scholarly journals Evaluations of Actiheart, IDEEA® and RT3 monitors for estimating activity energy expenditure in free-living women

2013 ◽  
Vol 2 ◽  
Author(s):  
Marie Löf ◽  
Hanna Henriksson ◽  
Elisabet Forsum
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Living Conditions ◽  
Reproductive Age ◽  
Women Of Reproductive Age ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Further Development ◽  
Activity Energy ◽  
Free Living Conditions

AbstractActivity energy expenditure (AEE) during free-living conditions can be assessed using devices based on different principles. To make proper comparisons of different devices' capacities to assess AEE, they should be evaluated in the same population. Thus, in the present study we evaluated, in the same group of subjects, the ability of three devices to assess AEE in groups and individuals during free-living conditions. In twenty women, AEE was assessed using RT3 (three-axial accelerometry) (AEERT3), Actiheart (a combination of heart rate and accelerometry) (AEEActi) and IDEEA (a multi-accelerometer system) (AEEIDEEA). Reference AEE (AEEref) was assessed using the doubly labelled water method and indirect calorimetry. Average AEEActi was 5760 kJ per 24 h and not significantly different from AEEref (5020 kJ per 24 h). On average, AEERT3 and AEEIDEEA were 2010 and 1750 kJ per 24 h lower than AEEref, respectively (P < 0·001). The limits of agreement (± 2 sd) were 2940 (Actiheart), 1820 (RT3) and 2650 (IDEEA) kJ per 24 h. The variance for AEERT3 was lower than for AEEActi (P = 0·006). The RT3 classified 60 % of the women in the correct activity category while the corresponding value for IDEEA and Actiheart was 30 %. In conclusion, the Actiheart may be useful for groups and the RT3 for individuals while the IDEEA requires further development. The results are likely to be relevant for a large proportion of Western women of reproductive age and demonstrate that the procedure selected to assess physical activity can greatly influence the possibilities to uncover important aspects regarding interactions between physical activity, diet and health.

Validation of the RT3 Accelerometer for Measuring Physical Activity of Children in Simulated Free-Living Conditions

2008 ◽  
Vol 20 (2) ◽  
pp. 181-197 ◽  
Author(s):  
David Xiaoqian Sun ◽  
Gordon Schmidt ◽  
Sock Miang Teo-Koh
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Oxygen Uptake ◽  
Metabolic Cost ◽  
Physical Activities ◽  
Living Conditions ◽  
Free Living ◽  
Outdoor Test ◽  
Activity Energy ◽  
Free Living Conditions

This is a validation study of the RT3 accelerometer for measuring physical activities of children in simulated free-living conditions. Twenty-five children age 12–14 years completed indoor testing, and 18 of them completed outdoor testing. Activity counts from the RT3 accelerometer estimated activity energy expenditure (AEE) and the Cosmed K4b2 analyzer measured oxygen uptake. Correlations were found between activity counts and metabolic cost (r = .95, p < .001), metabolic cost and RT3 estimated AEE (r = .96, p < .001) in the indoor test, activity counts and RT3 estimated AEE (r = .97, p < .001) in the outdoor test, and activity counts and metabolic cost when all activities were combined (r = .77, p < .001). Results indicate that the RT3 accelerometer might be used to provide acceptable estimates of free-living physical activity in children.

scholarly journals Prior automatic posture and activity identification improves physical activity energy expenditure prediction from hip-worn triaxial accelerometry

2018 ◽  
Vol 124 (3) ◽  
pp. 780-790 ◽  
Author(s):  
M. Garnotel ◽  
T. Bastian ◽  
H. M. Romero-Ugalde ◽  
A. Maire ◽  
J. Dugas ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Specific Model ◽  
Living Conditions ◽  
Physical Activity Energy Expenditure ◽  
Free Living ◽  
Automatic Activity ◽  
Activity Energy ◽  
Free Living Conditions ◽  
Variance Explained

