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Daily physical activity assessment with accelerometers: new insights and validation studies

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TLDR
There was a large variability in accelerometer output and their validity to assess daily physical activity and there is little evidence that adding other physiological measures such as heart rate significantly improves the estimation of energy expenditure.
Abstract
The field of application of accelerometry is diverse and ever expanding. Because by definition all physical activities lead to energy expenditure, the doubly labelled water (DLW) method as gold standard to assess total energy expenditure over longer periods of time is the method of choice to validate accelerometers in their ability to assess daily physical activities. The aim of this paper was to provide a systematic overview of all recent (2007-2011) accelerometer validation studies using DLW as the reference. The PubMed Central database was searched using the following keywords: doubly or double labelled or labeled water in combination with accelerometer, accelerometry, motion sensor, or activity monitor. Limits were set to include articles from 2007 to 2011, as earlier publications were covered in a previous review. In total, 38 articles were identified, of which 25 were selected to contain sufficient new data. Eighteen different accelerometers were validated. There was a large variability in accelerometer output and their validity to assess daily physical activity. Activity type recognition has great potential to improve the assessment of physical activity-related health outcomes. So far, there is little evidence that adding other physiological measures such as heart rate significantly improves the estimation of energy expenditure.

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Journal ArticleDOI

Evolution of accelerometer methods for physical activity research

TL;DR: A collaborative approach towards analytic methods is proposed to facilitate PA research, which requires a shift away from multiple independent calibration studies and makes the case for a distinction between PA represented by accelerometer-based devices and PA assessed by self-report.
Journal ArticleDOI

Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges

TL;DR: This survey discusses clear motivations and advantages of multi-sensor data fusion and particularly focuses on physical activity recognition, aiming at providing a systematic categorization and common comparison framework of the literature, by identifying distinctive properties and parameters affecting data fusion design choices at different levels.
Journal ArticleDOI

Age group comparability of raw accelerometer output from wrist- and hip-worn monitors.

TL;DR: Accelerometer outputs from AG and GA seem comparable when attached to the same body location in adults, whereas inconsistent differences are apparent between the two brands and placements in children, hence limiting the comparability between brands in this age group.
Journal ArticleDOI

Accelerometer-based measures in physical activity surveillance: current practices and issues

TL;DR: It appears that accelerometers still have limitations regarding generalisability, validity, comprehensiveness, simplicity, affordability, adaptability, between-study comparability and sustainability, and the widespread adoption of accelerometers specifically for large-scale PA surveillance systems may be premature.
References
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Journal ArticleDOI

Patient-focused endpoints in advanced cancer: criterion-based validation of accelerometer-based activity monitoring.

TL;DR: AM-systems provide valid estimates of body positions and transfers, but not step count, especially in non-self caring patients, but there is considerable variability in results, which is consistent, in part, with the inaccuracy in step count.
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Predicting physical activity energy expenditure using accelerometry in adults from sub-Sahara Africa.

TL;DR: The derived equations performed better than existing published equations in predicting PAEE from accelerometer counts in this population and, therefore, has important applications for monitoring population levels of total physical activity patterns.
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Comparison of equations for predicting energy expenditure from accelerometer counts in children

TL;DR: Examining the degree of agreement between three different prediction equations, when applied to data on physical activity in a large sample of children, found predicted physical activity energy expenditure (PAEE) differed substantially between equations, depending on time‐frame assumptions.
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Physical activity pattern and activity energy expenditure in healthy pregnant and non-pregnant Swedish women

TL;DR: Healthy moderately active Swedish women compensated for the increased energy costs of pregnancy by 0.9 MJ/24 h, mainly achieved by selecting less demanding activities and slower walking pace.
Journal ArticleDOI

Estimating Energy Expenditure With the RT3 Triaxial Accelerometer

TL;DR: The RT3 provided a relatively accurate assessment of free-living activity-related energy expenditure at the group level and generally underestimated total and activity- related energy expenditure compared to DLW.
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