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1.
This study establishes tri-axial activity count (AC) cut-points for the GT3X+ accelerometer to classify physical activity intensity in overweight and obese adults. Further, we examined the accuracy of established and novel energy expenditure (EE) prediction equations based on AC and other metrics. Part 1: Twenty overweight or obese adults completed a 30 minute incremental treadmill walking protocol. Heart rate (HR), EE, and AC were measured using the GT3X+ accelerometer. Part 2: Ten overweight and obese adults conducted a self-paced external walk during which EE, AC, and HR were measured. Established equations (Freedson et al., 1998; Sasaki et al., 2011) overestimated EE by 40% and 31%, respectively (p < .01). Novel gender-specific prediction equations provided good estimates of EE during treadmill and outdoor walking (standard error of the estimate = .91 and .65, respectively). We propose new cut-points and prediction equations to estimate EE using the GT3X+ tri-axial accelerometer in overweight and obese adults.  相似文献   

2.
This study compared accuracy of energy expenditure (EE) prediction models from accelerometer data collected in structured and simulated free-living settings. Twenty-four adults (mean age 45.8 years, 50% female) performed two sessions of 11 to 21 activities, wearing four ActiGraph GT9X Link activity monitors (right hip, ankle, both wrists) and a metabolic analyzer (EE criterion). Visit 1 (V1) involved structured, 5-min activities dictated by researchers; Visit 2 (V2) allowed participants activity choice and duration (simulated free-living). EE prediction models were developed incorporating data from one setting (V1/V2; V2/V2) or both settings (V1V2/V2). The V1V2/V2 method had the lowest root mean square error (RMSE) for EE prediction (1.04–1.23 vs. 1.10–1.34 METs for V1/V2, V2/V2), and the ankle-worn accelerometer had the lowest RMSE of all accelerometers (1.04–1.18 vs. 1.17–1.34 METs for other placements). The ankle-worn accelerometer and associated EE prediction models developed using data from both structured and simulated free-living settings should be considered for optimal EE prediction accuracy.  相似文献   

3.
ABSTRACT

The activPAL is a widely-used measure of sedentary time but few studies have evaluated its ability to estimate physical activity intensity. This study determined the accuracy of the algorithm used by the activPAL to predict metabolic equivalents (METs) from cadence and a curvilinear cadence-METs equation individualized for height. Thirty-six healthy adults (25 ± 6 years) completed a progressive walking protocol. Stepping cadence was video recorded and METs were determined via indirect calorimetry. Manually-counted cadence was input into the activPAL and curvilinear equations. The internal activPAL equation overpredicted METs at slower cadences (<120 steps/minute) but underpredicted METs at faster cadences (>120 step/minute) (proportional bias, p < .001). Conversely, the curvilinear equation exhibited neither fixed (p = .37) nor proportional bias (p = .07), and a lower absolute MET difference [0.87 ± 0.65 (range:0.0–3.2) vs. 0.56 ± 0.45 (range:0.0–2.7) METs]. The linear activPAL equation poorly estimates METs from stepping cadence but these inaccuracies may be lessened through the use of an individualized curvilinear equation.  相似文献   

4.
ABSTRACT

A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of activities using acceleration, physiological signals (e.g., heart rate, body temperature, galvanic skin response), and participant characteristics (e.g., sex, age, height, weight, body composition) collected from wearable devices (Fitbit charge 2, Polar H7, SenseWear Armband Mini and Actigraph GT3-x) as potential inputs. By utilising a leave-one-out cross-validation approach in 59 subjects, we investigated the predictive accuracy in sedentary, ambulatory, household, and cycling activities compared to indirect calorimetry (Vyntus CPX). Over all activities, correlations of at least r = 0.85 were achieved by the models. Root mean squared error ranged from 1 to 1.37 METs and all overall models were statistically equivalent to the criterion measure. Significantly lower error was observed for Actigraph and Sensewear models, when compared to the manufacturer provided estimates of the Sensewear Armband (p < 0.05). A high degree of accuracy in EE estimation was achieved by applying non-linear models to wearable devices which may offer a means to capture the energy cost of free-living activities.  相似文献   