Accelerometry is increasingly used to quantify physical activity (PA) and related energy expenditure (EE). Linear regression models designed to derive PAEE from accelerometry-counts have shown their limits, mostly due to the lack of consideration of the nature of activities performed. Here we tested whether a model coupling an automatic activity/posture recognition (AAR) algorithm with an activity-specific count-based model, developed in 61 subjects in laboratory conditions, improved PAEE and total EE (TEE) predictions from a hip-worn triaxial-accelerometer (ActigraphGT3X+) in free-living conditions. Data from two independent subject groups of varying body mass index and age were considered: 20 subjects engaged in a 3-h urban-circuit, with activity-by-activity reference PAEE from combined heart-rate and accelerometry monitoring (Actiheart); and 56 subjects involved in a 14-day trial, with PAEE and TEE measured using the doubly-labeled water method. PAEE was estimated from accelerometry using the activity-specific model coupled to the AAR algorithm (AAR model), a simple linear model (SLM), and equations provided by the companion-software of used activity-devices (Freedson and Actiheart models). AAR-model predictions were in closer agreement with selected references than those from other count-based models, both for PAEE during the urban-circuit (RMSE = 6.19 vs 7.90 for SLM and 9.62 kJ/min for Freedson) and for EE over the 14-day trial, reaching Actiheart performances in the latter (PAEE: RMSE = 0.93 vs. 1.53 for SLM, 1.43 for Freedson, 0.91 MJ/day for Actiheart; TEE: RMSE = 1.05 vs. 1.57 for SLM, 1.70 for Freedson, 0.95 MJ/day for Actiheart). Overall, the AAR model resulted in a 43% increase of daily PAEE variance explained by accelerometry predictions.NEW & NOTEWORTHY Although triaxial accelerometry is widely used in free-living conditions to assess the impact of physical activity energy expenditure (PAEE) on health, its precision and accuracy are often debated. Here we developed and validated an activity-specific model which, coupled with an automatic activity-recognition algorithm, improved the variance explained by the predictions from accelerometry counts by 43% of daily PAEE compared with models relying on a simple relationship between accelerometry counts and EE.

The Actiheart in Adolescents: A Doubly Labelled Water Validation

2012 ◽  
Vol 24 (4) ◽  
pp. 589-602 ◽  
Author(s):  
Nerissa Campbell ◽  
Harry Prapavessis ◽  
Casey Gray ◽  
Erin McGowan ◽  
Elaine Rush ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Equation Modeling ◽  
Physical Activity Energy Expenditure ◽  
Limits Of Agreement ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Future Work ◽  
Activity Energy

Background/Objective: This study investigated the validity of the Actiheart device for estimating free-living physical activity energy expenditure (PAEE) in adolescents. Subjects/Methods: Total energy expenditure (TEE) was measured in eighteen Canadian adolescents, aged 15–18 years, by DLW. Physical activity energy expenditure was calculated as 0.9 X TEE minus resting energy expenditure, assuming 10% for the thermic effect of feeding. Participants wore the chest mounted Actiheart device which records simultaneously minute-by-minute acceleration (ACC) and heart rate (HR). Using both children and adult branched equation modeling, derived from laboratory-based activity, PAEE was estimated from the ACC and HR data. Linear regression analyses examined the association between PAEE derived from the Actiheart and DLW method where DLW PAEE served as the dependent variable. Measurement of agreement between the two methods was analyzed using the Bland-Altman procedure. Results: A nonsignificant association was found between the children derived Actiheart and DLW PAEE values (R = .23, R2 = .05, p = .36); whereas a significant association was found between the adult derived Actiheart and DLW PAEE values (R = .53, R2 = .29, p < .05). Both the children and adult equation models lead to overestimations of PAEE by the Actiheart compared with the DLW method, by a mean difference of 31.42 kcal·kg−·d−1 (95% limits of agreement: −45.70 to −17.15 kcal·kg−1·d−1 and 9.80 kcal·kg−1·d−1 (95% limits of agreement: −21.22-1.72 kcal·kg−1·d−1), respectively. Conclusion: There is relatively poor measurement of agreement between the Actiheart and DLW for assessing free-living PAEE in adolescents. Future work should develop group based branched equation models specifically for adolescents to improve the utility of the device in this population.

scholarly journals The eMouveRecherche application competes with research devices to evaluate energy expenditure, physical activity and still time in free-living conditions

2017 ◽  
Vol 69 ◽  
pp. 128-134 ◽  
Author(s):  
Romain Guidoux ◽  
Martine Duclos ◽  
Gérard Fleury ◽  
Philippe Lacomme ◽  
Nicolas Lamaudière ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Living Conditions ◽  
Free Living ◽  
Free Living Conditions

A moderate dose of caffeine ingestion does not change energy expenditure but decreases sleep time in physically active males: a double-blind randomized controlled trial

2013 ◽  
Vol 38 (1) ◽  
pp. 49-56 ◽  
Author(s):  
Pedro B. Júdice ◽  
João P. Magalhães ◽  
Diana A. Santos ◽  
Catarina N. Matias ◽  
Ana Isabel Carita ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Sleep Time ◽  
Living Conditions ◽  
Acute Effects ◽  
Moderate Dose ◽  
Free Living ◽  
Double Blind ◽  
Physically Active ◽  
Free Living Conditions

