Assessment of energy expenditure during high intensity cycling and running using a heart rate and activity monitor in young active adults
Autoři:
Malgorzata Klass aff001; Vitalie Faoro aff002; Alain Carpentier aff001
Působiště autorů:
Laboratory for Biometry and Exercise Nutrition, Université Libre de Bruxelles (ULB), Brussels, Belgium
aff001; Cardiopulmonary Exercise Laboratory, Université Libre de Bruxelles (ULB), Brussels, Belgium
aff002
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0224948
Souhrn
Objective
Although high intensity physical activities may represent a great proportion of the total energy expenditure in active people, only sparse studies have investigated the accuracy of wearable monitors to assess activity related energy expenditure (AEE) during high intensity exercises. Therefore, the purpose of the present study was to investigate the accuracy of the Actiheart, a light portable monitor estimating AEE based on heart rate (HR) and activity counts (ACT), during two popular activities (running and cycling) performed at high intensities. The benefit of an individual calibration of the HR-AEE relationship established during a preliminary maximal test was also evaluated.
Methods
AEE was estimated in eighteen active adults (4 women and 14 men; 25 ± 4 yr) with indirect calorimetry using a respiratory gas analysis system (reference method) and the Actiheart during 5-min running and cycling at 60, 75 and 85% of maximal oxygen uptake (VO2max) previously determined during a maximal test performed on a treadmill or cycle ergometer. For the Actiheart, AEE was estimated either using the group or individual calibrated equations available in the dedicated software, and their respective HR, ACT or combined HR/ACT algorithms.
Results
When the HR algorithm was used for cycling and the HR or HR/ACT algorithms for running, AEE measured by the Actiheart increased proportionally to exercise intensity from 60 to 85% VO2max (P<0.001). Compared to indirect calorimetry, the Actiheart group calibrated equations slightly to moderately underestimated (3 to 20%) AEE for the three exercise intensities (P<0.001). Accuracy of AEE estimation was greatly improved by individual calibration of the HR-AEE relationship (underestimation below 5% and intraclass correlation coefficient [ICC]: 0.79–0.93) compared to group calibration (ICC: 0.64–0.79).
Conclusion
The Actiheart enables to assess AEE during high intensity running and cycling when the appropriate algorithm is applied. Since an underestimation was present for group calibration, an individual and sport-specific calibration should be performed when a high accuracy is required.
Klíčová slova:
Accelerometers – Algorithms – Bioenergetics – Exercise – Heart rate – Running – Sports – Indirect calorimetry
Zdroje
1. Westerterp KR. Impacts of vigorous and non-vigorous activity on daily energy expenditure. Proc Nutr Soc. 2003;62: 645–650. doi: 10.1079/PNS2003279 14692600
2. Brychta R, Wohlers E, Moon J, Chen K. Energy Expenditure: Measurement of Human Metabolism. IEEE Eng Med Biol Mag. 2010;29: 42–47. doi: 10.1109/MEMB.2009.935463 20176521
3. van Hoye K, Mortelmans P, Lefevre J. Validation of the SenseWear Pro3 Armband Using an Incremental Exercise Test. J Strength Cond Res Natl Strength Cond Assoc. 2014;28: 2806–2814. doi: 10.1519/JSC.0b013e3182a1f836 25250859
4. Crouter SE, Churilla JR, Bassett DR. Estimating energy expenditure using accelerometers. Eur J Appl Physiol. 2006;98: 601–612. doi: 10.1007/s00421-006-0307-5 17058102
5. Drenowatz C, Eisenmann JC. Validation of the SenseWear Armband at high intensity exercise. Eur J Appl Physiol. 2011;111: 883–887. doi: 10.1007/s00421-010-1695-0 20972880
6. Koehler K, Braun H, de Marées M, Fusch G, Fusch C, Schaenzer W. Assessing energy expenditure in male endurance athletes: validity of the SenseWear Armband. Med Sci Sports Exerc. 2011;43: 1328–1333. doi: 10.1249/MSS.0b013e31820750f5 21131865
