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A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study

BACKGROUND: Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. PURPOSE: To expand a previously published child/youth catalog of validity indices to include adults (21–40, 41–60 and 61–85 years of age) asses...

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Autores principales: Mora-Gonzalez, Jose, Gould, Zachary R., Moore, Christopher C., Aguiar, Elroy J., Ducharme, Scott W., Schuna, John M., Barreira, Tiago V., Staudenmayer, John, McAvoy, Cayla R., Boikova, Mariya, Miller, Taavy A., Tudor-Locke, Catrine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9461139/
https://www.ncbi.nlm.nih.gov/pubmed/36076265
http://dx.doi.org/10.1186/s12966-022-01350-9
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author Mora-Gonzalez, Jose
Gould, Zachary R.
Moore, Christopher C.
Aguiar, Elroy J.
Ducharme, Scott W.
Schuna, John M.
Barreira, Tiago V.
Staudenmayer, John
McAvoy, Cayla R.
Boikova, Mariya
Miller, Taavy A.
Tudor-Locke, Catrine
author_facet Mora-Gonzalez, Jose
Gould, Zachary R.
Moore, Christopher C.
Aguiar, Elroy J.
Ducharme, Scott W.
Schuna, John M.
Barreira, Tiago V.
Staudenmayer, John
McAvoy, Cayla R.
Boikova, Mariya
Miller, Taavy A.
Tudor-Locke, Catrine
author_sort Mora-Gonzalez, Jose
collection PubMed
description BACKGROUND: Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. PURPOSE: To expand a previously published child/youth catalog of validity indices to include adults (21–40, 41–60 and 61–85 years of age) assessed across a range of treadmill speeds (slow [0.8–3.2 km/h], normal [4.0–6.4 km/h], fast [7.2–8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist). METHODS: Two hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015–2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV). RESULTS: Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045). CONCLUSIONS: Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy. TRIAL REGISTRATION: Clinicaltrials.gov NCT02650258. Registered 24 December 2015. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12966-022-01350-9.
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spelling pubmed-94611392022-09-10 A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study Mora-Gonzalez, Jose Gould, Zachary R. Moore, Christopher C. Aguiar, Elroy J. Ducharme, Scott W. Schuna, John M. Barreira, Tiago V. Staudenmayer, John McAvoy, Cayla R. Boikova, Mariya Miller, Taavy A. Tudor-Locke, Catrine Int J Behav Nutr Phys Act Research BACKGROUND: Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. PURPOSE: To expand a previously published child/youth catalog of validity indices to include adults (21–40, 41–60 and 61–85 years of age) assessed across a range of treadmill speeds (slow [0.8–3.2 km/h], normal [4.0–6.4 km/h], fast [7.2–8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist). METHODS: Two hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015–2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV). RESULTS: Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045). CONCLUSIONS: Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy. TRIAL REGISTRATION: Clinicaltrials.gov NCT02650258. Registered 24 December 2015. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12966-022-01350-9. BioMed Central 2022-09-08 /pmc/articles/PMC9461139/ /pubmed/36076265 http://dx.doi.org/10.1186/s12966-022-01350-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Mora-Gonzalez, Jose
Gould, Zachary R.
Moore, Christopher C.
Aguiar, Elroy J.
Ducharme, Scott W.
Schuna, John M.
Barreira, Tiago V.
Staudenmayer, John
McAvoy, Cayla R.
Boikova, Mariya
Miller, Taavy A.
Tudor-Locke, Catrine
A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study
title A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study
title_full A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study
title_fullStr A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study
title_full_unstemmed A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study
title_short A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study
title_sort catalog of validity indices for step counting wearable technologies during treadmill walking: the cadence-adults study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9461139/
https://www.ncbi.nlm.nih.gov/pubmed/36076265
http://dx.doi.org/10.1186/s12966-022-01350-9
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