An investigation of a novel three-dimensional activity monitor to predict free-living energy expenditure

Abstract

The aim of this study was to assess the capability of the 3dNX? accelerometer to predict energy expenditure in two separate, free-living cohorts. Twenty-three adolescents and 14 young adults took a single dose of doubly labelled water and wore a 3dNX? activity monitor during waking hours for a 10-day period while carrying out their normal routines. Multiple linear regression with backward elimination was used to establish the strength of the associations between various indices of energy expenditure, physical activity counts, and anthropometric variables. 3dNX? output accounted for 27% and 35% of the variance in the total energy expenditure of the adolescent and young adult cohort, respectively. The explained variance increased to 78%, with a standard error of estimate of 7%, when 3dNX? output was combined with body composition variables. The 3dNX? accelerometer can be used to predict free-living daily energy expenditure with a standard error of estimate of 1.65 MJ in adolescents and 1.52 MJ in young adults. The inclusion of anthropometric variables reduces the error to approximately 1 MJ. Although it remains to cross-validate these models in other populations, early indications suggest that the 3dNX? provides a useful method of predicting energy expenditure in free-living individuals.     

Estimating Energy Expenditure With the RT3 Triaxial Accelerometer

The RT3 is a relatively new triaxial accelerometer that has replaced the TriTrac. The aim of this study was to validate the RT3 against doubly labeled water (DLW) in a free-living, mixed weight sample of adults. Total energy expenditure (TEE) was measured over a 15-day period using DLW. Activity-related energy expenditure (AEE) was estimated by subtracting resting energy expenditure and thermic effect of feeding from TEE. The RT3 triaxial accelerometer was worn over 14 consecutive days. TEE and AEE were estimated using the RT3 proprietary equation. Thirty-six adults ages 18–56 years (56% women) with an average weight of 75.9 kg (SD = 14.8) completed all measurements. Compared to DLW, the RT3 underestimated TEE by 539 kJ (4%) and AEE by 485 kJ (15%) on average. The RT3 provided a relatively accurate assessment of free-living activity-related energy expenditure at the group level and generally underestimated total and activity-related energy expenditure compared to DLW.     

Comparing the Validity and Output of the GT1M and GT3X Accelerometer in 5- to 9-Year-Old Children

The purpose of this study was to compare the validity and output of the biaxial ActiGraph GT1M and the triaxial GT3X (ActiGraph, LLC, Pensacola, FL, USA) accelerometer in 5- to 9-year-old children. Thirty-two children wore the two monitors while their energy expenditure was measured with indirect calorimetry. They performed four locomotor and four play activities in an exercise laboratory and were further measured during 12 minutes of a sports lesson. Validity evidence in relation to indirect calorimetry was examined with linear regression equations applied to the laboratory data. During the sports lessons predicted energy expenditure according to the regression equations was compared to measured energy expenditure with the Wilcoxon-signed rank test and the Spearman correlation. To compare the output, agreement between counts of the two monitors during the laboratory activities was assessed with Bland-Altman plots. The evidence of validity was similar for both monitors. Agreement between the output of the two monitors was good for vertical counts (mean bias =??14 ± 22 counts) but not for horizontal counts (?17 ± 32 counts). The current results indicate that the two accelerometer models are able to estimate energy expenditure of a range of physical activities equally well in young children. However, they show output differences for movement in the horizontal direction.     

Assessment of energy expenditure in children using the RT3 accelerometer

The aim of this study was to evaluate the utility of the RT3 accelerometer in young children, compare its accuracy with heart rate monitoring, and develop an equation to predict energy expenditure from RT3 output. Forty-two volunteers (mean age 12.2 years, s = 1.1) exercised at two horizontal and graded walking speeds (4 and 6 km.h(-1), 0% grade and 6% grade), and one horizontal running speed (8 km.h(-1), 0% grade), on a treadmill. Energy expenditure and oxygen consumption (VO2) served as the criterion measures. Comparison of RT3 estimates (counts and energy expenditure) demonstrated significant differences at 4, 6, and 8 km.h(-1) on level ground (P < 0.01), while no significant differences were noted between horizontal and graded walking at 4 and 6 km.h(-1). Correlation and regression analyses indicated no advantage of vector magnitude over the vertical plane (X) alone. A strong relationship between RT3 estimates and indirect calorimetry across all speeds was obtained (r = 0.633-0.850, P < 0.01). A child-specific prediction equation (adjusted R2 = 0.753) was derived and cross-validated that offered a valid energy expenditure estimate for walking/running activities. Despite recognized limitations, the RT3 may be a useful tool for the assessment of children's physical activity during walking and running.     

Validation of Accelerometer-Based Energy Expenditure Prediction Models in Structured and Simulated Free-Living Settings

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.     

