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.     

Comparing the standards of one metabolic equivalent of task in accurately estimating physical activity energy expenditure based on acceleration

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.     

A low-cost method for estimating energy expenditure during soccer refereeing

This study aimed to apply a validated bioenergetics model of sprint running to recordings obtained from commercial basic high-sensitivity global positioning system receivers to estimate energy expenditure and physical activity variables during soccer refereeing. We studied five Italian fifth division referees during 20 official matches while carrying the receivers. By applying the model to the recorded speed and acceleration data, we calculated energy consumption during activity, mass-normalised total energy consumption, total distance, metabolically equivalent distance and their ratio over the entire match and the two halves. Main results were as follows: (match) energy consumption = 4729 ± 608 kJ, mass normalised total energy consumption = 74 ± 8 kJ · kg^?1, total distance = 13,112 ± 1225 m, metabolically equivalent distance = 13,788 ± 1151 m and metabolically equivalent/total distance = 1.05 ± 0.05. By using a very low-cost device, it is possible to estimate the energy expenditure of soccer refereeing. The provided predicting mass-normalised total energy consumption versus total distance equation can supply information about soccer refereeing energy demand.     

Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data

ABSTRACT

Detection of non-wear periods is an important step in accelerometer data processing. This study evaluated five non-wear detection algorithms for wrist accelerometer data and two rules for non-wear detection when non-wear and sleep algorithms are implemented in parallel. Non-wear algorithms were based on the standard deviation (SD), the high-pass filtered acceleration, or tilt angle. Rules for differentiating sleep from non-wear consisted of an override rule in which any overlap between non-wear and sleep was deemed non-wear; and a 75% rule in which non-wear periods were deemed sleep if the duration was < 75% of the sleep period. Non-wear algorithms were evaluated in 47 children who wore an ActiGraph GT3X+ accelerometer during school hours for 5 days. Rules for differentiating sleep from non-wear were evaluated in 15 adults who wore a GeneActiv Original accelerometer continuously for 24 hours. Classification accuracy for the non-wear algorithms ranged between 0.86–0.95, with the SD of the vector magnitude providing the best performance. The override rule misclassified 37.1 minutes of sleep as non-wear, while the 75% rule resulted in no misclassification. Non-wear algorithms based on the SD of the acceleration signal can effectively detect non-wear periods, while application of the 75% rule can effectively differentiate sleep from non-wear when examined concurrently.     

Comparability of accelerometer- and IPAQ-derived physical activity and sedentary time in South Asian women: A cross-sectional study

Abstract

There is limited research documenting objectively measured physical activity (PA) and sedentary time (ST) in South Asian (SA) women, with no published evidence of the validity of self-report methods for assessment of PA/ST in SA. The purpose of this study was to compare accelerometer- and International Physical Activity Questionnaire (IPAQ)-derived PA/ST among SA women in the United Kingdom (UK) via a mixed-methods approach. One hundred and forty SA women wore an accelerometer for seven consecutive days; a sub-sample (n = 50) completed the IPAQ-Short Form (IPAQ-SF) and a brief structured interview. Accelerometer-derived metabolic equivalent (MET) minutes per week (min/wk) moderate-to-vigorous physical activity (MVPA) (mean ± SD) for the full sample was 793.94 (±519.44) and mean accelerometer-derived ST wk was 530.20 (±81.76). IPAQ-SF-derived MVPA (MET min/wk) was 636.80 (±2113.56) and mean ST wk was 315.31 (±266.98). Pearson correlations were not significant between accelerometer- and IPAQ-SF-assessed MVPA (r = ?.119, p = .579) and ST (r = ?.140, p = .229). Major themes synthesised from interviews included inability to recall sitting time and limited general knowledge of real-life examples of MVPA. These results suggest that the IPAQ-SF may not accurately measure PA/ST in the UK SA women. These findings are supported by qualitative evidence indicating several issues with interpretation and recall of PA/ST as assessed via this questionnaire.     

A cross-cultural study of adolescents' physical activity levels in France and Spain

Abstract

The goals of this study were (1) to describe and compare levels of physical activity (PA), assessed by accelerometry, of adolescents in two close Spanish and French cities according to gender and period of the week and (2) to assess, with reference to country and gender, the extent to which international PA guidelines were fulfilled. The PA of 401 adolescents (53.37% females) from France and Spain (55.72% French) aged 14.45±0.67 years was assessed with GT3X accelerometers for seven consecutive days to evaluate their habitual levels of moderate to vigorous physical activity (MVPA). Data collection took place from September to December 2010 in six public and state schools in France and Spain. There were significant differences in MVPA in terms of country, gender and period of the week. Spanish adolescents were more active than French adolescents, boys were more active than girls and MVPA was higher on weekdays than at weekends. French girls showed the lowest level of PA. Only 35.9% of the whole sample met the guidelines for PA in both countries. Governments of relevant countries, especially France, should adopt PA promotion policies targeted at adolescents in order to enhance their compliance with PA guidelines.     

Evaluation of wrist and hip sedentary behaviour and moderate-to-vigorous physical activity raw acceleration cutpoints in older adults

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.     

