Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment

Abstract Physical activity (PA) is one of the most efficient ways to prevent obesity and its associated diseases worldwide. In the USA, less than 10% of the adult population were able to meet the PA recommendations when accelerometers were used to assess PA habituation. Accelerometers significantly...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Ville Stenbäck, Juhani Leppäluoto, Nelli Leskelä, Linda Viitala, Erkki Vihriälä, Dominique Gagnon, Mikko Tulppo, Karl-Heinz Herzig
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/17f1d9f116b04195bf18220cbe46b9c1
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:17f1d9f116b04195bf18220cbe46b9c1
record_format	dspace
spelling	oai:doaj.org-article:17f1d9f116b04195bf18220cbe46b9c12021-12-02T18:37:11ZStep detection and energy expenditure at different speeds by three accelerometers in a controlled environment10.1038/s41598-021-97299-z2045-2322https://doaj.org/article/17f1d9f116b04195bf18220cbe46b9c12021-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97299-zhttps://doaj.org/toc/2045-2322Abstract Physical activity (PA) is one of the most efficient ways to prevent obesity and its associated diseases worldwide. In the USA, less than 10% of the adult population were able to meet the PA recommendations when accelerometers were used to assess PA habituation. Accelerometers significantly differ from each other in step recognition and do not reveal raw data. The aim of our study was to compare a novel accelerometer, Sartorio Xelometer, which enables to gather raw data, with existing accelerometers ActiGraph GT3X+ and activPAL in terms of step detection and energy expenditure estimation accuracy. 53 healthy subjects were divided into 2 cohorts (cohort 1 optimization; cohort 2 validation) and wore 3 accelerometers and performed an exercise routine consisting of the following speeds: 1.5, 3, 4.5, 9 and 10.5 km/h (6 km/h for 2nd cohort included). Data from optimization cohort was used to optimize Sartorio step detection algorithm. Actual taken steps were recorded with a video camera and energy expenditure (EE) was measured. To observe the similarity between video and accelerometer step counts, paired samples t test and intraclass correlation were used separately for step counts in different speeds and for total counts as well as EE estimations. In speeds of 1.5, 3, 4.5, 6, 9 and 10.5 km/h mean absolute percentage error (MAPE) % were 8.1, 3.5, 4.3, 4.2, 3.1 and 7.8 for the Xelometer, respectively (after optimization). For ActiGraph GT3X+ the MAPE-% were 96.93 (87.4), 34.69 (23.1), 2.13 (2.3), 1.96 (2.6) and 2.99 (3.8), respectively and for activPAL 6.55 (5.6), 1.59 (0.6), 0.81 (1.1), 10.60 (10.3) and 15.76 (13.8), respectively. Significant intraclass correlations were observed with Xelometer estimates and actual steps in all speeds. Xelometer estimated the EE with a MAPE-% of 30.3, activPAL and ActiGraph GT3X+ with MAPE percentages of 20.5 and 24.3, respectively. The Xelometer is a valid device for assessing step counts at different gait speeds. MAPE is different at different speeds, which is of importance when assessing the PA in obese subjects and elderly. EE estimates of all three devices were found to be inaccurate when compared with indirect calorimetry.Ville StenbäckJuhani LeppäluotoNelli LeskeläLinda ViitalaErkki VihriäläDominique GagnonMikko TulppoKarl-Heinz HerzigNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ville Stenbäck Juhani Leppäluoto Nelli Leskelä Linda Viitala Erkki Vihriälä Dominique Gagnon Mikko Tulppo Karl-Heinz Herzig Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment
description	Abstract Physical activity (PA) is one of the most efficient ways to prevent obesity and its associated diseases worldwide. In the USA, less than 10% of the adult population were able to meet the PA recommendations when accelerometers were used to assess PA habituation. Accelerometers significantly differ from each other in step recognition and do not reveal raw data. The aim of our study was to compare a novel accelerometer, Sartorio Xelometer, which enables to gather raw data, with existing accelerometers ActiGraph GT3X+ and activPAL in terms of step detection and energy expenditure estimation accuracy. 53 healthy subjects were divided into 2 cohorts (cohort 1 optimization; cohort 2 validation) and wore 3 accelerometers and performed an exercise routine consisting of the following speeds: 1.5, 3, 4.5, 9 and 10.5 km/h (6 km/h for 2nd cohort included). Data from optimization cohort was used to optimize Sartorio step detection algorithm. Actual taken steps were recorded with a video camera and energy expenditure (EE) was measured. To observe the similarity between video and accelerometer step counts, paired samples t test and intraclass correlation were used separately for step counts in different speeds and for total counts as well as EE estimations. In speeds of 1.5, 3, 4.5, 6, 9 and 10.5 km/h mean absolute percentage error (MAPE) % were 8.1, 3.5, 4.3, 4.2, 3.1 and 7.8 for the Xelometer, respectively (after optimization). For ActiGraph GT3X+ the MAPE-% were 96.93 (87.4), 34.69 (23.1), 2.13 (2.3), 1.96 (2.6) and 2.99 (3.8), respectively and for activPAL 6.55 (5.6), 1.59 (0.6), 0.81 (1.1), 10.60 (10.3) and 15.76 (13.8), respectively. Significant intraclass correlations were observed with Xelometer estimates and actual steps in all speeds. Xelometer estimated the EE with a MAPE-% of 30.3, activPAL and ActiGraph GT3X+ with MAPE percentages of 20.5 and 24.3, respectively. The Xelometer is a valid device for assessing step counts at different gait speeds. MAPE is different at different speeds, which is of importance when assessing the PA in obese subjects and elderly. EE estimates of all three devices were found to be inaccurate when compared with indirect calorimetry.
format	article
author	Ville Stenbäck Juhani Leppäluoto Nelli Leskelä Linda Viitala Erkki Vihriälä Dominique Gagnon Mikko Tulppo Karl-Heinz Herzig
author_facet	Ville Stenbäck Juhani Leppäluoto Nelli Leskelä Linda Viitala Erkki Vihriälä Dominique Gagnon Mikko Tulppo Karl-Heinz Herzig
author_sort	Ville Stenbäck
title	Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment
title_short	Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment
title_full	Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment
title_fullStr	Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment
title_full_unstemmed	Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment
title_sort	step detection and energy expenditure at different speeds by three accelerometers in a controlled environment
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/17f1d9f116b04195bf18220cbe46b9c1
work_keys_str_mv	AT villestenback stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment AT juhanileppaluoto stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment AT nellileskela stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment AT lindaviitala stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment AT erkkivihriala stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment AT dominiquegagnon stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment AT mikkotulppo stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment AT karlheinzherzig stepdetectionandenergyexpenditureatdifferentspeedsbythreeaccelerometersinacontrolledenvironment
_version_	1718377783902601216

Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment

Ejemplares similares