Research on the effect of caffeine on energy expenditure (EE), physical activity (PA), and total sleep time (TST) during free-living conditions using objective measures is scarce. We aimed to determine the impact of a moderate dose of caffeine on TST, resting EE (REE), physical activity EE (PAEE), total EE (TEE), and daily time spent in sedentary, light, moderate, and vigorous intensity activities in a 4-day period and the acute effects on heart rate (HR) and EE in physically active males. Using a double-blind crossover trial (ClinicalTrials.gov ID: NCT01477294) with two conditions (4 days each with 3-day washout) randomly ordered as caffeine (5 mg/kg of body mass/day) and placebo (maltodextrin) administered twice per day (2.5 mg/kg), 30 nonsmoker males, low-caffeine users (<100 mg/day), aged 20–39, were followed. Body composition was assessed by dual-energy X-ray absorptiometry. PA was assessed by accelerometry, while a combined HR and movement sensor estimated EE and HR on the second hour after the first administration dose. REE was assessed by indirect calorimetry, and PAEE was calculated as [TEE − (REE + 0.1TEE)]. TST and daily food records were obtained. Repeated measures ANOVA and ANCOVA were used. After a 4-day period, adjusting for fat-free mass, PAEE, and REE, TST was reduced (p = 0.022) under caffeine intake, while no differences were found between conditions for REE, PAEE, TEE, and PA patterns. Also, no acute effects on HR and EE were found between conditions. Though a large individual variability was observed, our findings revealed no acute or long-term effects of caffeine on EE and PA but decreased TST during free-living conditions in healthy males.

scholarly journals Estimating energy expenditure from wrist and thigh accelerometry in free-living adults: a doubly labelled water study

2018 ◽  
Author(s):  
Tom White ◽  
Kate Westgate ◽  
Stefanie Hollidge ◽  
Michelle Venables ◽  
Patrick Olivier ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Mean Squared Error ◽  
Pearson Correlation ◽  
Population Level ◽  
Living Conditions ◽  
Estimation Model ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Highly Correlated ◽  
Free Living Conditions

AbstractBackgroundMany large studies have implemented wrist or thigh accelerometry to capture physical activity, but the accuracy of these measurements to infer Activity Energy Expenditure (AEE) and consequently Total Energy Expenditure (TEE) has not been demonstrated. The purpose of this study was to assess the validity of acceleration intensity at wrist and thigh sites as estimates of AEE and TEE under free-living conditions using a gold-standard criterion.MethodsMeasurements for 193 UK adults (105 men, 88 women, aged 40-66 years, BMI 20.4-36.6 kg·m-2) were collected with triaxial accelerometers worn on the dominant wrist, non-dominant wrist and thigh in free-living conditions for 9-14 days. In a subsample (50 men, 50 women) TEE was simultaneously assessed with doubly labelled water (DLW). AEE was estimated from non-dominant wrist using an established estimation model, and novel models were derived for dominant wrist and thigh in the non-DLW subsample. Agreement with both AEE and TEE from DLW was evaluated by mean bias, Root Mean Squared Error (RMSE) and Pearson correlation.ResultsMean TEE and AEE derived from DLW was 11.6 (2.3) MJ·day-1 and 49.8 (16.3) kJ·day-1·kg-1. Dominant and non-dominant wrist acceleration were highly correlated in free-living (r=0.93), but less so with thigh (r=0.73 and 0.66, respectively). Estimates of AEE were 48.6 (11.8) kJ·day-1·kg-1 from dominant wrist, 48.6 (12.3) from non-dominant wrist, and 46.0 (10.1) from thigh; these agreed strongly with AEE (RMSE ~12.2 kJ·day-1·kg-1, r ~0.71) with small mean biases at the population level (~6%). Only the thigh estimate bias was statistically significantly different from the criterion. When combining these AEE estimates with estimated REE, agreement was stronger with the criterion (RMSE ~1.0 MJ·day-1, r ~0.90). Conclusions: In UK adults, acceleration measured at either wrist or thigh can be used to estimate population levels of AEE and TEE in free-living conditions with high precision.

scholarly journals How Does a Hilly Urban Environment Influence Daily Physical Activity in Obese Individuals?

2013 ◽  
Vol 10 (5) ◽  
pp. 617-625 ◽  
Author(s):  
Dac Minh Tuan Nguyen ◽  
Virgile Lecoultre ◽  
Andrew P. Hills ◽  
Yves Schutz
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Urban Environment ◽  
Exercise Intensity ◽  
Walking Speed ◽  
Living Conditions ◽  
Daily Physical Activity ◽  
Outdoor Environment ◽  
Free Living ◽  
Free Living Conditions

