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Wearable multisensor and total energy expenditure estimation in young, adult and institutionalized elderly individuals: validation and practical recommendation

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Purpose

Abstract

Older institutionalized individuals with reduced residual abilities are going to growth in number in the next years. Monitoring the daily energy expenditure may allow a correct dietary intake and an effective physical activity program, thus improving their life quality. Wearable multisensors (WMS) have been developed to estimate energy expenditure (EE), but, if not calibrated, their accuracy may become questionable. This study was aimed at evaluating WMS accuracy in EE estimation in institutionalized elderly people where individual calibration is difficult to perform.

Methods

Twenty-three participants (age 48 ± 27 years; body mass 66.6 ± 12.7 kg; stature 1.69 ± 0.11 m; mean ± SD) were divided in young (YNG, <30 years; n = 9), adult (AD, 30–60 years, n = 7), and institutionalized elderly (ELD, >60 years; n = 7) individuals. EE at two different exercise intensities during cycling with the upper (UA) or lower limbs (LL) and walking was measured by indirect calorimetry (IC) and estimated by WMS.

Results

Estimated EE was always significantly lower than in IC in YNG and AD (P < 0.05). WMS underestimated EE in all conditions and the error increased with physical activity intensity. In YNG and ELD the correlation coefficient between measured and estimated EE improved during walking (R = 0.61 and R = 0.34 in YNG and ELD, respectively). In AD the best correlation occurred during LL (R = 0.78).

Conclusions

Without individual calibration, WMS underestimated EE measured by IC during all physical activities, with the lower correlation coefficient in institutionalized individuals. An individual calibration of WMS seems to be mandatory to obtain accurate estimations of EE, especially in institutionalized elderly people.

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References

  1. Fiatarone MA, Marks EC, Ryan ND, Meredith CN, Lipsitz LA, Evans WJ (1990) High-intensity strength training in nonagenarians—effects on skeletal-muscle. JAMA 263(22):3029–3034. doi:10.1001/jama.263.22.3029

    Article  CAS  PubMed  Google Scholar 

  2. Venturelli M, Schena F, Richardson RS (2012) The role of exercise capacity in the health and longevity of centenarians. Maturitas 73(2):115–120. doi:10.1016/j.maturitas.2012.07.009

    Article  PubMed  PubMed Central  Google Scholar 

  3. Martien S, Seghers J, Boen F, Delecluse C (2015) Energy expenditure in institutionalized older adults: validation of SenseWear mini. Med Sci Sports Exerc 47(6):1265–1271. doi:10.1249/MSS.0000000000000529

    Article  PubMed  Google Scholar 

  4. Esposito F, Malgrati D, Veicsteinas A, Orizio C (1996) Time and frequency domain analysis of electromyogram and sound myogram in the elderly. Eur J Appl Physiol Occup Physiol 73(6):503–510

    Article  CAS  PubMed  Google Scholar 

  5. Pizzigalli L, Ahmaidi S, Rainoldi A (2014) Effects of sedentary condition and longterm physical activity on postural balance and strength responses in elderly subjects. Sport Sci Health 10(2):135–141

    Article  Google Scholar 

  6. Krol-Zielinska M, Kusy K, Zielinski J, Osinski W (2011) Physical activity and functional fitness in institutionalized vs. independently living elderly: a comparison of 70–80-year-old city-dwellers. Arch Gerontol Geriatr 53(1):e10–e16

    Article  PubMed  Google Scholar 

  7. Larsson L, Grimby G, Karlsson J (1979) Muscle strength and speed of movement in relation to age and muscle morphology. J Appl Physiol Respir Environ Exerc Physiol 46(3):451–456

    CAS  PubMed  Google Scholar 

  8. Demura S, Minami M, Nagasawa Y, Tada N, Matsuzawa J, Sato S (2003) Physical-fitness declines in older Japanese adults. J Aging Phys Activ 11(1):112–122

    Article  Google Scholar 

  9. Cooper JA, Manini TM, Paton CM, Yamada Y, Everhart JE, Cummings S, Mackey DC, Newman AB, Glynn NW, Tylavsky F, Harris T, Schoeller DA, Study HA (2013) Longitudinal change in energy expenditure and effects on energy requirements of the elderly. Nutr J 12:73. doi:10.1186/1475-2891-12-73

  10. Patterson RE, Frank LL, Kristal AR, White E (2004) A comprehensive examination of health conditions associated with obesity in older adults. Am J Prev Med 27(5):385–390. doi:10.1016/j.amepre.2004.08.001

    Article  PubMed  Google Scholar 

  11. Marcell TJ (2003) Sarcopenia: causes, consequences, and preventions. J Gerontol A Biol Sci Med Sci 58(10):M911–M916

    Article  PubMed  Google Scholar 

  12. Esposito F, Ce E, Gobbo M, Veicsteinas A, Orizio C (2005) Surface EMG and mechanomyogram disclose isokinetic training effects on quadriceps muscle in elderly people. Eur J Appl Physiol 94(5–6):549–557. doi:10.1007/s00421-005-1371-y

    Article  PubMed  Google Scholar 

  13. Esposito F, Reese V, Shabetai R, Wagner PD, Richardson RS (2011) Isolated quadriceps training increases maximal exercise capacity in chronic heart failure: the role of skeletal muscle convective and diffusive oxygen transport. J Am Coll Cardiol 58(13):1353–1362. doi:10.1016/j.jacc.2011.06.025

    Article  PubMed  PubMed Central  Google Scholar 

  14. Ainsworth B, Cahalin L, Buman M, Ross R (2015) The current state of physical activity assessment tools. Prog Cardiovasc Dis 57(4):387–395. doi:10.1016/j.pcad.2014.10.005

