Skip to main content
Log in

A new method to estimate energy expenditure from abdominal and rib cage distances

  • Original Article
  • Published:
European Journal of Applied Physiology Aims and scope Submit manuscript

Abstract

The aim of this paper is to validate a new method of energy expenditure (EE) estimation stemming solely from the measurement of rib cage, abdominal and chest wall distances. We set out to prove that the variations of these distances, measured by two pairs of electromagnetic coils, lead to the estimation of the ventilation (\( \dot{V}_{E} \)) and the EE. Eleven subjects were recruited to take part in this study (27.6 ± 5.4 years; 73.7 ± 9.7 kg). Each subject participated in two tests. The objective of Test 1 was to determine the individual and group equations between the \( \dot{V}_{E} \) and EE during light to moderate activities while Test 2 compared the two pairs of electromagnetic coils with the indirect calorimetry so as to estimate EE in upright sitting and standing positions and during walking exercises. During Test 2, we compared EE measured by indirect calorimetry (EEIC-Val-REF) with EE estimated by the two pairs of electromagnetic coils through the application of: (1) the individual equation (EEmag-Val-INDIV) and (2) the group equation (EEmag-val-GROUP). The results show that there is no significant difference between EEIC-Val-REF and EEmag-Val-INDIV and between EEIC-Val-REF and EEmag-val-GROUP for each activity. Furthermore, the mean difference seems to show that the estimation of EE is better with the group equation. In conclusion, on the proven basis of this study we are able to validate this new method which permits the estimation of EE from abdominal and rib cage distances. This study also highlights the advantage of using a group equation to the estimate EE.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Achten J, Jeukendrup AE (2003) Heart rate monitoring: applications and limitations. Sports Med 33:517–538

    Article  PubMed  Google Scholar 

  • Ancoli-Israel S, Kripke DF, Mason W, Kaplan OJ (1985) Sleep apnea and periodic movements in an aging sample. J Gerontol 40:419–425

    PubMed  CAS  Google Scholar 

  • Arvidsson D, Slinde F, Larsson S, Hulthen L (2007) Energy cost of physical activities in children: validation of SenseWear Armband. Med Sci Sports Exerc 39:2076–2084

    Article  PubMed  Google Scholar 

  • Arvidsson D, Slinde F, Hulthen L (2009) Free-living energy expenditure in children using multi-sensor activity monitors. Clin Nutr 28:305–312

    Article  PubMed  Google Scholar 

  • Bassett DR, Ainsworth BE, Swartz AM (2000) Validity of four motion sensors in measuring moderate intensity physical activity. Med Sci Sports Exerc 32:S471–S480

    Article  PubMed  Google Scholar 

  • Bouchard C (2001) Physical activity and health: introduction to the dose-response symposium. Med Sci Sports Exerc 33:S347–S350

    Article  PubMed  CAS  Google Scholar 

  • Brage S, Brage N, Franks PW, Ekelund U, Wareham NJ (2005) Reliability and validity of the combined heart rate and movement sensor Actiheart. Eur J Clin Nutr 59:561–570

    Article  PubMed  CAS  Google Scholar 

  • Ceesay SM, Prentice AM, Day KC, Murgatroyd PR, Goldberg GR, Scott W, Spurr GB (1989) The use of heart rate monitoring in the estimation of energy expenditure: a validation study using indirect whole-body calorimetry. Br J Nutr 61:175–186

    Article  PubMed  CAS  Google Scholar 

  • Cereda E, Turrini M, Ciapanna D, Marbello L, Pietrobelli A, Corradi E (2007) Assessing energy expenditure in cancer patients: a pilot validation of a new wearable device. JPEN J Parenter Enteral Nutr 31:502–507

    Article  PubMed  Google Scholar 

  • Christensen CC, Frey HM, Foenstelien E, Aadland E, Refsum HE (1983) A critical evaluation of energy expenditure estimates based on individual O2 consumption/heart rate curves and average daily heart rate. Am J Clin Nutr 37:468–472