Background:Increases in physical activity (PA) are promoted by walking in an outdoor environment. Along with walking speed, slope is a major determinant of exercise intensity, and energy expenditure. The hypothesis was that in free-living conditions, a hilly environment diminishes PA to a greater extent in obese (OB) when compared with control (CO) individuals.Methods:To assess PA types and patterns, 28 CO (22 ± 2 kg/m2) and 14 OB (33 ± 4 kg/m2) individuals wore during an entire day 2 accelerometers and 1 GPS device, around respectively their waist, ankle and shoulder. They performed their usual PA and were asked to walk an additional 60 min per day.Results:The duration of inactivity and activity with OB individuals tended to be, respectively, higher and lower than that of CO individuals (P = .06). Both groups spent less time walking uphill/downhill than on the level (20%, 19%, vs. 61% of total walking duration, respectively, P < .001). However OB individuals spent less time walking uphill/downhill per day than CO (25 ± 15 and 38 ± 15 min/d, respectively, P < 0.05) and covered a shorter distance per day (3.8 km vs 5.2 km, P < 0.01).Conclusions:BMI and outdoor topography should also be considered when prescribing extra walking in free-living conditions.

scholarly journals Evaluation of Actiheart and a 7 d activity diary for estimating free-living total and activity energy expenditure using criterion methods in 1·5- and 3-year-old children

2014 ◽  
Vol 111 (10) ◽  
pp. 1830-1840 ◽  
Author(s):  
Hanna Henriksson ◽  
Elisabet Forsum ◽  
Marie Löf
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Fat Mass ◽  
Fat Free Mass ◽  
Activity Levels ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Metabolic Equivalent ◽  
Activity Diary ◽  
Activity Energy

Accurate and easy-to-use methods to assess free-living energy expenditure in response to physical activity in young children are scarce. In the present study, we evaluated the capacity of (1) 4 d recordings obtained using the Actiheart (mean heart rate (mHR) and mean activity counts (mAC)) to provide assessments of total energy expenditure (TEE) and activity energy expenditure (AEE) and (2) a 7 d activity diary to provide assessments of physical activity levels (PAL) using three sets of metabolic equivalent (MET) values (PALTorun, PALAdolphand PALAinsworth) in forty-four and thirty-one healthy Swedish children aged 1·5 and 3 years, respectively. Reference TEE, PALrefand AEE were measured using criterion methods, i.e. the doubly labelled water method and indirect calorimetry. At 1·5 years of age, mHR explained 8 % (P= 0·006) of the variation in TEE above that explained by fat mass and fat-free mass. At 3 years of age, mHR and mAC explained 8 (P= 0·004) and 6 (P= 0·03) % of the variation in TEE and AEE, respectively, above that explained by fat mass and fat-free mass. At 1·5 and 3 years of age, average PALAinsworthvalues were 1·44 and 1·59, respectively, and not significantly different from PALrefvalues (1·39 and 1·61, respectively). By contrast, average PALTorun(1·5 and 3 years) and PALAdolph(3 years) values were lower (P< 0·05) than the corresponding PALrefvalues. In conclusion, at both ages, Actiheart recordings explained a small but significant fraction of free-living energy expenditure above that explained by body composition variables, and our activity diary produced mean PAL values in agreement with reference values when using MET values published by Ainsworth.

scholarly journals Comparison of Energy Expenditure Assessed Using Wrist- and Hip-Worn ActiGraph GT3X in Free-Living Conditions in Young and Older Adults

2021 ◽  
Vol 8 ◽  
Author(s):  
Amine Guediri ◽  
Louise Robin ◽  
Justine Lacroix ◽  
Timothee Aubourg ◽  
Nicolas Vuillerme ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Energy Expenditure ◽  
Error Rate ◽  
Absolute Error ◽  
Living Conditions ◽  
Free Living ◽  
Activity Trackers ◽  
The Absolute ◽  
Free Living Conditions

The World Health Organization has presented their recommendations for energy expenditure to improve public health. Activity trackers do represent a modern solution for measuring physical activity, particularly in terms of steps/day and energy expended in physical activity (active energy expenditure). According to the manufacturer's instructions, these activity trackers can be placed on different body locations, mostly at the wrist and the hip, in an undifferentiated manner. The objective of this study was to compare the absolute error rate of active energy expenditure measured by a wrist-worn and hip-worn ActiGraph GT3X+ over a 24-h period in free-living conditions in young and older adults. Over the period of a 24-h period, 22 young adults and 22 older adults were asked to wear two ActiGraph GT3X+ at two different body locations recommended by the manufacturer, namely one around the wrist and one above the hip. Freedson algorithm was applied for data analysis. For both groups, the absolute error rate tended to decrease from 1,252 to 43% for older adults and from 408 to 46% for young participants with higher energy expenditure. Interestingly, for both young and older adults, the wrist-worn ActiGraph provided a significantly higher values of active energy expenditure (943 ± 264 cal/min) than the hip-worn (288 ± 181 cal/min). Taken together, these results suggest that caution is needed when using active energy expenditure as an activity tracker-based metric to quantify physical activity.

Sign in / Sign up

Export Citation Format

Share Document