    Article  PubMed  Google Scholar 

  15. Shephard RJ, Aoyagi Y (2012) Measurement of human energy expenditure, with particular reference to field studies: an historical perspective. Eur J Appl Physiol 112(8):2785–2815. doi:10.1007/s00421-011-2268-6

    Article  PubMed  Google Scholar 

  16. Durkalec-Michalski KWM, Bajerska J, Jeszka J (2013) Comparison of accuracy of various non-calorimetric methods measuring energy expenditure at different intensities. Hum Mov 14(2):161–167

    Google Scholar 

  17. Crouter SE, Churilla JR, Bassett DR Jr (2006) Estimating energy expenditure using accelerometers. Eur J Appl Physiol 98(6):601–612. doi:10.1007/s00421-006-0307-5

    Article  PubMed  Google Scholar 

  18. Sylvia LG, Bernstein EE, Hubbard JL, Keating L, Anderson EJ (2014) Practical guide to measuring physical activity. J Acad Nutr Diet 114(2):199–208

    Article  PubMed  Google Scholar 

  19. Assah FK, Ekelund U, Brage S, Wright A, Mbanya JC, Wareham NJ (2011) Accuracy and validity of a combined heart rate and motion sensor for the measurement of free-living physical activity energy expenditure in adults in Cameroon. Int J Epidemiol 40(1):112–120

    Article  PubMed  Google Scholar 

  20. Rampichini SMG, Mameli C, Agnello L, Schneider L, Veictseinas A, Zuccotti GV (2015) Energy expenditure in obese children: evaluation of a new multisensor device. Sport Sci Health 11(3):305–312

    Article  Google Scholar 

  21. Elbelt U, Schuetz T, Hoffmann I, Pirlich M, Strasburger CJ, Lochs H (2010) Differences of energy expenditure and physical activity patterns in subjects with various degrees of obesity. Clin Nutr 29(6):766–772. doi:10.1016/j.clnu.2010.05.003

    Article  PubMed  Google Scholar 

  22. Ferguson T, Rowlands AV, Olds T, Maher C (2015) The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study. Int J Behav Nutr Phys Act 12:42. doi:10.1186/s12966-015-0201-9

  23. Al-Gindan YY, Hankey CR, Govan L, Gallagher D, Heymsfield SB, Lean ME (2015) Derivation and validation of simple anthropometric equations to predict adipose tissue mass and total fat mass with MRI as the reference method. Br J Nutr 114(11):1852–1867. doi:10.1017/S0007114515003670

    Article  CAS  PubMed  Google Scholar 

  24. Layec G, Venturelli M, Jeong EK, Richardson RS (2014) The validity of anthropometric leg muscle volume estimation across a wide spectrum: from able-bodied adults to individuals with a spinal cord injury. J Appl Physiol 116(9):1142–1147. doi:10.1152/japplphysiol.01120.2013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Brage S, Ekelund U, Brage N, Hennings MA, Froberg K, Franks PW, Wareham NJ (2007) Hierarchy of individual calibration levels for heart rate and accelerometry to measure physical activity. J Appl Physiol (1985) 103(2):682–692. doi:10.1152/japplphysiol.00092.2006

    Article  Google Scholar 

  26. Schofield WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39(Suppl 1):5–41

    PubMed  Google Scholar 

  27. Vernillo G, Savoldelli A, Pellegrini B, Schena F (2014) Evaluation of the SenseWear Mini Armband to assess energy expenditure during pole walking. Int J Sport Nutr Exerc Metab 24(5):565–569. doi:10.1123/ijsnem.2014-0075

    Article  PubMed  Google Scholar 

  28. Vernillo G, Savoldelli A, Pellegrini B, Schena F (2015) Validity of the SenseWear Armband to assess energy expenditure in graded walking. J Phys Act Health 12(2):178–183. doi:10.1123/jpah.2013-0437

    Article  PubMed  Google Scholar 

  29. Demura S, Yamada T (2008) Influence of high-intensity sustained exercise by the lower limbs on gait properties. Sport Sci Health 2(3):106–112

    Article  Google Scholar 

  30. Fan Y, Li Z, Han S, Lv C, Zhang B (2016) The influence of gait speed on the stability of walking among the elderly. Gait Posture 47:31–36. doi:10.1016/j.gaitpost.2016.02.018

    Article  PubMed  Google Scholar 

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Acknowledgments

Authors wish to acknowledge all the participant for their courtesy and collaboration. A special thank is headed to Dr. Ettore Mutti of Mons. Mazzali Foundation, and to Pietro Maio and Arianna Ongaro for their precious contribution to data collection and analysis.

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Authors and Affiliations

  1. Department of Biomedical Sciences for Health (SCIBIS), Università degli Studi di Milano, Via G. Colombo 71, 20133, Milan, Italy

    Susanna Rampichini, A. Fantauzzi, E. Cè, S. Longo, E. Limonta, A. V. Bisconti, F. Esposito & M. Venturelli

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  1. Susanna Rampichini
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  2. A. Fantauzzi
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  3. E. Cè
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  4. S. Longo
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  6. A. V. Bisconti
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  7. F. Esposito
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  8. M. Venturelli
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Correspondence to Susanna Rampichini.

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Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical Standards of the institutional or national research committee and with the 1964 Helsinki declaration and its later amendments or compatible ethical Standards. This article does not contain any studies with animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in this study.

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Rampichini, S., Fantauzzi, A., Cè, E. et al. Wearable multisensor and total energy expenditure estimation in young, adult and institutionalized elderly individuals: validation and practical recommendation. Sport Sci Health 12, 463–470 (2016). https://doi.org/10.1007/s11332-016-0321-x

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  • DOI: https://doi.org/10.1007/s11332-016-0321-x

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