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.

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.

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.

Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure

2004 ◽  
Vol 96 (1) ◽  
pp. 343-351 ◽  
Author(s):  
Søren Brage ◽  
Niels Brage ◽  
Paul W. Franks ◽  
Ulf Ekelund ◽  
Man-Yu Wong ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Energy Expenditure ◽  
A Priori ◽  
Whole Body ◽  
Equation Modeling ◽  
Physical Activity Energy Expenditure ◽  
Improve Measurement ◽  
Post Hoc ◽  
Activity Energy

The combination of heart rate (HR) monitoring and movement registration may improve measurement precision of physical activity energy expenditure (PAEE). Previous attempts have used either regression methods, which do not take full advantage of synchronized data, or have not used movement data quantitatively. The objective of the study was to assess the precision of branched model estimates of PAEE by utilizing either individual calibration (IC) of HR and accelerometry or corresponding mean group calibration (GC) equations. In 12 men (20.6-25.2 kg/m2), IC and GC equations for physical activity intensity (PAI) were derived during treadmill walking and running for both HR (Polar) and hipacceleration [Computer Science and Applications (CSA)]. HR and CSA were recorded minute by minute during 22 h of whole body calorimetry and converted into PAI in four different weightings (P1-4) of the HR vs. the CSA (1-P1-4) relationships: if CSA > x, we used the P1 weighting if HR > y, otherwise P2. Similarly, if CSA ≤ x, we used P3 if HR > z, otherwise P4. PAEE was calculated for a 12.5-h nonsleeping period as the time integral of PAI. A priori, we assumed P1 = 1, P2 = P3 = 0.5, P4 = 0, x = 5 counts/min, y = walking/running transition HR, and z = flex HR. These parameters were also estimated post hoc. Means ± SD estimation errors of a priori models were -4.4 ± 29 and 3.5 ± 20% for IC and GC, respectively. Corresponding post hoc model errors were -1.5 ± 13 and 0.1 ± 9.8%, respectively. All branched models had lower errors ( P ≤ 0.035) than single-measure estimates of CSA (less than or equal to -45%) and HR (≥39%), as well as their nonbranched combination (≥25.7%). In conclusion, combining HR and CSA by branched modeling improves estimates of PAEE. IC may be less crucial with this modeling technique.

Validation of Combined Heart Rate and Movement Sensing to Estimate Free-living Physical Activity Energy Expenditure

2007 ◽  
Vol 39 (Supplement) ◽  
pp. S26
Author(s):  
Soren Brage ◽  
Ulf Ekelund ◽  
Paul W. Franks ◽  
Mark A. Hennings ◽  
Antony Wright ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Energy Expenditure ◽  
Physical Activity Energy Expenditure ◽  
Free Living ◽  
Activity Energy

scholarly journals The use of heart rate monitoring in the estimation of energy expenditure: a validation study using indirect whole-body calorimetry

1989 ◽  
Vol 61 (2) ◽  
pp. 175-186 ◽  
Author(s):  
Sana M. Ceesay ◽  
Andrew M. Prentice ◽  
Kenneth C. Day ◽  
Peter R. Murgatroyd ◽  
Gail R. Goldberg ◽  
...  
Keyword(s):  
Heart Rate ◽  
Energy Expenditure ◽  
Predictive Power ◽  
Low Cost ◽  
Total Energy Expenditure ◽  
Whole Body ◽  
Heart Rate Monitoring ◽  
Calibration Curves ◽  
Individual Calibration ◽  
The Mean

1. A modified heart rate (HR) method for predicting total energy expenditure (TEE) was cross-validated against whole-body calorimetry (CAL). Minute-by-minute HR was converted to energy expenditure (EE) using individual calibration curves when HR exceeded a pre-determined ‘FLEX’ value designed to discriminate periods of activity. (‘FLEX’ HR was defined as the mean of the highest HR during rest and the lowest HR during the lightest imposed exercise.) Sedentary EE (below FLEX) was calculated as the mean EE during lying down, sitting and standing at rest. Sleeping EE was calculated as basal metabolic rate (BMR) predicted from standard equations.2. Calibration curves of oxygen consumption v. HR for different postures at rest and during exercise were obtained for twenty healthy subjects (eleven male, nine female); mean r 0.941 (SD 0.04). The mean FLEX HR for men and women were 86 (sd 10) and 96 (SD 6) beats/min respectively.3. Simultaneous measurements of HR and EE were made during 21 h continuous CAL, which included 4 x 30 min imposed exercise (cycling, rowing, stepping, jogging). HR exceeded FLEX for a mean of 98 (SD 41) min. Mean TEE by CAL (TEE. CAL) was 8063 (sd 1445) kJ.4. The HR method yielded a mean non-significant underestimate in TEE (TEE. HR) of 1.2 (sd 6.2)% (range−11.4 to + 10.6 %). Regression of TEE. HR (y) v. TEE. CAL (X) yielded Y = 0.868 X +927 kJ, r 0.943, se of the estimate 458 kJ, n 20.5. The satisfactory predictive power and low cost of the method makes it suitable for many field and epidemiological applications.