5.
This study examined the metabolic cost (METs) of performing object projection skills at three practice trial intervals (6, 12, and 30 seconds). Forty adults (female n = 20) aged 18–30 (M = 23.7 ± 2.9 years) completed three, nine-minute sessions of skill trials performed at 6, 12, and 30 second intervals. Participants performed kicking, throwing and striking trials in a blocked schedule with maximal effort. Average METs during each session were measured using a COSMED K4b2. A three (interval condition) X two (sex) ANOVA was conducted to examine differences in METs across interval conditions and by sex. Results indicated a main effect for interval condition (F(5,114) = 187.02, p < .001, η2 = 0.76) with decreased interval times yielding significantly higher METs [30 sec = 3.45, 12 sec = 5.68, 6 sec = 8.21]. A main effect for sex (F(5, 114) = 35.39, p < .001, η2 = 0.24) also was found with men demonstrating higher METs across all intervals. At a rate of only two trials/min, participants elicited moderate physical activity, with 12 and 6-second intervals exhibiting vigorous PA. Demonstrating MVPA during the performance of object projection skill performance has potential implications for PA interventions.  相似文献   

6.
The purpose of this study was to validate a wireless network of accelerometers and compare it to a hip-mounted accelerometer for predicting energy expenditure in a semi-structured environment. Adults (n = 25) aged 18–30 engaged in 14 sedentary, ambulatory, exercise, and lifestyle activities over a 60-min protocol while wearing a portable metabolic analyser, hip-mounted accelerometer, and wireless network of three accelerometers worn on the right wrist, thigh, and ankle. Participants chose the order and duration of activities. Artificial neural networks were created separately for the wireless network and hip accelerometer for energy expenditure prediction. The wireless network had higher correlations (r = 0.79 vs. r = 0.72, P < 0.01) but similar root mean square error (2.16 vs. 2.09 METs, P > 0.05) to the hip accelerometer. Measured (from metabolic analyser) and predicted energy expenditure from the hip accelerometer were significantly different for the 3 of the 14 activities (lying down, sweeping, and cycle fast); conversely, measured and predicted energy expenditure from the wireless network were not significantly different for any activity. In conclusion, the wireless network yielded a small improvement over the hip accelerometer, providing evidence that the wireless network can produce accurate estimates of energy expenditure in adults participating in a range of activities.  相似文献   

7.
Wrist-based accelerometers are now common in assessing physical activity (PA) and sedentary behaviour (SB) in population-based studies, but there is a scarcity of raw acceleration cutpoints in older adults. The study aimed to determine and evaluate wrist-based GENEActiv (GA) and hip-based ActiGraph GT3X+ (AG) raw acceleration cutpoints for SB and moderate-to-vigorous PA (MVPA) in older adults ≥60 years of age. A laboratory-based calibration analyses of 34 healthy older adults involved receiver operator characteristic (ROC) curves to determine raw acceleration cutpoints for SB and MVPA. ROC analysis revealed an area under the curve (AUC) of 0.88 for GA SB and MVPA, and 0.90 for AG SB and 0.94 for AG MVPA. Sensitivity optimised SB and specificity optimised MVPA GA cutpoints of 57 mg and 104 mg, and AG cutpoints of 15 mg and 69 mg were also generated, respectively. Cross-validation analysis revealed moderate agreement for GA and AG SB cutpoints, and fair to substantial agreement for GA and AG MVPA cutpoints, respectively. The resultant cutpoints can classify older adults as engaging in SB or not engaging in MVPA but the sensitivity optimised SB cutpoints should be interpreted with a degree of caution due to their modest cross-validation results.  相似文献   

8.
The ability to compare published group-level estimates of objectively measured moderate-to-vigorous physical activity (MVPA) across studies continues to increase in difficulty. The objective of this study was to develop conversion equations and demonstrate their utility to compare estimates of MVPA derived from the wrist and hip. Three studies of youth (N = 232, 9-12yrs, 50% boys) concurrently wore a hip-worn ActiGraph and a wrist-worn GENEActiv for 7-days. ActiGraph hip count data were reduced using four established cutpoints. Wrist accelerations were reduced using the Hildebrand MVPA 200 mg threshold. Conversion equations were developed on a randomly selected subsample of 132 youth. Equations were cross-validated and absolute error, absolute percent error, and modified Bland-Altman plots were evaluated for conversion accuracy. Across equations R2adj was 0.51–0.56 with individual-level absolute error in minutes ranging from 7 (wrist-to-hip Puyau) to 14.5 minutes (wrist-to-hip Freedson 3MET) and absolute percent differences ranging from 13.9%-24.5%. Group-level cross-validation to convert hip-to-wrist MVPA resulted in average absolute percent errors ranging from 3.1%-4.9%. Conversion of wrist-to-hip MVPA resulted in average absolute percent errors ranging from 3.0%-10.0%. We recommend the use of these equations to compare published estimates of MVPA between the wear-site cut-point combinations presented.  相似文献   

