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Proceedings of the 4th International ICST Conference on Pervasive Computing Technologies for Healthcare

DOI: 10.4108/icst.pervasivehealth2010.8879

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Comparison of accelerometer-based energy expenditure estimation algorithms

Proceedings article published in 2010 by Niall Twomey, Stephen Faul, William P. Marnane
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: policy unknown
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Postprint: policy unknown
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Data provided by SHERPA/RoMEO

Abstract

Many accelerometer-based energy expenditure estimation algorithms and platforms have been established in recent topical literature, and each boasts a high correlation against the gold standard in energy expenditure measurement, i.e. indirect calorimetry. The aim of this study was to implement a set of these algorithms, run them all over a common dataset and investigate the strengths and weaknesses associated with each. The algorithms were then ported to a SHIMMER device for a real time, mobile and non-invasive energy expenditure estimation solution. High correlations were found between the accelerometer-regressed energy expenditure estimates and the reference dataset both on a computer and SHIMMER-implementation of the algorithms.