Effect of season on thermoregulatory responses and energy expenditure of goats on semi-arid range in India

2002 ◽  
Vol 139 (1) ◽  
pp. 87-93 ◽  
Author(s):  
A. K. SHINDE ◽  
RAGHAVENDRA BHATTA ◽  
S. K. SANKHYAN ◽  
D. L. VERMA
Keyword(s):  
Heart Rate ◽  
Heat Stress ◽  
Solar Radiation ◽  
Energy Expenditure ◽  
Arid Regions ◽  
Physiological Responses ◽  
Face Mask ◽  
Mean Value ◽  
The Mean ◽  
Semi Arid

A study of the physiological responses and energy expenditure of goats was carried out from June 1999 to May 2000 by conducting two experiments: one on bucks maintained on stall feeding in autumn 1999 (Expt 1) followed by year-round grazing on native ranges over three seasons: monsoon, winter and summer (Expt 2). Physiological responses and energy expenditure (EE) measurements of housed and grazing goats were recorded at 06.00 h and 14.00 h for 5 consecutive days in each season. Goats were fixed with a face mask and meteorological balloon for collection of expired air and measurement of EE. Respiration rate (RR) at 06.00 h was similar in all seasons (14 respiration/min) except in the monsoon, where a significantly (P<0.05) higher value (26 respiration/min) was recorded. At 14.00 h, RR was higher in monsoon and summer (81 and 91 respiration/min) than in winter (52 respiration/min). Irrespective of the season, heart rate (HR) was higher at 14.00 h (86 beat/min) than at 06.00 h (64 beat/min). The rise of rectal temperature (RT) from morning (06.00 h) to peak daily temperature (14.00 h) was 0.9 °C in housed goats in autumn and 1.0, 2.1 and 2.0 °C in grazing goats during monsoon, winter and summer, respectively. The mean value was 1.7 °C. Skin temperature (ST) was lowest in winter (30.1 °C) and highest at 14.00 h in summer (40.3 °C). Energy expenditure of goats at 06.00 h was 32.7 W in winter and significantly (P<0.05) increased to 52.0 W in summer and 107.8 W in monsoon. At 14.00 h, EE was 140.2 W in winter and increased to 389.0 W and 391.3 W respectively in monsoon and summer. It is concluded that monsoon and summer are both stressful seasons in semi-arid regions. Animals should be protected from direct solar radiation during the hottest hours of the day to ameliorate the effect of heat stress.

scholarly journals Energy expenditure of free-living reindeer estimated by the doubly labelled water method

Rangifer ◽  
2000 ◽  
Vol 20 (2-3) ◽  
pp. 211 ◽  
Author(s):  
Geir Gotaas ◽  
Eric Milne ◽  
Paul Haggarty ◽  
Nicholas J.C. Tyler
Keyword(s):  
Energy Expenditure ◽  
Rangifer Tarandus ◽  
Water Flux ◽  
Co2 Production ◽  
Wild Ungulates ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Svalbard Reindeer ◽  
Mountain Pasture ◽  
The Mean

The doubly labelled water (DLW) method was used to measure total energy expenditure (TEE) in three male reindeer (Rangifer tarandus tarandus) aged 22 months in winter (February) while the animals were living unrestricted at natural mountain pasture in northern Norway (69&deg;20'N). The concentrations of 2H and l8O were measured in water extracted from samples of faeces collecred from the animals 0.4 and 11.2 days after injection of the isotopes. Calculated rates of water flux and CO2-production were adjusted to compensate for estimated losses of 2H in faecal solids and in methane produced by microbial fermentation of forage in the rumen. The mean specific TEE in the three animals was 3.057 W.kg-1 (range 2.436 - 3.728 W.kg1). This value is 64% higher than TEE measured by the DLW method in four captive, non-pregnant adult female reindeer in winter and probably mainly reflects higher levels of locomotor activity in the free-living animals. Previous estimates of TEE in free-living Rangifer in winter based on factorial models range from 3.038 W.kg-1 in female woodland caribou (R. t. caribou) to 1.813 W.kg-1 in female Svalbard reindeer (R. t. platyrhynchus). Thus, it seems that existing factorial models are unlikely to overestimate TEE in reindeer/caribou: they may, instead, be unduly conservative. While the present study serves as a general validation of the factorial approach, we suggest that the route to progress in the understanding of field energetics in wild ungulates is via application of the DLW method.

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
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