Energy expenditure estimation from respiration variables

被引:12
|
作者
Gilgen-Ammann, Rahel [1 ]
Koller, Marcel [1 ]
Huber, Celine [1 ]
Ahola, Riikka [2 ]
Korhonen, Topi [2 ]
Wyss, Thomas [1 ]
机构
[1] SFISM, Magglingen, Switzerland
[2] Polar Electro, Kempele, Finland
来源
SCIENTIFIC REPORTS | 2017年 / 7卷
关键词
PHYSICAL-ACTIVITY; HEART-RATE; ACCELEROMETER DATA; PREDICTION; VALIDITY; VENTILATION; VALIDATION; RELIABILITY; EXERCISE; MODEL;
D O I
10.1038/s41598-017-16135-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The aim of this study was to develop and cross-validate two models to estimate total energy expenditure (TEE) based on respiration variables in healthy subjects during daily physical activities. Ninety-nine male and female subjects systematically varying in age (18-60 years) and body mass index (BMI; 17-36 kg*m(-2)) completed eleven aerobic activities with a portable spirometer as the criterion measure. Two models were developed using linear regression analyses with the data from 67 randomly selected subjects (50.0% female, 39.9 +/- 11.8 years, 25.1 +/- 5.2 kg*m-2). The models were cross-validated with the other 32 subjects (49% female, 40.4 +/- 10.7 years, 24.7 +/- 4.6 kg*m(-2)) by applying equivalence testing and Bland-and-Altman analyses. Model 1, estimating TEE based solely on respiratory volume, respiratory rate, and age, was significantly equivalent to the measured TEE with a systematic bias of 0.06 kJ*min(-1) (0.22%) and limits of agreement of +/- 6.83 kJ*min(-1). Model 1 was as accurate in estimating TEE as Model 2, which incorporated further information on activity categories, heart rate, sex, and BMI. The results demonstrated that respiration variables and age can be used to accurately determine daily TEE for different types of aerobic activities in healthy adults across a broad range of ages and body sizes.
引用
收藏
页数:7
相关论文
共 50 条
  • [21] A new method to estimate energy expenditure from abdominal and rib cage distances
    Gastinger, S.
    Sefati, H.
    Nicolas, G.
    Sorel, A.
    Gratas-Delamarche, A.
    Prioux, J.
    EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY, 2011, 111 (11) : 2823 - 2835
  • [22] Physical Capacity and Energy Expenditure of Cavers
    Pinna, Virginia
    Magnani, Sara
    Sainas, Gianmarco
    Ghiani, Giovanna
    Vanni, Samuele
    Olla, Sergio
    Marini, Elisabetta
    Curreli, Nicoletta
    Cabras, Stefano
    Farinatti, Paulo
    Antoni, Giorgia
    Tocco, Filippo
    Rinaldi, Andrea C.
    Crisafulli, Antonio
    FRONTIERS IN PHYSIOLOGY, 2017, 8
  • [23] Energy Expenditure Estimation in Children, Adolescents and Adults by Using a Respiratory Magnetometer Plethysmography System and a Deep Learning Model
    Zhou, Fenfen
    Yin, Xiaojian
    Hu, Rui
    Houssein, Aya
    Gastinger, Steven
    Martin, Brice
    Li, Shanshan
    Prioux, Jacques
    NUTRIENTS, 2022, 14 (19)
  • [24] Validity of energy expenditure estimation methods during 10 days of military training
    Siddall, Andrew G.
    Powell, Steven D.
    Needham-Beck, Sarah C.
    Edwards, Victoria C.
    Thompson, Jane E. S.
    Kefyalew, Sarah S.
    Singh, Priya A.
    Orford, Elise R.
    Venables, Michelle C.
    Jackson, Sarah
    Greeves, Julie P.
    Blacker, Sam D.
    Myers, Steve D.
    SCANDINAVIAN JOURNAL OF MEDICINE & SCIENCE IN SPORTS, 2019, 29 (09) : 1313 - 1321
  • [25] Accelerometer Data Processing and Energy Expenditure Estimation in Preschoolers
    Migueles, Jairo H.
    Nystrom, Christine Delisle
    Henriksson, Pontus
    Cadenas-Sanchez, Cristina
    Ortega, Francisco B.
    Lof, Marie
    MEDICINE AND SCIENCE IN SPORTS AND EXERCISE, 2019, 51 (03) : 590 - 598
  • [26] 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
  • [27] Improving energy expenditure estimation by using a triaxial accelerometer
    Chen, KY
    Sun, M
    JOURNAL OF APPLIED PHYSIOLOGY, 1997, 83 (06) : 2112 - 2122
  • [28] EPOC aware Energy Expenditure Estimation with Machine Learning
    Kim, Soijee
    Lee, Kyoungwoo
    Lee, Junga
    Jeon, Justin Y.
    2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2016, : 1585 - 1590
  • [29] A Survey on Energy Expenditure Estimation Using Wearable Devices
    Alvarez-Garcia, Juan A.
    Cvetkovic, Bozidara
    Lustrek, Mitja
    ACM COMPUTING SURVEYS, 2020, 53 (05)
  • [30] Estimation of metabolic energy expenditure from core temperature using a human thermoregulatory model
    Welles, Alexander P.
    Buller, Mark J.
    Looney, David P.
    Rumpler, William V.
    Gribok, Andrei V.
    Hoyt, Reed W.
    JOURNAL OF THERMAL BIOLOGY, 2018, 72 : 44 - 52