Lindsay P Toth1, Susan Park1, Cary M Springer2, McKenzie D Feyerabend1, Jeremy A Steeves3, David R Bassett1. 1. Department of Kinesiology, Recreation, and Sport Studies, The University of Tennessee, Knoxville, TN. 2. Office of Information Technology, Research Computing Support, The University of Tennessee, Knoxville, TN. 3. Division of Education, Maryville College, Maryville, TN.
Abstract
PURPOSE: The purpose of this study was to determine the accuracy of 14-step counting methods under free-living conditions. METHODS: Twelve adults (mean ± SD age, 35 ± 13 yr) wore a chest harness that held a GoPro camera pointed down at the feet during all waking hours for 1 d. The GoPro continuously recorded video of all steps taken throughout the day. Simultaneously, participants wore two StepWatch (SW) devices on each ankle (all programmed with different settings), one activPAL on each thigh, four devices at the waist (Fitbit Zip, Yamax Digi-Walker SW-200, New Lifestyles NL-2000, and ActiGraph GT9X (AG)), and two devices on the dominant and nondominant wrists (Fitbit Charge and AG). The GoPro videos were downloaded to a computer and researchers counted steps using a hand tally device, which served as the criterion method. RESULTS: The SW devices recorded between 95.3% and 102.8% of actual steps taken throughout the day (P > 0.05). Eleven step counting methods estimated less than 100% of actual steps; Fitbit Zip, Yamax Digi-Walker SW-200, and AG with the moving average vector magnitude algorithm on both wrists recorded 71% to 91% of steps (P > 0.05), whereas the activPAL, New Lifestyles NL-2000, and AG (without low-frequency extension (no-LFE), moving average vector magnitude) worn on the hip, and Fitbit Charge recorded 69% to 84% of steps (P < 0.05). Five methods estimated more than 100% of actual steps; AG (no-LFE) on both wrists recorded 109% to 122% of steps (P > 0.05), whereas the AG (LFE) on both wrists and the hip recorded 128% to 220% of steps (P < 0.05). CONCLUSIONS: Across all waking hours of 1 d, step counts differ between devices. The SW, regardless of settings, was the most accurate method of counting steps.
PURPOSE: The purpose of this study was to determine the accuracy of 14-step counting methods under free-living conditions. METHODS: Twelve adults (mean ± SD age, 35 ± 13 yr) wore a chest harness that held a GoPro camera pointed down at the feet during all waking hours for 1 d. The GoPro continuously recorded video of all steps taken throughout the day. Simultaneously, participants wore two StepWatch (SW) devices on each ankle (all programmed with different settings), one activPAL on each thigh, four devices at the waist (Fitbit Zip, Yamax Digi-Walker SW-200, New Lifestyles NL-2000, and ActiGraph GT9X (AG)), and two devices on the dominant and nondominant wrists (Fitbit Charge and AG). The GoPro videos were downloaded to a computer and researchers counted steps using a hand tally device, which served as the criterion method. RESULTS: The SW devices recorded between 95.3% and 102.8% of actual steps taken throughout the day (P > 0.05). Eleven step counting methods estimated less than 100% of actual steps; Fitbit Zip, Yamax Digi-Walker SW-200, and AG with the moving average vector magnitude algorithm on both wrists recorded 71% to 91% of steps (P > 0.05), whereas the activPAL, New Lifestyles NL-2000, and AG (without low-frequency extension (no-LFE), moving average vector magnitude) worn on the hip, and Fitbit Charge recorded 69% to 84% of steps (P < 0.05). Five methods estimated more than 100% of actual steps; AG (no-LFE) on both wrists recorded 109% to 122% of steps (P > 0.05), whereas the AG (LFE) on both wrists and the hip recorded 128% to 220% of steps (P < 0.05). CONCLUSIONS: Across all waking hours of 1 d, step counts differ between devices. The SW, regardless of settings, was the most accurate method of counting steps.
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