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Jonghoon Park, Kazuko Ishikawa-Takata, Sachiko Tanaka, Kyoko Bessyo, Shigeho Tanaka and Toshihide Kimura

The purpose of this study was to examine the accuracy of uni- and triaxial accelerometers in monitoring step counts and gait intensity in older people who did or did not use an assistive device. Forty-nine healthy and frail older adults wore uniaxial (Lifecorder, Suzuken Co. Ltd.) and triaxial accelerometers (Activity Monitor, Matsushita Electronic Works, Ltd., and Active Style Pro, Omron Healthcare Co., Ltd.) during three trials at different gait speeds. All accelerometers gave relatively accurate step counts for healthy older participants compared with direct observation; however, the error was greater for frail older people with assistive devices. Gait intensity detection error was unaffected by gait speed. Among frail older people with assistive devices, the gait intensity error was smaller than for step count error. To accurately assess the steps walked or the gait intensity among frail older people using assistive devices, more study is needed on these groups of participants.

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Catrine Tudor-Locke, John M. Schuna Jr, Damon L. Swift, Amber T. Dragg, Allison B. Davis, Corby K. Martin, William D. Johnson and Timothy S. Church

meeting public health recommendations for physical activity. 13 By contrast, traditional Amish women average approximately 14,000 steps per day 14 and are considered “highly active.” 15 Systematic reviews of step-counting programs that have employed a step goal, 16 specifically a 10,000 steps per day

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James W. Navalta, Jeffrey Montes, Nathaniel G. Bodell, Charli D. Aguilar, Ana Lujan, Gabriela Guzman, Brandi K. Kam, Jacob W. Manning and Mark DeBeliso

, Sattar, & Lean, 2017 ). In order for individuals to truly attain their step goals, the ability to accurately determine step count becomes important. Wearable technology was rated as the top fitness trend the past two years ( Thompson, 2015 , 2016 ), and this tendency is expected to grow as the use of

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Lindsay P. Toth, Susan Park, Whitney L. Pittman, Damla Sarisaltik, Paul R. Hibbing, Alvin L. Morton, Cary M. Springer, Scott E. Crouter and David R. Bassett

Steps are an intuitive metric for assessing ambulatory physical activity ( Crespo, Keteyian, Heath, & Sempos, 1996 ; Siegel, Brackbill, & Heath, 1995 ; Simpson et al., 2003 ). In research, daily step counts have been used for physical activity surveillance ( Bassett, Wyatt, Thompson, Peters

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Brian M. Wood, Herman Pontzer, Jacob A. Harris, Audax Z.P. Mabulla, Marc T. Hamilton, Theodore W. Zderic, Bret A. Beheim and David A. Raichlen

advantages of each type of sensor ( Duncan, Badland, & Mummery, 2009 ). The methods described here were developed with such a goal in mind; that is, to permit us to synchronize accelerometers with GPS devices, and estimate step counts from GPS data. As part of our ongoing anthropological research with Hadza

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Jaclyn Megan Sions, Elisa Sarah Arch and John Robert Horne

is, pedometers and accelerometers, with varied weight, size, cost, commercial availability, and data resolution, have been shown to be reliable 28 and valid 29 , 30 for objectively assessing daily step counts among individuals with lower-limb amputations. Accelerometers, electromechanical devices

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Albert R. Mendoza, Kate Lyden, John Sirard, John Staudenmayer, Catrine Tudor-Locke and Patty S. Freedson

from the video and averaged. If there was a ≥ 5% difference between the two step count trials, the video was analyzed a third time and the average of the two closest total step counts was used for analysis. Two of 96 videos required a third measure. Training involved teaching observers how to identify

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Mhairi J. MacDonald, Samantha G. Fawkner, Ailsa G. Niven and David Rowe

adolescent population walking is a convenient alternative to active play and sports participation. To promote walking, researchers have sought to identify the required step count and step rate to achieve a health-enhancing number of steps and intensity of walking ( 1 , 3 , 24 , 30 , 35 ). In adults, 10

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Tiago V. Barreira, John P. Bennett and Minsoo Kang


To obtain validity evidence for the measurement of step counts by spring-levered and piezoelectric pedometers during dance.


Thirty-five adults in a college dance class participated in this study. Participants completed trials of 3- and 5-min of different styles of dance wearing Walk4life MVP and Omron HJ-303 pedometers, while their steps were visually counted. Pearson correlation, paired t-test, mean absolute percent error (MAPE), and mean bias were calculated between actual step and pedometer step counts for the 3- and 5-min dances separately.


For the Walk4life trials the correlations were .92 and .77 for the 3- and 5-min dances. No significant differences were shown by t-test for the 3- (P = .16) and 5-min dances (P = .60). However, MAPE was high, 17.7 ± 17.7% and 19.4 ± 18.3% for the 2 dance durations, respectively. For the Omron, the correlations were .44 and .58 for the 3- and 5-min dances, respectively. No significant differences were shown by t-test for the 3-min (P = .38) and for the 5-min (P = .88) dances. However, MAPE was high, 19.3 ± 16.4% and 26.6 ± 15.2% for the 2 dance durations, respectively.


This study demonstrated that pedometers can be used to estimate the number of steps taken by a group of college students while dancing, however caution is necessary with individual values.

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Michael Pereira da Silva, Fabio Eduardo Fontana, Eric Callahan, Oldemar Mazzardo and Wagner De Campos


The aim of this systematic review was to identify the most optimal step-count cutoff for children and adolescents (5–19 years old) among guidelines currently available in the literature.


The databases searched were PubMed, SportDiscus, Science Direct, Web of Science and LILACS. Studies were categorized into Health Cohort studies or Physical Activity (PA) Cohort studies according to the reference standard used. The quality of the studies was assessed using the QUADAS-2 instrument.


Six Health and 3 PA Cohort studies were included in the final pool of papers after Full Text reading. With the exception of a single study, studies demonstrated a high risk of methodological bias in at least 1 of the QUADAS-2 domains. Guidelines ranged from 10,000 to 16,000 steps/day for the Health studies (5–16 years old), and from 9,000 to 14,000 steps/day for PA studies (6–19 years old). Due to the high risk of methodological bias, none of the Health Cohort guidelines were endorsed. The PA Cohort study with the lowest risk of methodological bias suggested 12,000 steps/day for children and adolescents irrespective of gender.


PA Cohort studies demonstrated lower risk of methodological bias than Health Cohort studies. The optimal youth step-count guideline of 12,000 steps/day was endorsed.