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Validation of five minimally obstructive methods to estimate physical activity energy expenditure in young adults in semi-standardized settings. | LitMetric

AI Article Synopsis

  • This study compared the accuracy of five objective methods, including two new ones using accelerometry and activity recognition (Acti4), to measure total energy expenditure (EE) during various activities against a standard indirect calorimetry.
  • Fourteen participants performed a series of daily activities while their EE was measured, using different devices to track their physical activity levels alongside the calorimetry.
  • Results showed that the combination of a thigh-worn ActiGraph GT3X+ with Acti4 software was the most accurate in estimating EE, outperforming other methods and significantly improving estimation accuracy compared to traditional activity count-based approaches.

Article Abstract

We compared the accuracy of five objective methods, including two newly developed methods combining accelerometry and activity type recognition (Acti4), against indirect calorimetry, to estimate total energy expenditure (EE) of different activities in semi-standardized settings. Fourteen participants performed a standardized and semi-standardized protocol including seven daily life activity types, while having their EE measured by indirect calorimetry. Simultaneously, physical activity was quantified by an ActivPAL3, two ActiGraph GT3X+'s and an Actiheart. EE was estimated by the standard ActivPAL3 software (ActivPAL), ActiGraph GT3X+ (ActiGraph) and Actiheart (Actiheart), and by a combination of activity type recognition via Acti4 software and activity counts per minute (CPM) of either a hip- or thigh-worn ActiGraph GT3X+ (AGhip + Acti4 and AGthigh + Acti4). At group level, estimated physical activities EE by Actiheart (MSE = 2.05) and AGthigh + Acti4 (MSE = 0.25) were not significantly different from measured EE by indirect calorimetry, while significantly underestimated by ActiGraph, ActivPAL and AGhip + Acti4. AGthigh + Acti4 and Actiheart explained 77% and 45%, of the individual variations in measured physical activity EE by indirect calorimetry, respectively. This study concludes that combining accelerometer data from a thigh-worn ActiGraph GT3X+ with activity type recognition improved the accuracy of activity specific EE estimation against indirect calorimetry in semi-standardized settings compared to previously validated methods using CPM only.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435146PMC
http://dx.doi.org/10.3390/s150306133DOI Listing

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