Energy expenditure in children predicted from heart rate and activity calibrated against respiration calorimetry

1998 ◽  
Vol 275 (1) ◽  
pp. E12-E18 ◽  
Author(s):  
Margarita S. Treuth ◽  
Anne L. Adolph ◽  
Nancy F. Butte
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Carbon Dioxide Production ◽  
Vibration Sensor ◽  
Calibration Data ◽  
Regression Equations ◽  
Free Living ◽  
Acceptable Method ◽  
Activity Method ◽  
Separate Regression

The purpose of this study was to predict energy expenditure (EE) from heart rate (HR) and activity calibrated against 24-h respiration calorimetry in 20 children. HR, oxygen consumption (V˙o 2), carbon dioxide production (V˙co 2), and EE were measured during rest, sleep, exercise, and over 24 h by room respiration calorimetry on two separate occasions. Activity was monitored by a leg vibration sensor. The calibration day ( day 1) consisted of specified behaviors categorized as inactive (lying, sitting, standing) or active (two bicycle sessions). On the validation day ( day 2), the child selected activities. Separate regression equations forV˙o 2,V˙co 2, and EE for method 1 (combining awake and asleep using HR, HR2, and HR3), method 2 (separating awake and asleep), and method 3 (separating awake into active and inactive, and combining activity and HR) were developed using the calibration data. For day 1, the errors were similar for 24-hV˙o 2,V˙co 2, and EE among methods and also among HR, HR2, and HR3. The methods were validated using measured data from day 2. There were no significant differences in HR,V˙o 2,V˙co 2, respiratory quotient, and EE values during rest, sleep, or over the 24 h between days 1 and 2. Applying the linear HR equations to day 2 data, the errors were the lowest with the combined HR/activity method (−2.6 ± 5.2%, −4.1 ± 5.9%, −2.9 ± 5.1% forV˙o 2,V˙co 2, and EE, respectively). To demonstrate the utility of the HR/activity method, HR and activity were monitored for 24 h at home ( day 3). Free-living EE was predicted as 7,410 ± 1,326 kJ/day. In conclusion, the combination of HR and activity is an acceptable method for determining EE not only for groups of children, but for individuals.

Physiological responses and energy expenditure during competitive fencing

2014 ◽  
Vol 39 (3) ◽  
pp. 324-328 ◽  
Author(s):  
Raffaele Milia ◽  
Silvana Roberto ◽  
Marco Pinna ◽  
Girolamo Palazzolo ◽  
Irene Sanna ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Oxygen Uptake ◽  
Blood Lactate ◽  
Carbon Dioxide Production ◽  
Maximum Value ◽  
Average Group ◽  
Aerobic Energy Metabolism ◽  
Olympic Sport ◽  
Energetic Expenditure

Fencing is an Olympic sport in which athletes fight one against one using bladed weapons. Contests consist of three 3-min bouts, with rest intervals of 1 min between them. No studies investigating oxygen uptake and energetic demand during fencing competitions exist, thus energetic expenditure and demand in this sport remain speculative. The aim of this study was to understand the physiological capacities underlying fencing performance. Aerobic energy expenditure and the recruitment of lactic anaerobic metabolism were determined in 15 athletes (2 females and 13 males) during a simulation of fencing by using a portable gas analyzer (MedGraphics VO2000), which was able to provide data on oxygen uptake, carbon dioxide production and heart rate. Blood lactate was assessed by means of a portable lactate analyzer. Average group energetic expenditure during the simulation was (mean ± SD) 10.24 ± 0.65 kcal·min−1, corresponding to 8.6 ± 0.54 METs. Oxygen uptakeand heart rate were always below the level of anaerobic threshold previously assessed during the preliminary incremental test, while blood lactate reached its maximum value of 6.9 ± 2.1 mmol·L−1 during the final recovery minute between rounds. Present data suggest that physical demand in fencing is moderate for skilled fencers and that both aerobic energy metabolism and anaerobic lactic energy sources are moderately recruited. This should be considered by coaches when preparing training programs for athletes.

scholarly journals Review of Prediction Models to Estimate Activity-Related Energy Expenditure in Children and Adolescents

