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How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study

BACKGROUND: Smartphones have great potential for monitoring physical activity. Although a previous laboratory-based study reported that smartphone apps were accurate for tracking step counts, little evidence on their accuracy in free-living conditions currently exists. OBJECTIVE: We aimed to investi...

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Autores principales: Amagasa, Shiho, Kamada, Masamitsu, Sasai, Hiroyuki, Fukushima, Noritoshi, Kikuchi, Hiroyuki, Lee, I-Min, Inoue, Shigeru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329418/
https://www.ncbi.nlm.nih.gov/pubmed/30626569
http://dx.doi.org/10.2196/10418
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author Amagasa, Shiho
Kamada, Masamitsu
Sasai, Hiroyuki
Fukushima, Noritoshi
Kikuchi, Hiroyuki
Lee, I-Min
Inoue, Shigeru
author_facet Amagasa, Shiho
Kamada, Masamitsu
Sasai, Hiroyuki
Fukushima, Noritoshi
Kikuchi, Hiroyuki
Lee, I-Min
Inoue, Shigeru
author_sort Amagasa, Shiho
collection PubMed
description BACKGROUND: Smartphones have great potential for monitoring physical activity. Although a previous laboratory-based study reported that smartphone apps were accurate for tracking step counts, little evidence on their accuracy in free-living conditions currently exists. OBJECTIVE: We aimed to investigate the accuracy of step counts measured using iPhone in the real world. METHODS: We recruited a convenience sample of 54 adults (mean age 31 [SD 10] years) who owned an iPhone and analyzed data collected in 2016 and 2017. Step count was simultaneously measured using a validated pedometer (Kenz Lifecorder) and the iPhone. Participants were asked to carry and use their own iPhones as they typically would while wearing a pedometer on the waist for 7 consecutive days during waking hours. To assess the agreement between the two measurements, we calculated Spearman correlation coefficients and prepared a Bland-Altman plot. RESULTS: The mean step count measured using the iPhone was 9253 (3787) steps per day, significantly lower by 12% (1277/10,530) than that measured using the pedometer, 10,530 (3490) steps per day (P<.001). The Spearman correlation coefficient between devices was 0.78 (P<.001). The largest underestimation of steps by the iPhone was observed among those who reported to have seldom carried their iPhones (seldom carry: mean −3036, SD 2990, steps/day; sometimes carry: mean −1424, SD 2619, steps/day; and almost always carry: mean −929, SD 1443, steps/day; P for linear trend=.08). CONCLUSIONS: Smartphones may be of practical use to individuals, clinicians, and researchers for monitoring physical activity. However, their data on step counts should be interpreted cautiously because of the possibility of underestimation due to noncarrying time.
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spelling pubmed-63294182019-02-11 How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study Amagasa, Shiho Kamada, Masamitsu Sasai, Hiroyuki Fukushima, Noritoshi Kikuchi, Hiroyuki Lee, I-Min Inoue, Shigeru JMIR Mhealth Uhealth Short Paper BACKGROUND: Smartphones have great potential for monitoring physical activity. Although a previous laboratory-based study reported that smartphone apps were accurate for tracking step counts, little evidence on their accuracy in free-living conditions currently exists. OBJECTIVE: We aimed to investigate the accuracy of step counts measured using iPhone in the real world. METHODS: We recruited a convenience sample of 54 adults (mean age 31 [SD 10] years) who owned an iPhone and analyzed data collected in 2016 and 2017. Step count was simultaneously measured using a validated pedometer (Kenz Lifecorder) and the iPhone. Participants were asked to carry and use their own iPhones as they typically would while wearing a pedometer on the waist for 7 consecutive days during waking hours. To assess the agreement between the two measurements, we calculated Spearman correlation coefficients and prepared a Bland-Altman plot. RESULTS: The mean step count measured using the iPhone was 9253 (3787) steps per day, significantly lower by 12% (1277/10,530) than that measured using the pedometer, 10,530 (3490) steps per day (P<.001). The Spearman correlation coefficient between devices was 0.78 (P<.001). The largest underestimation of steps by the iPhone was observed among those who reported to have seldom carried their iPhones (seldom carry: mean −3036, SD 2990, steps/day; sometimes carry: mean −1424, SD 2619, steps/day; and almost always carry: mean −929, SD 1443, steps/day; P for linear trend=.08). CONCLUSIONS: Smartphones may be of practical use to individuals, clinicians, and researchers for monitoring physical activity. However, their data on step counts should be interpreted cautiously because of the possibility of underestimation due to noncarrying time. JMIR Publications 2019-01-09 /pmc/articles/PMC6329418/ /pubmed/30626569 http://dx.doi.org/10.2196/10418 Text en ©Shiho Amagasa, Masamitsu Kamada, Hiroyuki Sasai, Noritoshi Fukushima, Hiroyuki Kikuchi, I-Min Lee, Shigeru Inoue. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 09.01.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Short Paper
Amagasa, Shiho
Kamada, Masamitsu
Sasai, Hiroyuki
Fukushima, Noritoshi
Kikuchi, Hiroyuki
Lee, I-Min
Inoue, Shigeru
How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study
title How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study
title_full How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study
title_fullStr How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study
title_full_unstemmed How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study
title_short How Well iPhones Measure Steps in Free-Living Conditions: Cross-Sectional Validation Study
title_sort how well iphones measure steps in free-living conditions: cross-sectional validation study
topic Short Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329418/
https://www.ncbi.nlm.nih.gov/pubmed/30626569
http://dx.doi.org/10.2196/10418
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