scholarly journals Validity of the iPhone M7 Motion Coprocessor to Estimate Physical Activity During Structured and Free-Living Activities in Healthy Adults

2021 ◽  
pp. 1-8
Author(s):  
Nicola K. Thomson ◽  
Lauren McMichan ◽  
Eilidh Macrae ◽  
Julien S. Baker ◽  
David J. Muggeridge ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Body Movement ◽  
Primary Objective ◽  
Physical Activities ◽  
Healthy Adults ◽  
Treadmill Walking ◽  
Step Count ◽  
Free Living

Modern smartphones such as the iPhone contain an integrated accelerometer, which can be used to measure body movement and estimate the volume and intensity of physical activity. Objectives: The primary objective was to assess the validity of the iPhone to measure step count and energy expenditure during laboratory-based physical activities. A further objective was to compare free-living estimates of physical activity between the iPhone and the ActiGraph GT3X+ accelerometer. Methods: Twenty healthy adults wore the iPhone 5S and GT3X+ in a waist-mounted pouch during bouts of treadmill walking, jogging, and other physical activities in the laboratory. Step counts were manually counted, and energy expenditure was measured using indirect calorimetry. During two weeks of free-living, participants (n = 17) continuously wore a GT3X+ attached to their waist and were provided with an iPhone 5S to use as they would their own phone. Results: During treadmill walking, iPhone (703 ± 97 steps) and GT3X+ (675 ± 133 steps) provided accurate measurements of step count compared with the criterion method (700 ± 98 steps). Compared with indirect calorimetry (8 ± 3 kcal·min−1), the iPhone (5 ± 1 kcal·min−1) underestimated energy expenditure with poor agreement. During free-living, the iPhone (7,990 ± 4,673 steps·day−1) recorded a significantly lower (p < .05) daily step count compared with the GT3X+ (9,085 ± 4,647 steps·day−1). Conclusions: The iPhone accurately estimated step count during controlled laboratory walking but recorded a significantly lower volume of physical activity compared with the GT3X+ during free-living.

scholarly journals The Energy Expenditure of Free-Living Physical Activities in Primary Schoolchildren

2016 ◽  
Vol 13 (s1) ◽  
pp. S57-S61 ◽  
Author(s):  
Alison L. Innerd ◽  
Liane B. Azevedo
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Physical Activities ◽  
Free Living ◽  
Metabolic Equivalent ◽  
Primary Schoolchildren ◽  
Vigorous Intensity

Background:The aim of this study is to establish the energy expenditure (EE) of a range of child-relevant activities and to compare different methods of estimating activity MET.Methods:27 children (17 boys) aged 9 to 11 years participated. Participants were randomly assigned to 1 of 2 routines of 6 activities ranging from sedentary to vigorous intensity. Indirect calorimetry was used to estimate resting and physical activity EE. Activity metabolic equivalent (MET) was determined using individual resting metabolic rate (RMR), the Harrell-MET and the Schofield equation.Results:Activity EE ranges from 123.7± 35.7 J/min/Kg (playing cards) to 823.1 ± 177.8 J/min/kg (basketball). Individual RMR, the Harrell-MET and the Schofield equation MET prediction were relatively similar at light and moderate but not at vigorous intensity. Schofield equation provided a better comparison with the Compendium of Energy Expenditure for Youth.Conclusion:This information might be advantageous to support the development of a new Compendium of Energy Expenditure for Youth.

Stride Rate and Walking Intensity in Healthy Older Adults

2014 ◽  
Vol 22 (2) ◽  
pp. 276-283 ◽  
Author(s):  
Leslie Peacock ◽  
Allan Hewitt ◽  
David A. Rowe ◽  
Rona Sutherland
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Multilevel Model ◽  
Vigorous Physical Activity ◽  
Treadmill Walking ◽  
Overground Walking ◽  
Healthy Older Adults ◽  
Stride Rate

Purpose:The study investigated (a) walking intensity (stride rate and energy expenditure) under three speed instructions; (b) associations between stride rate, age, height, and walking intensity; and (c) synchronization between stride rate and music tempo during overground walking in a population of healthy older adults.Methods:Twenty-nine participants completed 3 treadmill-walking trials and 3 overground-walking trials at 3 self-selected speeds. Treadmill VO2 was measured using indirect calorimetry. Stride rate and music tempo were recorded during overground-walking trials.Results:Mean stride rate exceeded minimum thresholds for moderate to vigorous physical activity (MVPA) under slow (111.41 ± 11.93), medium (118.17 ± 11.43), and fast (123.79 ± 11.61) instructions. A multilevel model showed that stride rate, age, and height have a significant effect (p < .01) on walking intensity.Conclusions:Healthy older adults achieve MVPA with stride rates that fall below published minima for MVPA. Stride rate, age, and height are significant predictors of energy expenditure in this population. Music can be a useful way to guide walking cadence.

scholarly journals Activity Energy Expenditure in Youth: Sex, Age, and Body Size Patterns