Classification of Physical Activity Cut-Points and the Estimation of Energy Expenditure During Walking Using the GT3X+ Accelerometer in Overweight and Obese Adults

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.     

Walking for health in pregnancy: assessment by indirect calorimetry and accelerometry

The purpose of this study was to examine RT3 accelerometer activity counts and activity energy expenditure of 36 pregnant women at 20 and 32 weeks' gestation during treadmill walking and free-living conditions. During treadmill walking, oxygen consumption was collected, and activity energy expenditure was estimated for a 30-min walk at a self-selected walking pace. The number of min it would take a pregnant woman to meet exercise recommendations (i.e., kcal/week) were calculated. Preliminary activity count cut points at a self-selected walking pace were then estimated and applied in interpreting free-living data. For the treadmill walking condition, the self-selected walking pace significantly decreased from 20 to 32 weeks' gestation. Additionally, few women (< 12% each day) met physical activity guidelines in the free-living condition. Encouraging pregnant women to walk for 30-40 min per day at a self-selected walking pace may be an appropriate public health recommendation.     

Validation of a wireless accelerometer network for energy expenditure measurement

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.     

Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort

Abstract

This study developed a multivariate model to predict free-living energy expenditure (EE) in independent military cohorts. Two hundred and eighty-eight individuals (20.6 ± 3.9 years, 67.9 ± 12.0 kg, 1.71 ± 0.10 m) from 10 cohorts wore accelerometers during observation periods of 7 or 10 days. Accelerometer counts (PAC) were recorded at 1-minute epochs. Total energy expenditure (TEE) and physical activity energy expenditure (PAEE) were derived using the doubly labelled water technique. Data were reduced to n = 155 based on wear-time. Associations between PAC and EE were assessed using allometric modelling. Models were derived using multiple log-linear regression analysis and gender differences assessed using analysis of covariance. In all models PAC, height and body mass were related to TEE (P < 0.01). For models predicting TEE (r ² = 0.65, SE = 462 kcal · d^?1 (13.0%)), PAC explained 4% of the variance. For models predicting PAEE (r ² = 0.41, SE = 490 kcal · d^?1 (32.0%)), PAC accounted for 6% of the variance. Accelerometry increases the accuracy of EE estimation in military populations. However, the unique nature of military life means accurate prediction of individual free-living EE is highly dependent on anthropometric measurements.     

Validierung von neun Bewegungssensoren bei Kindern und jungen Erwachsenen

The purpose of this study was to determine the accuracy of one accelerometer and eight pedometers in schoolchildren and young adults under controlled experimental conditions and under free-living conditions over a 24-h period. The most accurate results under controlled conditions were obtained with a piezoelectric pedometer. For this device absolute deviations (median) ranged between 0.2 and 1.0% for children and between 0.2 and 1.4% for young adults. Absolute deviations for the accelerometer were 0.8–3.1% for children and 0.6–3.2% for adults. Motion sensors were more accurate with increasing walking speed. For several pedometers the absolute deviation exceeded 50% in tests with schoolchildren. These differing results illustrate that step counts from different motion sensors cannot be compared directly. Therefore, the validity and reliability of activity monitors should be examined carefully before being used in scientific research.     

Assessment of energy expenditure in children using the RT3 accelerometer

Abstract

The aim of this study was to evaluate the utility of the RT3 accelerometer in young children, compare its accuracy with heart rate monitoring, and develop an equation to predict energy expenditure from RT3 output. Forty-two volunteers (mean age 12.2 years, s = 1.1) exercised at two horizontal and graded walking speeds (4 and 6 km · h^?1, 0% grade and 6% grade), and one horizontal running speed (8 km · h^?1, 0% grade), on a treadmill. Energy expenditure and oxygen consumption ([Vdot]O₂) served as the criterion measures. Comparison of RT3 estimates (counts and energy expenditure) demonstrated significant differences at 4, 6, and 8 km · h^?1 on level ground (P < 0.01), while no significant differences were noted between horizontal and graded walking at 4 and 6 km · h^?1. Correlation and regression analyses indicated no advantage of vector magnitude over the vertical plane (X) alone. A strong relationship between RT3 estimates and indirect calorimetry across all speeds was obtained (r = 0.633–0.850, P < 0.01). A child-specific prediction equation (adjusted R ² = 0.753) was derived and cross-validated that offered a valid energy expenditure estimate for walking/running activities. Despite recognized limitations, the RT3 may be a useful tool for the assessment of children's physical activity during walking and running.     

