2019
DOI: 10.1002/acr2.11099
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Comparison of Physical Activity Measures Derived From the Fitbit Flex and the ActiGraph GT3X+ in an Employee Population With Chronic Knee Symptoms

Abstract: Objective. We examined the accuracy of data from an affordable personal monitor (Fitbit Flex) compared with that of data from a research-grade accelerometer worn simultaneously for 7 days; high accuracy would support substitution with this less-expensive personal activity monitor in future community-based arthritis research.Methods. Subjects (N = 35) with chronic knee symptoms were recruited for a pilot intervention study using Fitbits to increase physical activity in employees with chronic knee symptoms at an… Show more

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Cited by 30 publications
(29 citation statements)
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References 15 publications
(47 reference statements)
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“…This makes the interpretation of sedentary behaviour estimates difficult and may have skewed results. Wearable activity trackers may be useful in studies wanting to objectively measure time spent in autistic adults' physical activity and sedentary behaviour, due to their lower cost, accessibility, and low burden of wear (Semanik et al, 2020). Wearable activity trackers were used in three studies.…”
Section: Discussionmentioning
confidence: 99%
“…This makes the interpretation of sedentary behaviour estimates difficult and may have skewed results. Wearable activity trackers may be useful in studies wanting to objectively measure time spent in autistic adults' physical activity and sedentary behaviour, due to their lower cost, accessibility, and low burden of wear (Semanik et al, 2020). Wearable activity trackers were used in three studies.…”
Section: Discussionmentioning
confidence: 99%
“…Alongside the smartphone, other inertial sensors for consumer use are on the market (Fitbit) and allow activity detection. The comparison of these sensors with sensors used in the research community shows a good capability of consumer sensors for activity detection [ 116 ], but still less accurate than IMUs used in the research field which does not make it an adequate substitute for FLEs studies [ 117 ]. Furthermore, the lack of transparency and the difference in the algorithm used for step and activity detection with those sensors is a hindrance to the use of these sensors in the research community.…”
Section: Discussionmentioning
confidence: 99%
“…A proprietary algorithm converts the raw acceleration signal from the tracker into step counts and activity intensity. Each minute interval is categorized as sedentary (<1.5 metabolic equivalent tasks [METs] according to Fitbit), lightly active (1.5-3 METs), fairly active (3-6 METs), or very active (>6 METs or ≥145 steps/min in at least 10 min bouts) according to Fitbit’s determination of METs [ 30 ]. Data were collected continuously by the wrist-worn tracker for 30 days, at which point the device must be synchronized via Bluetooth with a smartphone and the Fitbit app.…”
Section: Methodsmentioning
confidence: 99%