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Suzanne M. de Graauw ◽  
Janke F. de Groot ◽  
Marco van Brussel ◽  
Marjolein F. Streur ◽  
Tim Takken
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Prediction Model ◽  
Children And Adolescents ◽  
Prediction Models ◽  
Accurate Estimate ◽  
Healthy Children ◽  
Triaxial Accelerometer ◽  
Free Living ◽  
Doubly Labelled Water

Purpose. To critically review the validity of accelerometry-based prediction models to estimate activity energy expenditure (AEE) in children and adolescents.Methods. The CINAHL, EMBASE, PsycINFO, and PubMed/MEDLINE databases were searched. Inclusion criteria were development or validation of an accelerometer-based prediction model for the estimation of AEE in healthy children or adolescents (6–18 years), criterion measure: indirect calorimetry, or doubly labelled water, and language: Dutch, English or German.Results. Nine studies were included. Median methodological quality was5.5±2.0 IR (out of a maximum 10 points). Prediction models combining heart rate and counts explained 86–91% of the variance in measured AEE. A prediction model based on a triaxial accelerometer explained 90%. Models derived during free-living explained up to 45%.Conclusions. Accelerometry-based prediction models may provide an accurate estimate of AEE in children on a group level. Best results are retrieved when the model combines accelerometer counts with heart rate or when a triaxial accelerometer is used. Future development of AEE prediction models applicable to free-living scenarios is needed.

scholarly journals Validating accelerometry estimates of energy expenditure across behaviours using heart rate data in a free-living seabird

2017 ◽  
Vol 220 (10) ◽  
pp. 1875-1881 ◽  
Author(s):  
Olivia Hicks ◽  
Sarah Burthe ◽  
Francis Daunt ◽  
Adam Butler ◽  
Charles Bishop ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Rate Data ◽  
Free Living ◽  
Heart Rate Data

scholarly journals Critical evaluation of the factorial and heart-rate recording methods for the determination of energy expenditure of free-living elderly people

1997 ◽  
Vol 78 (5) ◽  
pp. 709-722 ◽  
Author(s):  
Beatrice Morio ◽  
Patrick Ritz ◽  
Elisabeth Verdier ◽  
Christophe Montaurier ◽  
Bernard Beaufrere ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Elderly People ◽  
Living Conditions ◽  
Energy Costs ◽  
Free Living ◽  
Factorial Method ◽  
Recording Method ◽  
Mean Differences ◽  
Free Living Conditions

The aim of the present study was to validate against the doubly-labelled water (DLW) technique the factorial method and the heart rate (HR) recording method for determining daily energy expenditure (DEE) of elderly people in free-living conditions. The two methods were first calibrated and validated in twelve healthy subjects (six males and six females; 70·1 (sd 2·7) years) from opencircuit whole-body indirect calorimetry measurements during three consecutive days and during 1 d respectively. Mean energy costs of the various usual activities were determined for each subject using the factorial method, and individual relationships were set up between HR and energy expenditure for the HR recording method. In free-living conditions, DEE was determined over the same period of time by the DLW, the factorial and the HR recording methods during 17, 14 and 4 d respectively. Mean free-living DEE values for men estimated using the DLW, the factorial and the HR recording methods were 12·8 (sd 3·1), 12·7 (sd 2·2) and 13·5 (sd 2·7) MJ/d respectively. Mean free-living DEE values for women were 9·6 (sd 0·8), 8·8 (sd 1·2) and 10·2 (sd 1·5) MJ/d respectively. No significant differences were found between the three methods for either sex, using the Bland & Altman (1986) test. Mean differences in DEE of men were -0·9 (sd 11·8) % between the factorial and DLW methods, and +4·7 (sd 16·1) % between the HR recording and DLW methods. Similarly, in women, mean differences were -7·7 (sd 12·7) % between the factorial and DLW methods, and +5·9 (sd 8·8) % between the HR recording and DLW methods. It was concluded that the factorial and the HR recording methods are satisfactory alternatives to the DLW method when considering the mean DEE of a group of subjects. Furthermore, mean energy costs of activities calculated in the present study using the factorial method were shown to be suitable for determining free-living DEE of elderly people when the reference value (i.e. sleeping metabolic rate) is accurately measured.

