Estimation of energy expenditure in adults with accelerometry and heart rate

被引:4
|
作者
Bazuelo-Ruiz, B. [1 ]
De Rosario, H. [2 ,3 ]
Dura-Gil, J. V. [2 ]
机构
[1] Univ Valencia, Dept Phys Educ & Sports, Valencia, Spain
[2] Univ Politecn Valencia, Inst Biomech Valencia, Valencia, Spain
[3] Biomed Res Networking Ctr Bioengn Biomat & Nanome, Healthcare Technol Grp, Valencia, Spain
关键词
Oxygen consumption; Lifestyle; ECG signals; Wearable device; PHYSICAL-ACTIVITY; PREDICTION; COST; VALIDATION; TREADMILL; ACCURACY; EQUATION; WALKING; RISK;
D O I
10.1016/j.scispo.2021.08.007
中图分类号
G8 [体育];
学科分类号
04 ; 0403 ;
摘要
Objectives. - Accurate determination of energy expenditure (EE) through accelerometry is relevant in the effectiveness of the PA programs. The mean amplitude deviation (MAD) is a good parameter to distinguish the intensity of physical activity. Here, the aims of the present study were twofold: a) to develop a new EE estimation equation using raw accelerometer data and heart rate, and b) to compare the oxygen consumption measured with the new equation developed and the most commonly used prediction equations in the literature in normal weight and overweight adults. Equipment and methods. - Twenty healthy adults (10 males and 10 females) wore a wearable device on the chest that integrates triaxial accelerometry and ECG signals. The test protocol consisted in 12 individualized intensities, 6 walking and 6 running speeds equally distributed. The correlation between MAD and measured oxygen consumption was investigated. Then, a new energy expenditure estimation equation was developed and compared with five formulas from the literature. Results. - Our results noted that MAD had a very high correlation (r = 0.937) with indirect calorimetry. The new equation developed had one of the two lowest mean absolute errors for both walking and running. Therefore, our equation appears to be suitable for both walking and running, for normal weight and overweight people. However, future studies should validate our new EE estimation equation with a wide range of population and field-based conditions. (c) 2022 L'Auteur(s). Publi ' e par Elsevier Masson SAS. Cet article est publi ' e en Open Access sous licence CC BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:431 / 437
页数:7
相关论文
共 50 条
  • [31] Energy Expenditure Estimation in Boys with Duchene Muscular Dystrophy using Accelerometer and Heart Rate Sensors
    Pande, Amit
    Casazza, Gretchen
    Nicorici, Alina
    Seto, Edmund
    Miyamoto, Sheridan
    Lange, Matthew
    Abresch, Ted
    Mohapatra, Prasant
    Han, Jay
    2014 IEEE Healthcare Innovation Conference (HIC), 2014, : 26 - 29
  • [32] Estimation of energy expenditure from heart rate measurements in cattle maintained under different conditions
    Brosh, A
    Aharoni, Y
    Degen, AA
    Wright, D
    Young, B
    JOURNAL OF ANIMAL SCIENCE, 1998, 76 (12) : 3054 - 3064
  • [33] Effect of BMI on Prediction of Accelerometry-Based Energy Expenditure in Youth
    Warolin, Joshua
    Carrico, Amanda R.
    Whitaker, Lauren E.
    Wang, Li
    Chen, Kong Y.
    Acra, Sari
    Buchowski, Maciej S.
    MEDICINE AND SCIENCE IN SPORTS AND EXERCISE, 2012, 44 (12) : 2428 - 2435
  • [34] Estimating energy expenditure from wrist and thigh accelerometry in free-living adults: a doubly labelled water study
    White, Tom
    Westgate, Kate
    Hollidge, Stefanie
    Venables, Michelle
    Olivier, Patrick
    Wareham, Nick
    Brage, Soren
    INTERNATIONAL JOURNAL OF OBESITY, 2019, 43 (11) : 2333 - 2342
  • [35] Assessment of energy expenditure during high intensity cycling and running using a heart rate and activity monitor in young active adults
    Klass, Malgorzata
    Faoro, Vitalie
    Carpentier, Alain
    PLOS ONE, 2019, 14 (11):
  • [36] A nonlinear mixed model approach to predict energy expenditure from heart rate
    Kortelainen, Lauri
    Helske, Jouni
    Finni, Taija
    Mehtatalo, Lauri
    Tikkanen, Olli
    Karkkainen, Salme
    PHYSIOLOGICAL MEASUREMENT, 2021, 42 (03)
  • [37] Energy Expenditure of Level Overground Walking in Young Adults: Comparison With Prediction Equations
    Xue, Jingjing
    Li, Shuo
    Wen, Rou
    Hong, Ping
    JOURNAL OF PHYSICAL ACTIVITY & HEALTH, 2021, 18 (08) : 965 - 972
  • [38] Using Smartphone Sensors for Improving Energy Expenditure Estimation
    Pande, Amit
    Zhu, Jindan
    Das, Aveek
    Zeng, Yunze
    Mohapatra, Prasant
    Han, Jay
    IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE, 2015, 3
  • [39] An evaluation of energy expenditure estimation by three activity monitors
    Ryan, Jennifer
    Gormley, John
    EUROPEAN JOURNAL OF SPORT SCIENCE, 2013, 13 (06) : 681 - 688
  • [40] Prediction of Energy Expenditure From Wrist Accelerometry in People With and Without Down Syndrome
    Agiovlasitis, Stamatis
    Motl, Robert W.
    Foley, John T.
    Fernhall, Bo
    ADAPTED PHYSICAL ACTIVITY QUARTERLY, 2012, 29 (02) : 179 - 190