    PubMed  CAS  Google Scholar 

  • Corder K, Brage S, Wareham NJ, Ekelund U (2005) Comparison of PAEE from combined and separate heart rate and movement models in children. Med Sci Sports Exerc 37:1761–1767

    Article  PubMed  Google Scholar 

  • Corder K, Brage S, Ekelund U (2007a) Accelerometers and pedometers: methodology and clinical application. Curr Opin Clin Nutr Metab Care 10:597–603

    Article  PubMed  Google Scholar 

  • Corder K, Brage S, Mattocks C, Ness A, Riddoch C, Wareham NJ, Ekelund U (2007b) Comparison of two methods to assess PAEE during six activities in children. Med Sci Sports Exerc 39:2180–2188

    Article  PubMed  Google Scholar 

  • Crespo CJ, Keteyian SJ, Heath GW, Sempos CT (1996) Leisure-time physical activity among US adults. Results from the Third National Health and Nutrition Examination Survey. Arch Intern Med 93:93–98

    Article  Google Scholar 

  • Dipietro L, Caspersen CJ, Ostfeld AM, Nadel ER (1993) A survey for assessing physical activity among older adults. Med Sci Sports Exerc 25:628–642

    PubMed  CAS  Google Scholar 

  • Durnin JV, Edwards RG (1955) Pulmonary ventilation as an index of energy expenditure. Q J Exp Physiol Cogn Med Sci 40:370–377

    PubMed  CAS  Google Scholar 

  • Dwyer TJ, Alison JA, McKeough ZJ, Elkins MR, Bye PT (2009) Evaluation of the SenseWear activity monitor during exercise in cystic fibrosis and in health. Respir Med 103:1511–1517

    Google Scholar 

  • Eston RG, Rowlands AV, Ingledew DK (1998) Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children’s activities. J Appl Physiol 84:362–371

    PubMed  CAS  Google Scholar 

  • Fiamma MN, Samara Z, Baconnier P, Similowski T, Straus C (2007) Respiratory inductive plethysmography to assess respiratory variability and complexity in humans. Respir Physiol Neurobiol 156:234–239

    Article  PubMed  Google Scholar 

  • Ford AB, Hellerstein HK (1959) Estimation of energy expenditure from pulmonary ventilation. J Appl Physiol 14:891–893

    PubMed  CAS  Google Scholar 

  • Fruin ML, Rankin JW (2004) Validity of a multi-sensor armband in estimating rest and exercise energy expenditure. Med Sci Sports Exerc 36:1063–1069

    Article  PubMed  Google Scholar 

  • Gastinger S, Sefati H, Nicolas G, Sorel A, Gratas-Delamarche A, Prioux J (2010a) Estimates of ventilation from measurements of rib cage and abdominal distances: a portable device. Eur J Appl Physiol 109:1179–1189

    Article  PubMed  CAS  Google Scholar 

  • Gastinger S, Sorel A, Nicolas G, Gratas-Delamarche A, Prioux J (2010b) A comparison between ventilation and heart rate as indicator of oxygen uptake during different intensities of exercise. J Sports Sci Med 9:110–118

    Google Scholar 

  • Goran MI, Poehlman ET (1992) Endurance training does not enhance total energy expenditure in healthy elderly persons. Am J Physiol 263:E950–E957

    PubMed  CAS  Google Scholar 

  • Grossman P (2004) The LifeShirt: a multi-function ambulatory system monitoring health, disease, and medical intervention in the real world. Stud Health Technol Inform 108:133–141

    PubMed  Google Scholar 

  • Harrell JS, McMurray RG, Baggett CD, Pennell ML, Pearce PF, Bangdiwala SI (2005) Energy costs of physical activities in children and adolescents. Med Sci Sports Exerc 37:329–336

    Article  PubMed  Google Scholar 

  • Harris JA, Benedict FG (1919) A biometric study of basal metabolism in man. Carnegie Institute of Washington, Washington

  • Heldt GP (1988) Simultaneous quantification of chest wall distortion by multiple methods in preterm infants. Am Rev Respir Dis 138:20–25