9.
This study examines the validity of the SenseWear Armband in different temperatures using the old (SenseWear v2.2) and newest version of the algorithm (SenseWear v5.2) against indirect calorimetry (IC). Thirty-nine male and female students (21.1 ± 1.41 years) completed an exercise trial in 19°C, 26°C and 33°C consisting of 5 min standing followed by alternating walking/running at 35% and 65% of their maximal oxygen uptake. The accuracy of the algorithms was evaluated by comparing estimated energy expenditure (EE) to IC using a mixed-model design. No difference was reported in EE between the different temperatures for IC. Both algorithms estimated EE significantly higher when exercising at high intensity in 33°C compared to 19°C. Compared to IC, SenseWear v2.2 accurately estimated EE during standing and light intensity exercise but underestimated EE when exercising in a hot environment and at high intensity. SenseWear v5.2 showed a difference when exercising at high intensity in thermoneutral and warm conditions. The new algorithm improved EE estimation in hot environments and at high intensity compared to the old version. However, given the inherent inaccuracy of the EE estimates of SenseWear, greater weight should be given to direct monitor outputs rather than the ability of a monitor to estimate EE precisely.  相似文献   

10.
This study examined the validity of current Actical activity energy expenditure (AEE) equations and intensity cut-points in preschoolers using AEE and direct observation as criterion measures. Forty 4–6-year-olds (5.3 ± 1.0 years) completed a ~150-min room calorimeter protocol involving age-appropriate sedentary behaviours (SBs), light intensity physical activities (LPAs) and moderate-to-vigorous intensity physical activities (MVPAs). AEE and/or physical activity intensity were calculated using Actical equations and cut-points by Adolph, Evenson, Pfeiffer and Puyau. Predictive validity was examined using paired sample t-tests. Classification accuracy was evaluated using weighted kappas, sensitivity, specificity and area under the receiver operating characteristic curve. The Pfeiffer equation significantly overestimated AEE during SB and underestimated AEE during LPA (P < 0.0125 for both). There was no significant difference between measured and predicted AEEs during MVPA. The Adolph cut-point showed significantly higher accuracy for classifying SB, LPA and MVPA than all others. The available Actical equation does not provide accurate estimates of AEE across all intensities in preschoolers. However, the Pfeiffer equation performed reasonably well for MVPA. Using cut-points of ≤6 counts · 15 s?1, 7–286 counts · 15 s?1 and ≥ 287 counts · 15 s?1 when classifying SB, LPA and MVPA, respectively, is recommended.  相似文献   

11.
The purpose of the study is to analyse how the standard of resting metabolic rate (RMR) affects estimation of the metabolic equivalent of task (MET) using an accelerometer. In order to investigate the effect on estimation according to intensity of activity, comparisons were conducted between the 3.5 ml O2 · kg?1 · min?1 and individually measured resting VO2 as the standard of 1 MET. MET was estimated by linear regression equations that were derived through five-fold cross-validation using 2 types of MET values and accelerations; the accuracy of estimation was analysed through cross-validation, Bland and Altman plot, and one-way ANOVA test. There were no significant differences in the RMS error after cross-validation. However, the individual RMR-based estimations had as many as 0.5 METs of mean difference in modified Bland and Altman plots than RMR of 3.5 ml O2 · kg?1 · min?1. Finally, the results of an ANOVA test indicated that the individual RMR-based estimations had less significant differences between the reference and estimated values at each intensity of activity. In conclusion, the RMR standard is a factor that affects accurate estimation of METs by acceleration; therefore, RMR requires individual specification when it is used for estimation of METs using an accelerometer.  相似文献   

