Validity of the Apple iPhone®/iPod Touch® as an Accelerometer-Based Physical Activity Monitor: A Proof-of-Concept Study

2014 ◽  
Vol 11 (4) ◽  
pp. 759-769 ◽  
Author(s):  
Meaghan Nolan ◽  
J. Ross Mitchell ◽  
Patricia K. Doyle-Baker
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Proof Of Concept ◽  
Activity Type ◽  
Free Living ◽  
Ipod Touch ◽  
Future Studies ◽  
Metabolic Cart ◽  
E Mail ◽  
Accuracy Speed

Background:The popularity of smartphones has led researchers to ask if they can replace traditional tools for assessing free-living physical activity. Our purpose was to establish proof-of-concept that a smartphone could record acceleration during physical activity, and those data could be modeled to predict activity type (walking or running), speed (km·h−1), and energy expenditure (METs).Methods:An application to record and e-mail accelerations was developed for the Apple iPhone®/iPod Touch®. Twentyfive healthy adults performed treadmill walking (4.0 km·h−1 to 7.2 km·h−1) and running (8.1 km·h−1 to 11.3 km·h−1) wearing the device. Criterion energy expenditure measurements were collected via metabolic cart.Results:Activity type was classified with 99% accuracy. Speed was predicted with a bias of 0.02 km·h−1 (SEE: 0.57 km·h−1) for walking, –0.03 km·h−1 (SEE: 1.02 km·h−1) for running. Energy expenditure was predicted with a bias of 0.35 METs (SEE: 0.75 METs) for walking, –0.43 METs (SEE: 1.24 METs) for running.Conclusion:Our results suggest that an iPhone/iPod Touch can predict aspects of locomotion with accuracy similar to other accelerometer-based tools. Future studies may leverage this and the additional features of smartphones to improve data collection and compliance.

scholarly journals Towards a Portable Model to Discriminate Activity Clusters from Accelerometer Data

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4504 ◽  
Author(s):  
Petra Jones ◽  
Evgeny M. Mirkes ◽  
Tom Yates ◽  
Charlotte L. Edwardson ◽  
Mike Catt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cross Validation ◽  
Accelerometer Data ◽  
Activity Type ◽  
Free Living ◽  
Independent Dataset ◽  
Clustering Model ◽  
Activity Types ◽  
Unsupervised Approach ◽  
Viable Approach

Few methods for classifying physical activity from accelerometer data have been tested using an independent dataset for cross-validation, and even fewer using multiple independent datasets. The aim of this study was to evaluate whether unsupervised machine learning was a viable approach for the development of a reusable clustering model that was generalisable to independent datasets. We used two labelled adult laboratory datasets to generate a k-means clustering model. To assess its generalised application, we applied the stored clustering model to three independent labelled datasets: two laboratory and one free-living. Based on the development labelled data, the ten clusters were collapsed into four activity categories: sedentary, standing/mixed/slow ambulatory, brisk ambulatory, and running. The percentages of each activity type contained in these categories were 89%, 83%, 78%, and 96%, respectively. In the laboratory independent datasets, the consistency of activity types within the clusters dropped, but remained above 70% for the sedentary clusters, and 85% for the running and ambulatory clusters. Acceleration features were similar within each cluster across samples. The clusters created reflected activity types known to be associated with health and were reasonably robust when applied to diverse independent datasets. This suggests that an unsupervised approach is potentially useful for analysing free-living accelerometer data.

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.

scholarly journals Validity of hip-mounted uniaxial accelerometry with heart-rate monitoring vs. triaxial accelerometry in the assessment of free-living energy expenditure in young children: the IDEFICS Validation Study

2012 ◽  
Vol 113 (10) ◽  
pp. 1530-1536 ◽  
Author(s):  
Robert Ojiambo ◽  
Kenn Konstabel ◽  
Toomas Veidebaum ◽  
John Reilly ◽  
Vera Verbestel ◽  
...  
Keyword(s):  
Physical Activity ◽  
Heart Rate ◽  
Energy Expenditure ◽  
Young Children ◽  
Validation Study ◽  
Longitudinal Axis ◽  
Activity Level ◽  
Free Living ◽  
Model Combining ◽  
Sedentary Activities

One of the aims of Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants (IDEFICS) validation study is to validate field measures of physical activity (PA) and energy expenditure (EE) in young children. This study compared the validity of uniaxial accelerometry with heart-rate (HR) monitoring vs. triaxial accelerometry against doubly labeled water (DLW) criterion method for assessment of free-living EE in young children. Forty-nine European children (25 female, 24 male) aged 4–10 yr (mean age: 6.9 ± 1.5 yr) were assessed by uniaxial ActiTrainer with HR, uniaxial 3DNX, and triaxial 3DNX accelerometry. Total energy expenditure (TEE) was estimated using DLW over a 1-wk period. The longitudinal axis of both devices and triaxial 3DNX counts per minute (CPM) were significantly ( P < 0.05) associated with physical activity level (PAL; r = 0.51 ActiTrainer, r = 0.49 uniaxial-3DNX, and r = 0.42 triaxial Σ3DNX). Eight-six percent of the variance in TEE could be predicted by a model combining body mass (partial r2 = 71%; P < 0.05), CPM-ActiTrainer (partial r2 = 11%; P < 0.05), and difference between HR at moderate and sedentary activities (ModHR − SedHR) (partial r2 = 4%; P < 0.05). The SE of TEE estimate for ActiTrainer and 3DNX models ranged from 0.44 to 0.74 MJ/days or ∼7–11% of the average TEE. The SE of activity-induced energy expenditure (AEE) model estimates ranged from 0.38 to 0.57 MJ/day or 24–26% of the average AEE. It is concluded that the comparative validity of hip-mounted uniaxial and triaxial accelerometers for assessing PA and EE is similar.