    Article  PubMed  CAS  Google Scholar 

  • Hoos MB, Plasqui G, Gerver WJ, Westerterp KR (2003) Physical activity level measured by doubly labeled water and accelerometry in children. Eur J Appl Physiol 89:624–626

    Article  PubMed  Google Scholar 

  • Jackson AS, Stanforth PR, Gagnon J, Rankinen T, Leon AS, Rao DC, Skinner JS, Bouchard C, Wilmore JH (2002) The effect of sex, age and race on estimating percentage body fat from body mass index: the Heritage Family Study. Int J Obes 26:789–796

    Article  CAS  Google Scholar 

  • Jakicic JM, Marcus M, Gallagher KI, Randall C, Thomas E, Goss FL, Robertson RJ (2004) Evaluation of the SenseWear Pro Armband to assess energy expenditure during exercise. Med Sci Sports Exerc 36:897–904

    Article  PubMed  Google Scholar 

  • Karvonen J, Chwalbinska-Moneta J, Saynajakangas S (1984) Comparison of heart rates measured by ECG and microcomputer. Phys Sportsmed 12:65–69

    Google Scholar 

  • King GA, Torres N, Potter C, Brooks TJ, Coleman KJ (2004) Comparison of activity monitors to estimate energy cost of treadmill exercise. Med Sci Sports Exerc 36:1244–1251

    Article  PubMed  Google Scholar 

  • Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346:393–403

    Article  PubMed  CAS  Google Scholar 

  • Konno K, Mead J (1967) Measurement of the separate volume changes of rib cage and abdomen during breathing. J Appl Physiol 22:407–422

    PubMed  CAS  Google Scholar 

  • Kurpad AV, Raj R, Maruthy KN, Vaz M (2006) A simple method of measuring total daily energy expenditure and physical activity level from the heart rate in adult men. Eur J Clin Nutr 60:32–40

    Article  PubMed  CAS  Google Scholar 

  • Leger L, Thivierge M (1998) Heart rate monitors: validity, stability, and functionality. Phys Sportsmed 16:143–151

    Google Scholar 

  • Leino K, Nunes S, Valta P, Takala J (2001) Validation of a new respiratory inductive plethysmograph. Acta Anaesthesiol Scand 45:104–111

    Article  PubMed  CAS  Google Scholar 

  • Macfarlane DJ (2001) Automated metabolic gas analysis systems: a review. Sports Med 31:841–861

    Article  PubMed  CAS  Google Scholar 

  • Manini TM, Everhart JE, Patel KV, Schoeller DA, Colbert LH, Visser M, Tylavsky F, Bauer DC, Goodpaster BH, Harris TB (2006) Daily activity energy expenditure and mortality among older adults. JAMA 296:171–179

    Article  PubMed  CAS  Google Scholar 

  • Montoye HJ, Washburn R, Servais S, Ertl A, Webster JG, Nagle FJ (1983) Estimation of energy expenditure by a portable accelerometer. Med Sci Sports Exerc 15:403–407

    PubMed  CAS  Google Scholar 

  • Montoye H, Kemper H, Saris W (1996) Measuring physical activity and energy expenditure. Hum Kinet

  • Neumann P, Zinserling J, Haase C, Sydow M, Burchardi H (1998) Evaluation of respiratory inductive plethysmography in controlled ventilation: measurement of tidal volume and PEEP-induced changes of end-expiratory lung volume. Chest 113:443–451

    Article  PubMed  CAS  Google Scholar 

  • Park S, Jayaraman S (2005) Wearable sensor systems: opportunities and challenges. Conf Proc IEEE Eng Med Biol Soc 4:4153–4155

    PubMed  Google Scholar 

  • Peronnet F, Massicotte D (1991) Table of nonprotein respiratory quotient: an update. Can J Sport Sci 16:23–29

    PubMed  CAS  Google Scholar 

  • Plasqui G, Westerterp KR (2007) Physical activity assessment with accelerometers: an evaluation against doubly labeled water. Obesity (Silver Spring) 15:2371–2379

    Article  Google Scholar 

  • Saltin B, Astrand PO (1967) Maximal oxygen uptake in athletes. J Appl Physiol 23:353–358

