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Cited by 32Physical Activity and HealthContext-Aware Activity Recognition SystemsObesity, Physical Activity, Diet

Effects of Body Mass Index and Tilt Angle on Output of Two Wearable Activity Monitors

FEITO, YURI, BASSETT, DAVID R., TYO, BRIAN, THOMPSON, DIXIE L.·2011·Medicine & Science in Sports & Exercise
DOI 10.1249/mss.0b013e3181fefd40
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Abstract

UNLABELLED: Accelerometer-based activity monitors have been used to provide objective measures of physical activity and energy expenditure (EE) in free-living individuals. However, output from these devices has not been compared among normal, overweight, and obese individuals. PURPOSE: The purpose of this study was to examine the effects of body mass index (BMI) and device tilt angle on activity counts recorded by wearable monitors in a controlled laboratory setting. A secondary aim was to examine the effects of these variables on estimated EE. METHODS: Seventy-one healthy adults wore an Actical and an ActiGraph GT1M on the right and left hip, respectively, while walking at 40, 67, and 94 m·min. EE was measured by indirect calorimetry and compared with estimated values using published equations. Three-way repeated-measures ANOVA were used to examine differences in outcome variables (activity counts and EE) between speeds, BMI, and tilt angle for each device. RESULTS: No significant differences in activity counts were observed among BMI categories for either the Actical or ActiGraph (P>0.05). For the Actical, however, among those with an absolute tilt angle <10°, the obese group recorded higher activity counts than the normal weight group (P=0.01). Using the Heil two-regression model, the Actical overestimated EE by up to 35% at the intermediate speed and up to 12% at the fastest speed (P<0.001). The Freedson METs regression equation yielded closer estimates of EE than the Freedson kilocalorie regression equation. CONCLUSIONS: Our findings indicate that the Actical has limitations when comparing individuals with varying BMI and tilt angles in a controlled laboratory environment. The ActiGraph seems to be a more suitable device for making these comparisons.

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Authors
FEITO, Y., BASSETT, D. R., TYO, B., & THOMPSON, D. L.
Affiliations
  • University of Tennessee at Knoxville (US)
  • Barry University (US)
ORCID
Venue
Medicine & Science in Sports & Exercise
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2011-05
Volume
43
Issue
5
Pages
861-866
ISSN
0195-9131 (ISSN-L)
DOI
10.1249/mss.0b013e3181fefd40
OpenAlex
W2007787414
Cited by
32
References
24
Citations by year
2022: 1 · 2021: 4 · 2020: 1 · 2019: 3 · 2018: 3 · 2017: 1 · 2016: 6 · 2015: 1 · 2014: 3 · 2013: 2 · 2012: 6
FWCI
1.95
Type
journal article
Language
en
Open access
closed
Locations
  • Medicine & Science in Sports & Exercise (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Keywords
wearable activity trackers, accelerometer, body mass index, obesity, energy expenditure estimation, physical activity measurement, Actical, ActiGraph GT1M, walking speed
MeSH terms
Adult, Calorimetry, Energy Metabolism, Equipment Design, Exercise Test, Female, Humans, Male, Obesity, Body Mass Index, Walking, Overweight, Young Adult, Actigraphy

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