED portable metabolic system during 15 min of rest and then performed up to nine different activities for 7 min each, on two separate days in the laboratory. Oxygen consumption was measured on a breath-by-breath basis, and accelerometer data were collected in 15-s epochs. Using receiver operating characteristic curve (ROC) analysis, cutpoints that maximised both sensitivity and specificity were determined for sedentary, moderate and vigorous activities. For both accelerometers, discrimination of sedentary behaviour was almost perfect, with the area under the ROC curve at or exceeding 0.98. For both the ActiGraph and Actical, the discrimination of moderate (0.85 and 0.86, respectively) and vigorous activity (0.83 and 0.86, respectively) was acceptable, but not as precise as for sedentary behaviour. This calibration study, using indirect calorimetry, suggests that the two accelerometers can be used to distinguish differing levels of physical activity intensity as well as inactivity among children 5 to 8 years of age.  相似文献   

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