    PubMed  CAS  Google Scholar 

  • Sherman SE, D’Agostino RB, Cobb JL, Kannel WB (1994) Does exercise reduce mortality rates in the elderly? Experience from the Framingham Heart Study. Am Heart J 128:965–972

    Article  PubMed  CAS  Google Scholar 

  • Spurr GB, Prentice AM, Murgatroyd PR, Goldberg GR, Reina JC, Christman NT (1988) Energy expenditure from minute-by-minute heart-rate recording: comparison with indirect calorimetry. Am J Clin Nutr 48:552–559

    PubMed  CAS  Google Scholar 

  • Stick SM, Ellis E, LeSouef PN, Sly PD (1992) Validation of respiratory inductance plethysmography (“Respitrace”) for the measurement of tidal breathing parameters in newborns. Pediatr Pulmonol 14:187–191

    Article  PubMed  CAS  Google Scholar 

  • St-Onge M, Mignault D, Allison DB, Rabasa-Lhoret R (2007) Evaluation of a portable device to measure daily energy expenditure in free-living adults. Am J Clin Nutr 85:742–749

    PubMed  CAS  Google Scholar 

  • Taylor HL, Buskirk E, Henschel A (1955) Maximal oxygen intake as an objective measure of cardio-respiratory performance. J Appl Physiol 8:73–80

    PubMed  CAS  Google Scholar 

  • Treiber FA, Musante L, Hartdagan S, Davis H, Levy M, Strong WB (1989) Validation of a heart rate monitor with children in laboratory and field settings. Med Sci Sports Exerc 21:338–342

    PubMed  CAS  Google Scholar 

  • Treuth MS, Adolph AL, Butte NF (1998) Energy expenditure in children predicted from heart rate and activity calibrated against respiration calorimetry. Am J Physiol 275:E12–E18

    PubMed  CAS  Google Scholar 

  • Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ilanne-Parikka P, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M, Salminen V, Uusitupa M (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344:1343–1350

    Article  PubMed  CAS  Google Scholar 

  • Wareham NJ, Rennie KL (1998) The assessment of physical activity in individuals and populations: why try to be more precise about how physical activity is assessed? Int J Obes Relat Metab Disord 22(2):S30–S38

    PubMed  Google Scholar 

  • Wasserman K, Whipp B, Casaburi R (1986) Respiratory control during exercise. In: Fishman A, Cherniak NS, Widdicombe JG (eds) Handbook of physiology: the respiratory system, a control of breathing. Bethesda MD: Am Physiol Soc pp 595–620

  • WHO Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser 1995; 854:1–452

  • Wierenga ME, Browning JM, Mahn JL (1990) A descriptive study of how clients make life-style changes. Diabetes Educ 16:469–473

    Article  PubMed  CAS  Google Scholar 

  • Zakeri I, Adolph AL, Puyau MR, Vohra FA, Butte NF (2008) Application of cross-sectional time series modeling for the prediction of energy expenditure from heart rate and accelerometry. J Appl Physiol 104:1665–1673

    Article  PubMed  Google Scholar 

  • Zinman B, Ruderman N, Campaigne BN, Devlin JT, Schneider SH (2004) Physical activity/exercise and diabetes. Diabetes Care 27(1):S58–S62

    Article  Google Scholar 

Download references

Acknowledgments

The authors wish to acknowledge all the subjects for their participation in the study. We also wish to honor the memory of Delphine Thévenet by dedicating her this article.

Conflict of interest

This study was funded through the SVP (“SurVeiller pour Prévenir”) and the “PucesCom.Santé” projects. There is no conflict of interest in this research. The six authors have participated in the development and implementation of the protocol and in the writing of this article.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Gastinger.

Additional information

Communicated by Susan A. Ward.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gastinger, S., Sefati, H., Nicolas, G. et al. A new method to estimate energy expenditure from abdominal and rib cage distances. Eur J Appl Physiol 111, 2823–2835 (2011). https://doi.org/10.1007/s00421-011-1900-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00421-011-1900-9

Keywords

Navigation