IEEE J Biomed Health Inform - Estimating energy expenditure using body-worn accelerometers: a comparison of methods, sensors number and positioning.

Tópicos

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Resumo

Several methods to estimate energy expenditure (EE) using body-worn sensors exist; however, quantifications of the differences in estimation error are missing. In this paper, we compare three prevalent EE estimation methods and five body locations to provide a basis for selecting among methods, sensors number, and positioning. We considered 1) counts-based estimation methods, 2) activity-specific estimation methods using METs lookup, and 3) activity-specific estimation methods using accelerometer features. The latter two estimation methods utilize subsequent activity classification and EE estimation steps. Furthermore, we analyzed accelerometer sensors number and on-body positioning to derive optimal EE estimation results during various daily activities. To evaluate our approach, we implemented a study with 15 participants that wore five accelerometer sensors while performing a wide range of sedentary, household, lifestyle, and gym activities at different intensities. Indirect calorimetry was used in parallel to obtain EE reference data. Results show that activity-specific estimation methods using accelerometer features can outperform counts-based methods by 88% and activity-specific methods using METs lookup for active clusters by 23%. No differences were found between activity-specific methods using METs lookup and using accelerometer features for sedentary clusters. For activity-specific estimation methods using accelerometer features, differences in EE estimation error between the best combinations of each number of sensors (1 to 5), analyzed with repeated measures ANOVA, were not significant. Thus, we conclude that choosing the best performing single sensor does not reduce EE estimation accuracy compared to a five sensors system and can reliably be used. However, EE estimation errors can increase up to 80% if a nonoptimal sensor location is chosen.

Resumo Limpo

sever method estim energi expenditur ee use bodyworn sensor exist howev quantif differ estim error miss paper compar three preval ee estim method five bodi locat provid basi select among method sensor number posit consid countsbas estim method activityspecif estim method use met lookup activityspecif estim method use acceleromet featur latter two estim method util subsequ activ classif ee estim step furthermor analyz acceleromet sensor number onbodi posit deriv optim ee estim result various daili activ evalu approach implement studi particip wore five acceleromet sensor perform wide rang sedentari household lifestyl gym activ differ intens indirect calorimetri use parallel obtain ee refer data result show activityspecif estim method use acceleromet featur can outperform countsbas method activityspecif method use met lookup activ cluster differ found activityspecif method use met lookup use acceleromet featur sedentari cluster activityspecif estim method use acceleromet featur differ ee estim error best combin number sensor analyz repeat measur anova signific thus conclud choos best perform singl sensor reduc ee estim accuraci compar five sensor system can reliabl use howev ee estim error can increas nonoptim sensor locat chosen

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