2016 ◽  
Vol 13 (s1) ◽  
pp. S62-S70 ◽  
Author(s):  
Jung-Min Lee ◽  
Pedro F. Saint-Maurice ◽  
Youngwon Kim ◽  
Glenn A. Gaesser ◽  
Gregory Welk
Keyword(s):  
Physical Activity ◽  
Body Size ◽  
Energy Expenditure ◽  
Relative Intensity ◽  
Indirect Calorimetry ◽  
Physical Activities ◽  
Childhood And Adolescence ◽  
Energy Costs ◽  
Diverse Range ◽  
Activity Energy

Background:The assessment of physical activity (PA) and energy expenditure (EE) in youth is complicated by inherent variability in growth and maturation during childhood and adolescence. This study provides descriptive summaries of the EE of a diverse range of activities in children ages 7 to 13.Methods:A sample of 105 7- to 13-year-old children (boys: 57%, girls: 43%, and Age: 9.9 ± 1.9) performed a series of 12 activities from a pool of 24 activities while being monitored with an indirect calorimetry system.Results:Across physical activities, averages of VO2 ml·kg·min-1, VO2 L·min-1, EE, and METs ranged from 3.3 to 53.7 ml·kg·min-1, from 0.15 to 3.2 L·min-1, from 0.7 to 15.9 kcal·min-1, 1.5 MET to 7.8 MET, respectively.Conclusions:The energy costs of the activities varied by age, sex, and BMI status reinforcing the need to consider adjustments when examining the relative intensity of PA in youth.

Validation of the RT3 Accelerometer for Measuring Physical Activity of Children in Simulated Free-Living Conditions

2008 ◽  
Vol 20 (2) ◽  
pp. 181-197 ◽  
Author(s):  
David Xiaoqian Sun ◽  
Gordon Schmidt ◽  
Sock Miang Teo-Koh
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Oxygen Uptake ◽  
Metabolic Cost ◽  
Physical Activities ◽  
Living Conditions ◽  
Free Living ◽  
Outdoor Test ◽  
Activity Energy ◽  
Free Living Conditions

This is a validation study of the RT3 accelerometer for measuring physical activities of children in simulated free-living conditions. Twenty-five children age 12–14 years completed indoor testing, and 18 of them completed outdoor testing. Activity counts from the RT3 accelerometer estimated activity energy expenditure (AEE) and the Cosmed K4b2 analyzer measured oxygen uptake. Correlations were found between activity counts and metabolic cost (r = .95, p < .001), metabolic cost and RT3 estimated AEE (r = .96, p < .001) in the indoor test, activity counts and RT3 estimated AEE (r = .97, p < .001) in the outdoor test, and activity counts and metabolic cost when all activities were combined (r = .77, p < .001). Results indicate that the RT3 accelerometer might be used to provide acceptable estimates of free-living physical activity in children.

Validation of the Kenz Lifecorder EX and ActiGraph GT1M accelerometers for walking and running in adults

2008 ◽  
Vol 33 (6) ◽  
pp. 1155-1164 ◽  
Author(s):  
Mark G. Abel ◽  
James C. Hannon ◽  
Katie Sell ◽  
Tia Lillie ◽  
Geri Conlin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Walking Speed ◽  
Treadmill Walking ◽  
Activity Monitors ◽  
Step Counts ◽  
Equation Analysis ◽  
Walking Speeds ◽  
Activity Energy

Accelerometer-based activity monitors are commonly used by researchers and clinicians to assess physical activity. Recently, the Kenz Lifecorder EX (KL) and ActiGraph GT1M (AG) accelerometers have been made commercially available, but there is limited research on the validity of these devices. Therefore, we sought to validate step count, activity energy expenditure (EE), and total EE output from the KL and AG during treadmill walking and running. Ten male and 10 female participants performed 10 min treadmill walking and running trials, at speeds of 54, 80, 107, 134, 161, and 188 m·min–1. Step counts were hand tallied by 2 observers, and indirect calorimetry was used to validate the accelerometers’ estimates of EE. AG total EE was calculated using the Freedson equation. Analysis of variance (ANOVA) and Pearson’s correlations were used to analyze the data. At the slowest walking speed, the AG and KL counted 64% ± 15% and 92% ± 6% of the observed steps, respectively. At all other treadmill speeds, both activity monitors undercounted, compared with observed steps, by ≤3%. The KL underestimated activity EE at faster running speeds (p < 0.01), overestimated total EE at some walking speeds, and underestimated total EE at some running speeds (p < 0.01). The Freedson equation inaccurately measured total EE at most walking and running speeds. The KL and the AG are moderately priced accelerometers that provide researchers and clinicians with accurate estimates of step counts and activity EE at most walking and running speeds.

scholarly journals An Accelerometer-Based Earpiece to Monitor and Quantify Physical Activity

2009 ◽  
Vol 6 (6) ◽  
pp. 781-789 ◽  
Author(s):  
Chinmay Manohar ◽  
Shelly McCrady ◽  
Ioannis T. Pavlidis ◽  
James A. Levine
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Daily Activity ◽  
Free Living ◽  
Body Postures ◽  
Sensing Technology ◽  
Walking Velocity ◽  
Activity Sensing