12.
This study aimed to validate the Sedentary Sphere posture classification method from wrist-worn accelerometers in children. Twenty-seven 9–10-year-old children wore ActiGraph GT9X (AG) and GENEActiv (GA) accelerometers on both wrists, and activPAL on the thigh while completing prescribed activities: five sedentary activities, standing with a phone, walking (criterion for all 7: observation) and 10-min free-living play (criterion: activPAL). In an independent sample, 21 children wore AG and GA accelerometers on the non-dominant wrist and activPAL for two days of free-living. Per cent accuracy, pairwise 95% equivalence tests (±10% equivalence zone) and intra-class correlation coefficients (ICC) analyses were completed. Accuracy was similar, for prescribed activities irrespective of brand (non-dominant wrist: 77–78%; dominant wrist: 79%). Posture estimates were equivalent between wrists within brand (±6%, ICC > 0.81, lower 95% CI ≥ 0.75), between brands worn on the same wrist (±5%, ICC ≥ 0.84, lower 95% CI ≥ 0.80) and between brands worn on opposing wrists (±6%, ICC ≥ 0.78, lower 95% CI ≥ 0.72). Agreement with activPAL during free-living was 77%, but sedentary time was underestimated by 7% (GA) and 10% (AG). The Sedentary Sphere can be used to classify posture from wrist-worn AG and GA accelerometers for group-level estimates in children, but future work is needed to improve the algorithm for better individual-level results.  相似文献   

13.
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   

14.
A study was conducted to assess the validity of the Global Physical Activity Questionnaire (GPAQ) for measuring sedentary behaviour (SB) in the Chilean adult population. About 217 adults (93/124 male/female, 43.8 ± 15.75 years) who were randomly selected during National Health Survey 2009–2010 completed the protocol. The participants wore an ActiGraph GT3X (AG) for 7 consecutive days and then completed the GPAQ (single-item question for measuring time spent sitting in a usual day). Validity was examined using Spearman’s correlation, mean bias and limits of agreement (LoA), with AG (vertical axis <100 counts · min?1) as the reference standard for estimates of SB in bouts of 1 (AG1), 5 (AG5) and 10 (AG10) min. Agreement between the GPAQ and AG for classifying data into quartiles and tertiles was assessed with kappa method. The GPAQ showed fair correlation with AG1, AG5 and AG10 (range = 0.23–0.26), with large mean biases (range = ?293.9, ?76.12 min · day?1). Agreement between the GPAQ and AG1, AG5 and AG10 was poor for categorising time spent in SB into tertiles and quartiles. The single question from the GPAQ has shown fair validity for measuring SB and poor ability for correctly classifying individuals into tertiles or quartiles of SB in a Chilean population.  相似文献   

15.
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   

16.
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   

17.
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   

18.
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   

19.
The purpose of this study was to examine the factorial invariance of the Abbreviated Neighborhood Environment Walkability Scale (NEWS-A) across subgroups based on demographic, health-related, behavioral, and environmental characteristics among Nurses’ Health Study participants (N = 2,919; age M = 73.0, SD = 6.9 years) living in California, Massachusetts, and Pennsylvania. A series of multigroup confirmatory factor analyses were conducted to evaluate increasingly restrictive hypotheses of factorial invariance. Factorial invariance was supported across age, walking limitations, and neighborhood walking. Only partial scalar invariance was supported across state residence and neighborhood population density. This evidence provides support for using the NEWS-A with older women of different ages, who have different degrees of walking limitations, and who engage in different amounts of neighborhood walking. Partial scalar invariance suggests that researchers should be cautious when using the NEWS-A to compare older adults living in different states and neighborhoods with different levels of population density.  相似文献   

20.
Objective: To examine children’s energy expenditure (EE) during object projection skill performance at three intensity intervals. Methods: Children’s (42, Mage = 8.1) average metabolic equivalents of task (METs) were calculated using a COSMED K4b2 while they repeatedly performed blocks of kicking, throwing (overhand), and striking (two-handed) during 6, 12, and 30-s interval conditions. A repeated-measures analysis of covariance examined differences in METs while controlling for skill level. Results: Data indicated a main effect for interval condition (df = 2, 123, F = 94.36, p <.001, η2 = .605). Post hoc t-tests demonstrated decreasing performance interval times yielded progressively higher METs (p <.001) across the three conditions (30s = 4.5±0.8 METs, 12s = 6.3±1.3, 6s = 8.3±1.6). There also was a main effect for sex (df = 1,120, F = 52.28, p <.001 η2 = .305). Boys demonstrated higher METs at each performance interval (p <.001). Conclusion: Skill practice with a maximum of one trial every 30s resulted in the equivalent of at least moderate physical activity (>4.0 METs) and intervals of 6s demonstrated vigorous physical activity (>7.0 METs). Practicing/performing object projection skills, even at intervals that allow for adequate instruction and feedback (i.e., 1 trial/30s), promotes MVPA in children.  相似文献   

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