Validity of combining heart rate and uniaxial acceleration to measure free-living physical activity energy expenditure in young men

2012 ◽  
Vol 113 (11) ◽  
pp. 1763-1771 ◽  
Author(s):  
C. Villars ◽  
A. Bergouignan ◽  
J. Dugas ◽  
E. Antoun ◽  
D. A. Schoeller ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Intraclass Correlation ◽  
Tolerance Test ◽  
Free Living ◽  
Individual Level ◽  
Individual Calibration ◽  
Old Men ◽  
Activity Energy ◽  
Free Living Conditions

Combining accelerometry (ACC) with heart rate (HR) monitoring is thought to improve activity energy expenditure (AEE) estimations compared with ACC alone to evaluate the validity of ACC and HR used alone or combined. The purpose of this study was to estimate AEE in free-living conditions compared with doubly labeled water (DLW). Ten-day free-living AEE was measured by a DLW protocol in 35 18- to 55-yr-old men (11 lean active; 12 lean sedentary; 12 overweight sedentary) wearing an Actiheart (combining ACC and HR) and a RT3 accelerometer. AEE was estimated using group or individual calibration of the HR/AEE relationship, based on an exercise-tolerance test. In a subset ( n = 21), AEE changes (ΔAEE) were measured after 1 mo of detraining (active subjects) or an 8-wk training (sedentary subjects). Actiheart-combined ACC/HR estimates were more accurate than estimates from HR or ACC alone. Accuracy of the Actiheart group-calibrated ACC/HR estimates was modest [intraclass correlation coefficient (ICC) = 0.62], with no bias but high root mean square error (RMSE) and limits of agreement (LOA). The mean bias of the estimates was reduced by one-third, like RMSE and LOA, by individual calibration (ICC = 0.81). Contrasting with group-calibrated estimates, the Actiheart individual-calibrated ACC/HR estimates explained 40% of the variance of the DLW-ΔAEE (ICC = 0.63). This study supports a good level of agreement between the Actiheart ACC/HR estimates and DLW-measured AEE in lean and overweight men with varying fitness levels. Individual calibration of the HR/AEE relationship is necessary for AEE estimations at an individual level rather than at group scale and for ΔAEE evaluation.

Combined heart rate and activity improve estimates of oxygen consumption and carbon dioxide production rates

1996 ◽  
Vol 81 (4) ◽  
pp. 1754-1761 ◽  
Author(s):  
Jon K. Moon ◽  
Nancy F. Butte
Keyword(s):  
Carbon Dioxide ◽  
Heart Rate ◽  
Oxygen Consumption ◽  
Energy Expenditure ◽  
Carbon Dioxide Production ◽  
Alternative Methods ◽  
Prediction Errors ◽  
Nonlinear Functions ◽  
Production Rates ◽  
Basal Energy Expenditure

Moon, Jon K., and Nancy F. Butte. Combined heart rate and activity improve estimates of oxygen consumption and carbon dioxide production rates. J. Appl. Physiol.81(4): 1754–1761, 1996.—Oxygen consumption (V˙o 2) and carbon dioxide production (V˙co 2) rates were measured by electronically recording heart rate (HR) and physical activity (PA). Mean daily V˙o 2 andV˙co 2 measurements by HR and PA were validated in adults ( n = 10 women and 10 men) with room calorimeters. Thirteen linear and nonlinear functions of HR alone and HR combined with PA were tested as models of 24-h V˙o 2 andV˙co 2. Mean sleepV˙o 2 andV˙co 2 were similar to basal metabolic rates and were accurately estimated from HR alone [respective mean errors were −0.2 ± 0.8 (SD) and −0.4 ± 0.6%]. The range of prediction errors for 24-h V˙o 2 andV˙co 2 was smallest for a model that used PA to assign HR for each minute to separate active and inactive curves (V˙o 2, −3.3 ± 3.5%; V˙co 2, −4.6 ± 3%). There were no significant correlations betweenV˙o 2 orV˙co 2 errors and subject age, weight, fat mass, ratio of daily to basal energy expenditure rate, or fitness. V˙o 2,V˙co 2, and energy expenditure recorded for 3 free-living days were 5.6 ± 0.9 ml ⋅ min−1 ⋅ kg−1, 4.7 ± 0.8 ml ⋅ min−1 ⋅ kg−1, and 7.8 ± 1.6 kJ/min, respectively. Combined HR and PA measured 24-h V˙o 2 andV˙co 2 with a precision similar to alternative methods.