Predicting the throwing velocity of the ball in handball with anthropometric variables and isotonic tests

The aims of this study were to (1) investigate the influence of general anthropometric variables, handball-specific anthropometric variables, and upper-limb power and strength on ball-throwing velocity in a standing position (ν(ball)), and (2) predict this velocity using multiple regression methods. Forty-two skilled male handball players (age 21.0?±?3.0 years; height?=?1.81?±?0.07?m; body mass?=?78.3?±?11.3?kg) participated in the study. We measured general anthropometric variables (height, body mass, lean mass, body mass index) and handball-specific anthropometric parameters (hand size, arm span). Upper-limb dynamic strength was assessed using a medicine ball (2?kg) throwing test, and power using a one-repetition maximum bench-press test. All the variables studied were correlated with ball velocity. Medicine ball throwing performance was the best predictor (r?=?0.80). General anthropometric variables were better predictors (r?=?0.55-0.70) than handball-specific anthropometric variables (r?=?0.35-0.51). The best multiple regression model accounted for 74% of the total variance and included body mass, medicine ball throwing performance, and power output in the 20-kg bench press. The equation formulated could help trainers, athletes, and professionals detect future talent and test athletes' current fitness.     

Concurrent validation of the Actigraph gt3x+, Polar Active accelerometer,Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings

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.     

Head and neck size and neck strength predict linear and rotational acceleration during purposeful soccer heading

There is increasing societal concern about the long-term effects of repeated impacts from soccer heading, but there is little information about ways to reduce head impact severity. The purpose of this study was to identify factors that contribute to head acceleration during soccer heading. One-hundred soccer players completed 12 controlled soccer headers. Peak linear (PLA) and rotational (PRA) accelerations were measured using a triaxial accelerometer and gyroscope. Head acceleration contributing factors were grouped into 3 categories: size (head mass, neck girth), strength (sternocleidomastoid, upper trapezius) and technique [kinematics (trunk, head-to-trunk range-of-motion), sternocleidomastoid and upper trapezius activity]. Multiple regression analyses indicated size variables explained 22.1% of the variance in PLA and 23.3% of the variance in PRA; strength variables explained 13.3% of the variance in PLA and 17.2% of the variance in PRA; technique variables did not significantly predict PLA or PRA. These findings suggest that head and neck size and neck strength predict PLA and PRA. Anthropometric and neck strength measurements should be considered when determining an athlete’s readiness to begin soccer heading.     

Measurement of total energy expenditure by the doubly labelled water method in professional soccer players

To determine the daily energy requirements of professional soccer players during a competitive season, we measured total energy expenditure in seven players (age 22.1 - 1.9 years, height 1.75 - 0.05 m, mass 69.8 - 4.7 kg; mean - s ) using the doubly labelled water method. Energy intake was simultaneously estimated from 7 day self-report dietary records. Mean total energy expenditure and energy intake were 14.8 - 1.7 MJ · day -1 (3532 - 408 kcal· day -1 ) and 13.0 - 2.4 MJ · day -1 (3113 - 581 kcal· day -1 ), respectively. Although there was a significant difference between total energy expenditure and energy intake ( P ? 0.01), there was a strong relationship between the two ( r = 0.893, P ? 0.01). Basal metabolic rate and recommended energy allowance calculated from the Recommended Dietary Allowances for the Japanese were 7.0 - 0.3 MJ ·day -1 (1683 - 81 kcal· day -1 ) and 15.6 - 0.8 MJ · day -1 (3739 - 180 kcal· day -1 ), respectively. A physical activity level (total energy expenditure/ basal metabolic rate) of 2.11 - 0.30 indicated that, during the competitive season, professional soccer players undertake much routine physical activity, similar to that of competitive athletes during moderate training. Energy intake estimated using dietary records was under-reported, suggesting that its calculation from these data does not predict energy expenditure in soccer players.     

Agreement in activity energy expenditure assessed by accelerometer and self-report in adolescents: variation by sex, age, and weight status

The agreement between self-reported and objective estimates of activity energy expenditure was evaluated in adolescents by age, sex, and weight status. Altogether, 403 participants (217 females, 186 males) aged 13-16 years completed a 3-day physical activity diary and wore a GT1M accelerometer on the same days. Partial correlations (controlling for body mass) were used to determine associations between estimated activity energy expenditure (kcal · min(-1)) from the diary and accelerometry. Differences in the magnitude of the correlations were examined using Fisher's r to z transformations. Bland-Altman procedures were used to determine concordance between the self-reported and objective estimates. Partial correlations between assessments of activity energy expenditure (kcal · min(-1)) did not differ significantly by age (13-14 years: r = 0.41; 15-16 years: r = 0.42) or weight status (normal weight: r = 0.42; overweight: r = 0.39). The magnitude of the association was significantly affected by sex (Δr = 0.11; P < 0.05). The agreement was significantly higher in males than in females. The relationship between activity energy expenditure assessed by the objective method and the 3-day diary was moderate (controlling for weight, correlations ranged between 0.33 and 0.44). However, the 3-day diary revealed less agreement in specific group analyses; it markedly underestimated activity energy expenditure in overweight/obese and older adolescents. The assessment of activity energy expenditure is complex and may require a combination of methods.     