Assessment of Differing Definitions of Accelerometer Nonwear Time

Abstract

Twelve college and high school varsity male swimmers swam 200 yd. for time once a day for 16 days following the ingestion of a large meal (673 g). Each subject performed under rotating experimental conditions, which involved a post-meal rest interval of ½ hr., 1 hr., 2 hr., or no eating for at least 3 hr. before swimming. A nonsignificant F of .53 was obtained when the data were subjected to a single-factor with repeated measures analysis of variance.

It was concluded that swimming performance time was not affected by the time interval between eating and swimming. No stomach cramps were reported; most cases of stomach nausea occurred in the ½-hr. interval group, and scattered minor physical disturbances occurred under the other conditions.     

An evaluation of energy expenditure estimation by three activity monitors

Abstract

A comparative evaluation of the ability of activity monitors to predict energy expenditure (EE) is necessary to aid in the investigation of the effect of EE on health. The purpose of this study was to validate and compare the RT3, the SWA and the IDEEA at measuring EE in adults and children. Twenty-six adults and 22 children completed a resting metabolic rate (RMR) test and performed four treadmill activities at 3 km.h^?1, 6 km.h^?1, 6 km.h^?1 at a 10% incline, 9 km.h^?1. EE was assessed throughout the protocol by the RT3, the SWA and the IDEEA. Indirect calorimetry (IC) was used as a criterion measure of EE against which each monitor was compared. Mean bias was assessed by subtracting EE from IC from EE from each monitor for each activity. Limit of agreement plots were used to assess the agreement between each monitor and IC. Limits of agreement for resting EE were narrowest for the RT3 for adults and children. Although the IDEEA displayed the smallest mean bias between measures at 3 km.h^?1, 6 km.h^?1 and 9 km.h^?1 in adults and children, the SWA agreed closest with IC at 6 km.h^?1, 6 km.h^?1 at a 10% incline and 9 km.h^?1. Limits of agreement were closest for the SWA at 9 km.h^?1 in adults representing 42% of the overall mean EE. Although the RT3 provided the best estimate of resting EE in adults and children, the SWA provided the most accurate estimate of EE across a range of physical activity intensities.     

Comparison of ActiGraph GT3X+ and Actical accelerometer data in 9–11-year-old Canadian children

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.     

Differences in energy expenditure between high- and low-volume training

Abstract

Several studies have examined energy expenditure in various sports but there is a lack of research on the contribution of exercise and habitual activity during different training periods. This study examined changes in total daily energy expenditure (TDEE) and its components during high- and low-volume training periods. Further, changes in time spent in sedentary, light, moderate and vigorous activity in response to different training volumes were explored. Energy expenditure was measured in 15 male endurance athletes during 2 non-consecutive weeks – 1 week of high volume (>13 hours) training and another week of low volume (<7 hours) training. The SenseWear Pro 3 Armband, individual heart-rate-oxygen consumption regression and indirect calorimetry was used to measure non-exercise activity thermogensis (NEAT), exercise energy expenditure (EEE) and resting metabolic rate, respectively. Time spent at different intensities was assessed using previously established MET cutpoints. TDEE as well as EEE increased significantly with higher training volume, while no difference in NEAT occurred. Further, significantly less time was spent in sedentary activities during the high-volume week. These results suggest that highly trained athletes do not compensate for increased training volume and reduce sedentary activities to allow for more training time.     

Comparison of two Actigraph models for assessing free-living physical activity in Indian adolescents

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.     

Energy Expenditure and Intensity of Active Video Games in Children and Adolescents

Purpose: This study aimed to compare the energy expenditure and intensity of active video games to that of treadmill walking in children and adolescents. Method: Seventy-two boys and girls (aged 8–13 years) were recruited from local public schools. Energy expenditure and heart rate were measured during rest, during 3-km/hr, 4-km/hr, and 5-km/hr walks, and during active games (Adventure, Boxing I, Boxing II, and Dance). During walking and active games, we also assessed physical activity using an accelerometer. Results: The energy expenditure of the active games Adventure, Boxing I, Boxing II, and Dance was similar to that of treadmill walking at 5 km/hr in boys and girls. Heart rate was significantly higher for the game Adventure compared with walking at 3 km/hr, 4 km/hr, and 5 km/hr and the game Dance in both genders. The heart rate of girls during the games Adventure and Dance was significantly higher compared with boys. There was a statistically significant difference (p < .05, with an effect size ranging from 0.40 to 3.54) in the counts·min^?1, measured through accelerometry, between activities. Conclusion: XBOX 360 Kinect games provide energy expenditure and physical activity of moderate intensity for both genders. The use of active video games can be an interesting alternative to increase physical activity levels.     