scholarly journals Accelerometry combined with heart rate telemetry in the assessment of total energy expenditure

2006 ◽  
Vol 95 (3) ◽  
pp. 631-639 ◽  
Author(s):  
H. Patrik Johansson ◽  
Lena Rossander-Hulthén ◽  
Frode Slinde ◽  
Björn Ekblom
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Total Energy ◽  
Total Energy Expenditure ◽  
New Method ◽  
Criterion Measure ◽  
Analysis Model ◽  
Free Living ◽  
Advantages And Disadvantages ◽  
Method Analysis

The aim of the present study was: (1) to develop a new method for total energy expenditure (TEE) assessment, using accelerometry (ACC) and heart rate (HR) telemetry in combination; (2) to validate the new method against the criterion measure (DLW) and to compare with two of the most common methods, FLEX-HR and ACC alone. In the first part of the study VO2, HR and ACC counts were measured in twenty-seven subjects during walking and running on a treadmill. Considering the advantages and disadvantages of the HR and ACC methods an analysis model was developed, using ACC at intensities of low and medium levels and HR at higher intensities. During periods of inactivity, RMR is used. A formula for determining TEE from ACC, HR and RMR was developed: TEE =1·1×(EQHR×TTHR+EQACC1×TTACC1+EQACC2×TTACC2+RMR×TTRMR). In the validation part of the study a sub-sample of eight subjects wore an accelerometer, HR was logged and TEE was measured for 14d with the DLW method. Analysis of the Bland–Altman plots with 95% CI indicates that there are no significant differences in TEE estimated with HR–ACC and ACC alone compared with TEE measured with DLW. It is concluded that the HR–ACC combination as well as ACC alone has potential as a method for assessment of TEE during free-living activities as compared with DLW

scholarly journals Validity of hip-mounted uniaxial accelerometry with heart-rate monitoring vs. triaxial accelerometry in the assessment of free-living energy expenditure in young children: the IDEFICS Validation Study

2012 ◽  
Vol 113 (10) ◽  
pp. 1530-1536 ◽  
Author(s):  
Robert Ojiambo ◽  
Kenn Konstabel ◽  
Toomas Veidebaum ◽  
John Reilly ◽  
Vera Verbestel ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Energy Expenditure ◽  
Young Children ◽  
Validation Study ◽  
Longitudinal Axis ◽  
Activity Level ◽  
Free Living ◽  
Model Combining ◽  
Sedentary Activities

One of the aims of Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants (IDEFICS) validation study is to validate field measures of physical activity (PA) and energy expenditure (EE) in young children. This study compared the validity of uniaxial accelerometry with heart-rate (HR) monitoring vs. triaxial accelerometry against doubly labeled water (DLW) criterion method for assessment of free-living EE in young children. Forty-nine European children (25 female, 24 male) aged 4–10 yr (mean age: 6.9 ± 1.5 yr) were assessed by uniaxial ActiTrainer with HR, uniaxial 3DNX, and triaxial 3DNX accelerometry. Total energy expenditure (TEE) was estimated using DLW over a 1-wk period. The longitudinal axis of both devices and triaxial 3DNX counts per minute (CPM) were significantly ( P < 0.05) associated with physical activity level (PAL; r = 0.51 ActiTrainer, r = 0.49 uniaxial-3DNX, and r = 0.42 triaxial Σ3DNX). Eight-six percent of the variance in TEE could be predicted by a model combining body mass (partial r2 = 71%; P < 0.05), CPM-ActiTrainer (partial r2 = 11%; P < 0.05), and difference between HR at moderate and sedentary activities (ModHR − SedHR) (partial r2 = 4%; P < 0.05). The SE of TEE estimate for ActiTrainer and 3DNX models ranged from 0.44 to 0.74 MJ/days or ∼7–11% of the average TEE. The SE of activity-induced energy expenditure (AEE) model estimates ranged from 0.38 to 0.57 MJ/day or 24–26% of the average AEE. It is concluded that the comparative validity of hip-mounted uniaxial and triaxial accelerometers for assessing PA and EE is similar.