Measurement of total energy expenditure by the doubly labelled water method in professional soccer players

To determine the daily energy requirements of professional soccer players during a competitive season, we measured total energy expenditure in seven players (age 22.1+/-1.9 years, height 1.75+/-0.05 m, mass 69.8+/-4.7 kg; mean +/- s) using the doubly labelled water method. Energy intake was simultaneously estimated from 7 day self-report dietary records. Mean total energy expenditure and energy intake were 14.8+/-1.7 MJ x day(-1) (3532+/-408 kcal x day(-1)) and 13.0+/-2.4 MJ x day(-1) (3113+/-581 kcal x day(-1)), respectively. Although there was a significant difference between total energy expenditure and energy intake (P < 0.01), there was a strong relationship between the two (r= 0.893, P< 0.01). Basal metabolic rate and recommended energy allowance calculated from the Recommended Dietary Allowances for the Japanese were 7.0+/-0.3 MJ x day(-1) (1683+/-81 kcal x day(-1)) and 15.6+/-0.8 MJ x day(-1) (3739+/-180 kcal x day(-1)), respectively. A physical activity level (total energy expenditure/ basal metabolic rate) of 2.11+/-0.30 indicated that, during the competitive season, professional soccer players undertake much routine physical activity, similar to that of competitive athletes during moderate training. Energy intake estimated using dietary records was under-reported, suggesting that its calculation from these data does not predict energy expenditure in soccer players.     

IDEEA估算日常行为能耗:以能量代谢舱进行验证

目的探讨智能化可穿戴式能耗分析仪(IDEEA)在南京市成年人夜间行为能耗测定中的准确度。方法共选取受试者120人,佩戴IDEEA进入能量代谢舱进行11h的能耗测试,在此期间完成特定的活动。结果能耗结果进行配对样本T检验,结果显示MC(能量代谢舱)与IDEEA所测得的能耗结果存在显著性差异,但是绝对误差在5%左右。结论 IDEEA测量能耗误差率在可以接受的范围内,它提供了一个估算能耗的替代方法。所提供即时和累积的能耗数据可以用来估测一段时间范围内的人体活动能耗。     

Predicting the throwing velocity of the ball in handball with anthropometric variables and isotonic tests

Abstract

The aims of this study were to (1) investigate the influence of general anthropometric variables, handball-specific anthropometric variables, and upper-limb power and strength on ball-throwing velocity in a standing position (ν_ball), and (2) predict this velocity using multiple regression methods. Forty-two skilled male handball players (age 21.0 ± 3.0 years; height = 1.81 ± 0.07 m; body mass = 78.3 ± 11.3 kg) participated in the study. We measured general anthropometric variables (height, body mass, lean mass, body mass index) and handball-specific anthropometric parameters (hand size, arm span). Upper-limb dynamic strength was assessed using a medicine ball (2 kg) throwing test, and power using a one-repetition maximum bench-press test. All the variables studied were correlated with ball velocity. Medicine ball throwing performance was the best predictor (r = 0.80). General anthropometric variables were better predictors (r = 0.55–0.70) than handball-specific anthropometric variables (r = 0.35–0.51). The best multiple regression model accounted for 74% of the total variance and included body mass, medicine ball throwing performance, and power output in the 20-kg bench press. The equation formulated could help trainers, athletes, and professionals detect future talent and test athletes' current fitness.     

Energy balance and dietary habits of America's Cup sailors

This research, which was conducted with crew members of an America's Cup team, had the following objectives: (a) to assess energy expenditure and intake during training; (b) to evaluate the sailors' diet, and (c) to identify any dietary flaws to determine the appropriate intake of nutrients, correct possible dietary mistakes, and improve their food habits. Energy expenditure was estimated on 15 sailors using direct measurements (oxygen consumption) and a 3-day activity questionnaire. Oxygen consumption was measured on sailors during both on-water America's Cup sailing training and dry-land fitness training. Composition of the diet was estimated using a 3-day food record. Average daily energy expenditure of the sailors ranged from 14.95 to 24.4 MJ, depending on body mass and boat role, with the highest values found in grinders and mastmen. Daily energy intake ranged from 15.7 to 23.3 MJ (from +6% to -18% of energy expenditure). The contributions of carbohydrate, protein, and fat to total energy intake were 43%, 18%, and 39% respectively, values that are not in accord with the recommended guidelines for athletes. Our results show the importance of assessing energy balance and food habits for America's Cup sailors performing different roles. The practical outcome of this study was that the sailors were given dietary advice and prescribed a Mediterranean diet, explained in specific nutrition lectures.