Evidence for data missing at random in youth physical activity monitoring research

This study examined whether or not activity monitor data collected as part of a typical 7-day physical activity (PA) measurement protocol can be expected to be missing at random. A total of 315 participants (9–18 years) each wore a SenseWear Armband monitor for 7 consecutive days. Participants were classified as “compliant” (86 boys and 124 girls) if they had recorded accelerometer data during 70% or more of the predefined awake time (7 AM–10 PM) on four different days; and “non-compliant” (44 boys and 51 girls) when not meeting these criteria. Linear mixed models were used to examine differences in energy expenditure (EE) levels by compliance across 10 different time periods. The results indicated that non-compliant girls were older (13.4 ± 2.9 vs. 12.2 ± 2.5) and taller (156.8 ± 10.3 vs. 152.8 ± 11.3) than their same gender compliant peers (P < .05). Comparisons of EE rates at segmented portions of the day revealed no differences between compliant and non-compliant groups (P ≥ .05). Differences in EE ranged from ?0.32 kcal · kg^?1 · h^?1 (before school time) to 0.62 kcal · kg^?1 · h^?1 (physical education class) in boys and ?0.39 kcal · kg^?1 · h^?1 (transportation from school) to 0.37 kcal · kg^?1 · hour^?1 (recess) in girls. The results showed that compliant and non-compliant individuals differed in a few demographic characteristics but exhibited similar activity patterns. This suggests that data were considered to be missing at random, but additional work is needed to confirm this observation in a representative sample of children using other types of activity monitors and protocols.     

Short- and long-term reliability of leg extensor power measurement in middle-aged and older adults

Muscular power is important for maintaining physical functioning with aging. Proper quantification of the reliability of muscular power tests is crucial to inform monitoring of individuals and sample size planning for interventional studies. This study evaluated short- and long-term reliability of leg extensor power measurement in 72 adults (age 62.7 ± 8.6 years). Participants completed four repeat trials on the Nottingham leg extensor power rig, with a further trial twelve weeks later. Mean change, typical error, and intraclass correlation coefficients (ICC) were calculated. For short-term reliability, mean change in power output was trivial after two trials (1.2–4.8%). Typical errors were small following four trials in the dominant leg of males (10.9–5.8%), three in the non-dominant leg of males (9.9–6.2%) and the dominant leg of females (10.0–9.6%) and two in the non-dominant leg in females (8.3%). Intraclass correlation coefficients (ICCs) were very high (0.88–0.96). For long-term reliability, mean change remained trivial (1.0–2.5%), typical errors remained small (5.8–8.6%), and ICCs very high (0.94–0.96). The leg extensor power rig is a reliable method for assessing lower body muscular power, both short- and long-term, with only minimal habituation effects.     

Accelerometry to measure physical activity in toddlers: Determination of wear time requirements for a reliable estimate of physical activity

Accelerometry is widely used to evaluate physical activity in toddlers however recommendations regarding wear time are needed to understand physical activity behaviours in this age group. This study aimed to determine the minimum wear time to reliably evaluate physical activity in toddlers. Children from the 3D Birth Cohort (n = 255, 49.8% boys, 2.1 ± 0.2 years) were asked to wear an accelerometer (GT3X+, ActiGraph) for 7 days. Physical activity was expressed in active time (min/day) and counts per minute (CPM). Single day intraclass correlation coefficients (ICCs) were calculated to assess the effect of varying minimal wear time on reliability estimates. The Spearman-Brown formula was used to determine wear time required to achieve reliability levels of 70%, 80% and 90%. For active time, a reliability of 72.1% was achieved with wearing the accelerometer for ≥ 4 days of ≥ 6 h, which comprised 85.9% of the sample. For CPM, ≥ 4 days of ≥ 6 h provided a reliability of 74.7% and comprised 85.9% of the children. Results differed slightly when girls and boys were analysed separately, but restricting analyses to children with a weekend day did not. In summary, a minimum of 4 days with ≥ 6 h of accelerometry data provides a reliable estimate of physical activity in 2-year toddlers.     

Validity of the Actical activity monitor for assessing steps and energy expenditure during walking

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.     

The use of accelerometry in adolescents and its implementation with non-wear time activity diaries in free-living conditions

Abstract

The aim of this study was to evaluate the use of a non-wearing time activity diary (hereafter non-wear activity diary) when using accelerometry in adolescents to provide insight into their physical activity levels. In total, 213 Belgian adolescents (89 boys, 124 girls) were eligible for this study. Adolescents wore an accelerometer for seven consecutive days and kept a non-wear activity diary. On the last day, they completed the International Physical Activity Questionnaire for Adolescents. The differences between the accelerometer data with and without use of the non-wear activity diary were significant for all physical activity intensities according to the Wilcoxon signed rank test. Bland-Altman plots showed that with more time spent in any physical activity intensity, the difference between including and not including the non-wear activity diary increased. The correlation coefficient between the International Physical Activity Questionnaire for Adolescents and the accelerometer data increased when the non-wear activity diary was included. Differences in the percentage of adolescents reaching the physical activity recommendations between the accelerometer data only and the accelerometer with the non-wear activity diary were significant. We conclude that if the non-wear activity diary data are not included, some adolescents could be misclassified as not being physically active according to the physical activity recommendations. It is therefore recommended to use a non-wear activity diary for gaining insight into the physical activity levels of individuals.