7. Gastin PB, Cayzer C, Dwyer D, Robertson S. Validity of the ActiGraph GT3X+ and BodyMedia SenseWear Armband to estimate energy expenditure during physical activity and sport. J Sci Med Sport. 2018;21: 291–295. doi: 10.1016/j.jsams.2017.07.022 28797831
8. Warren JM, Ekelund U, Besson H, Mezzani A, Geladas N, Vanhees L. Assessment of physical activity–a review of methodologies with reference to epidemiological research: a report of the exercise physiology section of the European Association of Cardiovascular Prevention and Rehabilitation. Eur J Cardiovasc Prev Rehabil. 2010;17: 127–139. doi: 10.1097/HJR.0b013e32832ed875 20215971
9. Hiilloskorpi HK, Pasanen ME, Fogelholm MG, Laukkanen RM, Mänttäri AT. Use of Heart Rate to Predict Energy Expenditure from Low to High Activity Levels. Int J Sports Med. 2003;24: 332–336. doi: 10.1055/s-2003-40701 12868043
10. Andrews RB. Net heart rate as a substitute for respiratory calorimetry. Am J Clin Nutr. 1971;24: 1139–1147. doi: 10.1093/ajcn/24.9.1139 5094486
11. Hiilloskorpi Fogelholm, Laukkanen Pasanen, Oja Mänttäri, et al. Factors Affecting the Relation Between Heart Rate and Energy Expenditure During Exercise. Int J Sports Med. 1999;20: 438–443. doi: 10.1055/s-1999-8829 10551338
12. Isacco L, Duché P, Boisseau N. Influence of Hormonal Status on Substrate Utilization at Rest and during Exercise in the Female Population: Sports Med. 2012;42: 327–342. doi: 10.2165/11598900-000000000-00000 22380007
13. O’Driscoll R, Turicchi J, Beaulieu K, Scott S, Matu J, Deighton K, et al. How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies. Br J Sports Med. 2018;. doi: 10.1136/bjsports-2018-099643 30194221
14. Kendall B, Bellovary B, Gothe NP. Validity of wearable activity monitors for tracking steps and estimating energy expenditure during a graded maximal treadmill test. J Sports Sci. 2018; 1–8. doi: 10.1080/02640414.2018.1481723 29863968
15. Lam YY, Ravussin E. Analysis of energy metabolism in humans: A review of methodologies. Mol Metab. 2016;5: 1057–1071. doi: 10.1016/j.molmet.2016.09.005 27818932
16. Luke A, Maki KC, Barkey N, Cooper R, McGee D. Simultaneous monitoring of heart rate and motion to assess energy expenditure. Med Sci Sports Exerc. 1997;29: 144–148. doi: 10.1097/00005768-199701000-00021 9000168
17. Strath SJ, Bassett DR, Swartz AM, Thompson DL. Simultaneous heart rate-motion sensor technique to estimate energy expenditure. Med Sci Sports Exerc. 2001;33: 2118–2123. doi: 10.1097/00005768-200112000-00022 11740308
18. Strath SJ, Brage S, Ekelund U. Integration of Physiological and Accelerometer Data to Improve Physical Activity Assessment: Med Sci Sports Exerc. 2005;37: S563–S571. doi: 10.1249/01.mss.0000185650.68232.3f 16294119
19. Brage S, Brage N, Franks PW, Ekelund U, Wong M-Y, Andersen LB, et al. Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure. J Appl Physiol. 2004;96: 343–351. doi: 10.1152/japplphysiol.00703.2003 12972441
20. Brage S, Brage N, Franks PW, Ekelund U, Wareham NJ. Reliability and validity of the combined heart rate and movement sensor Actiheart. Eur J Clin Nutr. 2005;59: 561–570. doi: 10.1038/sj.ejcn.1602118 15714212
21. Brage S, Westgate K, Franks PW, Stegle O, Wright A, Ekelund U, et al. Estimation of Free-Living Energy Expenditure by Heart Rate and Movement Sensing: A Doubly-Labelled Water Study. PLOS ONE. 2015;10: e0137206. doi: 10.1371/journal.pone.0137206 26349056
22. Chowdhury EA, Western MJ, Nightingale TE, Peacock OJ, Thompson D. Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors. PLOS ONE. 2017;12: e0171720. doi: 10.1371/journal.pone.0171720 28234979
23. Crouter SE, Churilla JR, Bassett DR. Accuracy of the Actiheart for the assessment of energy expenditure in adults. Eur J Clin Nutr. 2008;62: 704–711. doi: 10.1038/sj.ejcn.1602766 17440515
24. Barreira TV, Kang M, Caputo JL, Farley RS, Renfrow MS. Validation of the Actiheart monitor for the measurement of physical activity. Int J Exerc Sci. 2009;2: 60–71.