Background:Physical activity is important in ill-health. Inexpensive, accurate and precise devices could help assess daily activity. We integrated novel activity-sensing technology into an earpiece used with portable music-players and phones; the physical-activity-sensing earpiece (PASE). Here we examined whether the PASE could accurately and precisely detect physical activity and measure its intensity and thence predict energy expenditure.Methods:Experiment 1: 18 subjects wore PASE with different body postures and during graded walking. Energy expenditure was measured using indirect calorimetry. Experiment 2: 8 subjects wore the earpiece and walked a known distance. Experiment 3: 8 subjects wore the earpiece and ‘jogged’ at 3.5mph.Results:The earpiece correctly distinguished lying from sitting/standing and distinguished standing still from walking (76/76 cases). PASE output showed excellent sequential increases with increased in walking velocity and energy expenditure (r2 > .9). The PASE prediction of free-living walking velocity was, 2.5 ± (SD) 0.18 mph c.f. actual velocity, 2.5 ± 0.16 mph. The earpiece successfully distinguished walking at 3.5 mph from ‘jogging’ at the same velocity (P < .001).Conclusions:The subjects tolerated the earpiece well and were comfortable wearing it. The PASE can therefore be used to reliably monitor free-living physical activity and its associated energy expenditure.

scholarly journals Youth Energy Expenditure During Common Free-Living Activities and Treadmill Walking

2016 ◽  
Vol 13 (s1) ◽  
pp. S29-S34 ◽  
Author(s):  
John M. Schuna ◽  
Tiago V. Barreira ◽  
Daniel S. Hsia ◽  
William D. Johnson ◽  
Catrine Tudor-Locke
Keyword(s):  
Energy Expenditure ◽  
Oxygen Uptake ◽  
Physical Activities ◽  
Treadmill Walking ◽  
Stair Climbing ◽  
Free Living ◽  
Metabolic Equivalents ◽  
Age Related ◽  
Age Trends ◽  
Age Range

Background:Energy expenditure (EE) estimates for a broad age range of youth performing a variety of activities are needed.Methods:106 participants (6–18 years) completed 6 free-living activities (seated rest, movie watching, coloring, stair climbing, basketball dribbling, jumping jacks) and up to 9 treadmill walking bouts (13.4 to 120.7 m/min; 13.4 m/min increments). Breath-by-breath oxygen uptake (VO2) was measured using the COSMED K4b2 and EE was quantified as youth metabolic equivalents (METy1:VO2/measured resting VO2, METy2:VO2/estimated resting VO2). Age trends were evaluated with ANOVA.Results:Seated movie watching produced the lowest mean METy1 (6- to 9-year-olds: 0.94 ± 0.13) and METy2 values (13- to 15-year-olds: 1.10 ± 0.19), and jumping jacks produced the highest mean METy1 (13- to 15-year-olds: 6.89 ± 1.47) and METy2 values (16- to 18-year-olds: 8.61 ± 2.03). Significant age-related variability in METy1 and METy2 were noted for 8 and 2 of the 15 evaluated activities, respectively.Conclusions:Descriptive EE data presented herein will augment the Youth Compendium of Physical Activities.

Energy Expenditure in Playground Games in Primary School Children Measured by Accelerometer and Heart Rate Monitors

2017 ◽  
Vol 27 (5) ◽  
pp. 467-474 ◽  
Author(s):  
Jorge Cañete García-Prieto ◽  
Vicente Martinez-Vizcaino ◽  
Antonio García-Hermoso ◽  
Mairena Sánchez-López ◽  
Natalia Arias-Palencia ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Energy Expenditure ◽  
Primary School ◽  
Correlation Coefficient ◽  
School Children ◽  
Indirect Calorimetry ◽  
Coefficient Of Variation ◽  
Primary School Children ◽  
Heart Rate Monitors

The aim of this study was to examine the energy expenditure (EE) measured using indirect calorimetry (IC) during playground games and to assess the validity of heart rate (HR) and accelerometry counts as indirect indicators of EE in children´s physical activity games. 32 primary school children (9.9 ± 0.6 years old, 19.8 ± 4.9 kg · m-2 BMI and 37.6 ± 7.2 ml · kg-1 · min-1 VO2max). Indirect calorimetry (IC), accelerometry and HR data were simultaneously collected for each child during a 90 min session of 30 playground games. Thirty-eight sessions were recorded in 32 different children. Each game was recorded at least in three occasions in other three children. The intersubject coefficient of variation within a game was 27% for IC, 37% for accelerometry and 13% for HR. The overall mean EE in the games was 4.2 ± 1.4 kcals · min-1 per game, totaling to 375 ± 122 kcals/per 90 min/session. The correlation coefficient between indirect calorimetry and accelerometer counts was 0.48 (p = .026) for endurance games and 0.21 (p = .574) for strength games. The correlation coefficient between indirect calorimetry and HR was 0.71 (p = .032) for endurance games and 0.48 (p = .026) for strength games. Our data indicate that both accelerometer and HR monitors are useful devices for estimating EE during endurance games, but only HR monitors estimates are accurate for endurance games.

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