Literature DB >> 2733585

Assessment of energy expenditure by recording heart rate and body acceleration.

G A Meijer1, K R Westerterp, H Koper, F ten Hoor.   

Abstract

The feasibility of a portable accelerometer equipped with a three-directional sensor for the assessment of physical activity and the consequences for energy expenditure was examined under laboratory conditions and during normal daily life. Heart rate monitoring was also conducted to allow comparison of both techniques. In the laboratory study 16 healthy subjects performed a number of specified exercises within a range of activity levels that may be expected in normal life. Accelerometer output was compared with energy expenditure measured by continuous respirometry. A linear relationship was found between accelerometer output and energy expenditure for the pooled data. The standard error of estimate is 79.1 J.min-1.kg-1. In the field study four subjects were observed during a week under free living conditions. Energy expenditure was calculated from food intake registered over the whole period. Energy expenditure calculated from accelerometer output and heart rate exceeded the energy intake figures by 30% and 33%, respectively. Possible explanations for this discrepancy are discussed. Despite this discrepancy, accelerometer output appeared to correlate highly with energy intake (r = 0.99, P less than 0.025), which suggests accurate performance of the accelerometer under free living conditions. The heart rate method gave much poorer results in estimating individual energy expenditure.

Mesh:

Year:  1989        PMID: 2733585

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  13 in total

1.  Improvement of walking speed prediction by accelerometry and altimetry, validated by satellite positioning.

Authors:  O Perrin; P Terrier; Q Ladetto; B Merminod; Y Schutz
Journal:  Med Biol Eng Comput       Date:  2000-03       Impact factor: 2.602

2.  The effect of a 5-month endurance-training programme on physical activity: evidence for a sex-difference in the metabolic response to exercise.

Authors:  G A Meijer; G M Janssen; K R Westerterp; F Verhoeven; W H Saris; F ten Hoor
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1991

3.  Predicting energy expenditure from accelerometry counts in adolescent girls.

Authors:  Kathryn H Schmitz; Margarita Treuth; Peter Hannan; Robert McMurray; Kimberly B Ring; Diane Catellier; Russ Pate
Journal:  Med Sci Sports Exerc       Date:  2005-01       Impact factor: 5.411

Review 4.  Measurement of physical activity in children with particular reference to the use of heart rate and pedometry.

Authors:  A V Rowlands; R G Eston; D K Ingledew
Journal:  Sports Med       Date:  1997-10       Impact factor: 11.136

5.  Energy expenditure estimates of the Caltrac accelerometer for running, race walking, and stepping.

Authors:  P D Swan; W C Byrnes; E M Haymes
Journal:  Br J Sports Med       Date:  1997-09       Impact factor: 13.800

6.  Estimates for energy expenditure in free-living animals using acceleration proxies: A reappraisal.

Authors:  Rory P Wilson; Luca Börger; Mark D Holton; D Michael Scantlebury; Agustina Gómez-Laich; Flavio Quintana; Frank Rosell; Patricia M Graf; Hannah Williams; Richard Gunner; Lloyd Hopkins; Nikki Marks; Nathan R Geraldi; Carlos M Duarte; Rebecca Scott; Michael S Strano; Hermina Robotka; Christophe Eizaguirre; Andreas Fahlman; Emily L C Shepard
Journal:  J Anim Ecol       Date:  2019-06-27       Impact factor: 5.091

Review 7.  Estimating human energy expenditure: a review of techniques with particular reference to doubly labelled water.

Authors:  Philip Ainslie; Thomas Reilly; Klass Westerterp
Journal:  Sports Med       Date:  2003       Impact factor: 11.136

8.  Physical activity and energy expenditure in lean and obese adult human subjects.

Authors:  G A Meijer; K R Westerterp; A M van Hulsel; F ten Hoor
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1992

9.  Tri-axial dynamic acceleration as a proxy for animal energy expenditure; should we be summing values or calculating the vector?

Authors:  Lama Qasem; Antonia Cardew; Alexis Wilson; Iwan Griffiths; Lewis G Halsey; Emily L C Shepard; Adrian C Gleiss; Rory Wilson
Journal:  PLoS One       Date:  2012-02-17       Impact factor: 3.240

10.  Prediction of oxygen uptake dynamics by machine learning analysis of wearable sensors during activities of daily living.

Authors:  T Beltrame; R Amelard; A Wong; R L Hughson
Journal:  Sci Rep       Date:  2017-04-05       Impact factor: 4.379

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