25. Villars C, Bergouignan A, Dugas J, Antoun E, Schoeller DA, Roth H, et al. Validity of combining heart rate and uniaxial acceleration to measure free-living physical activity energy expenditure in young men. J Appl Physiol. 2012;113: 1763–1771. doi: 10.1152/japplphysiol.01413.2011 23019315
26. Nichols JF, Aralis H, Merino SG, Barrack MT, Stalker-Fader L, Rauh MJ. Utility of the Actiheart Accelerometer for Estimating Exercise Energy Expenditure in Female Adolescent Runners. Int J Sport Nutr Exerc Metab. 2010;20: 487–495. doi: 10.1123/ijsnem.20.6.487 21116021
27. Koehler K, de Marees M, Braun H, Schaenzer W. Evaluation of two portable sensors for energy expenditure assessment during high-intensity running. Eur J Sport Sci. 2013;13: 31–41. doi: 10.1080/17461391.2011.586439
28. Spierer DK, Hagins M, Rundle A, Pappas E. A comparison of energy expenditure estimates from the Actiheart and Actical physical activity monitors during low intensity activities, walking, and jogging. Eur J Appl Physiol. 2011;111: 659–667. doi: 10.1007/s00421-010-1672-7 20953878
29. Jones AM, Doust JH. A 1% treadmill grade most accurately reflects the energetic cost of outdoor running. J Sports Sci. 1996;14: 321–327. doi: 10.1080/02640419608727717 8887211
30. Weir JB de V. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol. 1949;109: 1–9. Available: http://jp.physoc.org/content/109/1-2/1 15394301
31. Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39 Suppl 1: 5–41.
32. Brage S, Ekelund U, Brage N, Hennings MA, Froberg K, Franks PW, et al. Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity. J Appl Physiol. 2007;103: 682–692. doi: 10.1152/japplphysiol.00092.2006 17463305
33. Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 2016;15: 155–163. doi: 10.1016/j.jcm.2016.02.012 27330520
34. Schneller MB, Pedersen MT, Gupta N, Aadahl M, Holtermann A. Validation of Five Minimally Obstructive Methods to Estimate Physical Activity Energy Expenditure in Young Adults in Semi-Standardized Settings. Sensors. 2015;15: 6133–6151. doi: 10.3390/s150306133 25781506
35. Rousset S, Fardet A, Lacomme P, Normand S, Montaurier C, Boirie Y, et al. Comparison of total energy expenditure assessed by two devices in controlled and free-living conditions. Eur J Sport Sci. 2015;15: 391–399. doi: 10.1080/17461391.2014.949309 25141769
36. Santos DA, Silva AM, Matias CN, Magalhães JP, Fields DA, Minderico CS, et al. Validity of a combined heart rate and motion sensor for the measurement of free-living energy expenditure in very active individuals. J Sci Med Sport. 2014;17: 387–393. doi: 10.1016/j.jsams.2013.09.006 24184093
37. Thompson D, Batterham AM, Bock S, Robson C, Stokes K. Assessment of Low-to-Moderate Intensity Physical Activity Thermogenesis in Young Adults Using Synchronized Heart Rate and Accelerometry with Branched-Equation Modeling. J Nutr. 2006;136: 1037–1042. doi: 10.1093/jn/136.4.1037 16549471
38. Deschenes MR, Hillard MN, Wilson JA, Dubina MI, Eason MK. Effects of Gender on Physiological Responses during Submaximal Exercise and Recovery: Med Sci Sports Exerc. 2006;38: 1304–1310. doi: 10.1249/01.mss.0000227316.93351.56 16826028
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