Abstract
BackgroundWearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD.ObjectiveThis study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD.MethodsA total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots.ResultsParticipants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0%), 8 (8/628, 1.3%), and 30 (30/628, 4.8%) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8%), 14.7 (14.7/620, 2.4%), and 74.4 (74.4/598, 12.4%) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (–0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking.ConclusionsThe waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.
Highlights
Wearable motion sensors have been applied for monitoring and promoting free-living ambulatory physical activity based on the outcome of steps taken per unit time among people with Parkinson disease (PD) [1]
The study of motion sensor precision, in particular, requires longer bouts of walking, as step count recordings from motion sensors can be compromised over time by subtle gait disturbances [5] brought about by energetic fatigue that may occur in PD and other neurological diseases
This study examined the accuracy and precision of 3 common motion sensors (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR) for measuring actual steps taken during longer periods of overground and treadmill walking in people with PD
Summary
Wearable motion sensors have been applied for monitoring and promoting free-living ambulatory physical activity based on the outcome of steps taken per unit time among people with Parkinson disease (PD) [1] Such applications, require evidence supporting the accuracy and precision of the motion sensors for capturing actual steps taken as a metric of ambulation. We located 2 studies that have examined the accuracy and precision of motion sensors for capturing steps during relatively short 2-min periods of overground walking in patients with PD [2,3] Assessment during such a short bout of walking does not provide an accurate and precise measurement associated with the energy systems required for free-living, ambulatory physical activity in neurological diseases [4]. Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD
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