scholarly journals Evaluations of Actiheart, IDEEA® and RT3 monitors for estimating activity energy expenditure in free-living women

2013 ◽  
Vol 2 ◽  
Author(s):  
Marie Löf ◽  
Hanna Henriksson ◽  
Elisabet Forsum
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Living Conditions ◽  
Reproductive Age ◽  
Women Of Reproductive Age ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Further Development ◽  
Activity Energy ◽  
Free Living Conditions

AbstractActivity energy expenditure (AEE) during free-living conditions can be assessed using devices based on different principles. To make proper comparisons of different devices' capacities to assess AEE, they should be evaluated in the same population. Thus, in the present study we evaluated, in the same group of subjects, the ability of three devices to assess AEE in groups and individuals during free-living conditions. In twenty women, AEE was assessed using RT3 (three-axial accelerometry) (AEERT3), Actiheart (a combination of heart rate and accelerometry) (AEEActi) and IDEEA (a multi-accelerometer system) (AEEIDEEA). Reference AEE (AEEref) was assessed using the doubly labelled water method and indirect calorimetry. Average AEEActi was 5760 kJ per 24 h and not significantly different from AEEref (5020 kJ per 24 h). On average, AEERT3 and AEEIDEEA were 2010 and 1750 kJ per 24 h lower than AEEref, respectively (P < 0·001). The limits of agreement (± 2 sd) were 2940 (Actiheart), 1820 (RT3) and 2650 (IDEEA) kJ per 24 h. The variance for AEERT3 was lower than for AEEActi (P = 0·006). The RT3 classified 60 % of the women in the correct activity category while the corresponding value for IDEEA and Actiheart was 30 %. In conclusion, the Actiheart may be useful for groups and the RT3 for individuals while the IDEEA requires further development. The results are likely to be relevant for a large proportion of Western women of reproductive age and demonstrate that the procedure selected to assess physical activity can greatly influence the possibilities to uncover important aspects regarding interactions between physical activity, diet and health.

scholarly journals Quantifying the free living energy exchanges of Arctic ungulates with stable isotopes

Rangifer ◽  
2000 ◽  
Vol 20 (2-3) ◽  
pp. 59 ◽  
Author(s):  
Paul Haggarty
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Energy Requirement ◽  
Ecological Impact ◽  
The Arctic ◽  
Unknown Parameters ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Energy Exchanges ◽  
Free Ranging

When natural diets meet an animal's requirement for energy, other essential nutrients will usually be supplied in amounts at least sufficient for survival. Knowledge of the energy requirements of free ranging species under typical conditions are important in assessing both their nutritional needs and their ecological impact. The doubly labelled water (DLW) method is currently the most promising objective field methodology for estimating free living energy expenditure but expenditure is only equal to the energy requirement when an animal is in energy balance. Reproduction and seasonal cycles of fat deposition and utilization represent significant components of the energy budget of arctic ungulates but the information gained in the course of a typical DLW study may be used to estimate processes such as milk output and fat storage and mobilization in order to predict requirements from expenditure. The DLW method has been exhaustively validated under highly controlled conditions and the introduction of innovations such as faecal sampling for the estimation of body water isotopic enrichment, the availability of appropriate correction factors and stoichiometrics for known sources of error, and iterative calculation of unknown parameters, have produced a methodology suitable for use in truly free ranging species. The few studies carried out so far in arctic ungulates indicate that previous predictions have generally underestimated the true level of expenditure, that there is considerable between animal variation in the level of expenditure and that this is largely determined by physical activity. The disadvantages of the DLW methodology are that it remains expensive and the isotope analysis is technically demanding. Furthermore, although DLW can provide an accurate value for free living energy expenditure, it is often important to have information on the individual components of expenditure, for example the relative contribution of physical activity and thermoregulatory thermogenesis, in order to interpret the values for overall expenditure. For these reasons the most valuable use of the DLW method in the field may be to validate factorial models and other approaches so that they may be used with confidence. Additional important information on the energy exchanges of free ranging animals may be obtained from other stable isotope methodologies. In addition to the use of the isotopes 2H and lsO in the DLW method, natural variations in the abundance of "C and 15N in the arctic environment may be exploited to study diet selection in truly free living arctic ungulates.

Free-living physical activity and energy expenditure of rural children and adolescents in the Nandi region of Kenya

2013 ◽  
Vol 40 (4) ◽  
pp. 318-323 ◽  
Author(s):  
Robert Ojiambo ◽  
Alexander R. Gibson ◽  
Kenn Konstabel ◽  
Daniel E. Lieberman ◽  
John R. Speakman ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Children And Adolescents ◽  
Rural Children ◽  
Free Living

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.

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