scholarly journals Assessment of the heart-rate method for determining energy expenditure in man, using a whole-body calorimeter

1979 ◽  
Vol 42 (1) ◽  
pp. 1-13 ◽  
Author(s):  
M. J. Dauncey ◽  
W. P. T. James
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Whole Body ◽  
Moderate Activity ◽  
Free Living ◽  
Light Activity ◽  
Rate Method ◽  
The Mean ◽  
Standard Techniques ◽  
Activity Energy

1. The heart-rate (HR) method for determining the energy expenditure of free-living subjects has been evaluated using a whole-body calorimete in which individuals lived continuously for 27 h while carrying out normal daily activities. Eight male volunteers each occupied the calorimeter on at least two occasions when HR and energy expenditure were measured continously.2. After each session in the calorimeter a calibration was obtained using standard techniques by determining HR and heat production (HP) over periods of 10–15 min at several levels of activity. Energy expenditure in the calorimeter was then predicted, by each of five methods, from the mean HR in the calorimeter. Additionally, one session in the calorimeter was used to obtain a calibration and was used for predicting the subject's energy expenditure while in the calorimeter on other occasions.3. Standard methods of prediction using one calibration point at rest and several points during activity were unreliable for predicting the energy expenditure of an individual. The 24 h HR was at the lower end of the calibration scale and there were considerable over-estimates or underestimates of energy expenditure, particularly during the night when the mean (±SD) difference between the actual and predicted HP was −66±38±6%. A linear regression fitted to points at the lower levels of activity improved the prediction of 24 h HP while a logistic plot reduced the error even further. The best estimate of energy expenditure was that obtained from a calibration over 24 h within the calorimeter; the mean (±SD) difference between the actual and predicted 24 h HP was +3+10.5% for light activity and −3±6.7% for moderate activity. Thus current procedures for calibrating subjects may lead to large errors which could be reduced by using a respiratory chamber.

scholarly journals Free-living energy expenditure of adult men assessed by continuous heart-rate monitoring and doubly-labelled water

1997 ◽  
Vol 78 (5) ◽  
pp. 695-708 ◽  
Author(s):  
Linda Davidson ◽  
Geraldine McNeill ◽  
Paul Haggarty ◽  
John S. Smith ◽  
Michael F. Franklin
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Leisure Time Physical Activity ◽  
Leisure Activities ◽  
Whole Body ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Adult Men ◽  
Data Points ◽  
Different Levels

Free-living energy expenditure was estimated by doubly-labelled water (DLW) and continuous heart-rate (HR) monitoring over nine consecutive days in nine healthy men with sedentary occupations but different levels of leisure-time physical activity. Individual calibrations of the HR-energy expenditure (EE) relationship were obtained for each subject using 30 min average values of HR and EE obtained during 24h whole-body calorimetry with a defined exercise protocol, and additional data points for individual leisure activities measured with an Oxylog portable O2 consumption meter. The HR data were processed to remove spurious values and insert missing data before the calculation of EE from second-order polynomial equations relating EE to HR. After data processing, the HR-derived EE for this group of subjects was on average 0.8 (sem 0.6) MJ/d, or 6.0 (sem 4.2)% higher than that estimated by DLW. The diary-respirometer method, used over the same 9d, gave values which were 1.9 (sem 0.7) MJ/d, or -12.1 (sem 4.0)% lower than the DLW method. The results suggest that HR monitoring can provide a better estimate of 24 h EE of groups than the diary-respirometer method, but show that both methods can introduce errors of 20% or more in individuals.

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