Young children’s activity and sedentary time were simultaneously measured via the Actical method (i.e., Actical accelerometer and specific cut-points) and the ActiGraph method (i.e., ActiGraph accelerometer and specific cut-points) at both 15-s and 60-s epochs to explore possible differences between these 2 measurement approaches. For 7 consecutive days, participants (n = 23) wore both the Actical and ActiGraph side-by-side on an elastic neoprene belt. Device-specific cut-points were applied. Paired sample t tests were conducted to determine the differences in participants’ daily average activity levels and sedentary time (min/h) measured by the 2 devices at 15-s and 60-s time sampling intervals. Bland-Altman plots were used to examine agreement between Actical and ActiGraph accelerometers. Regardless of epoch length, Actical accelerometers reported significantly higher rates of sedentary time (15 s: 42.7 min/h vs 33.5 min/h; 60 s: 39.4 min/h vs 27.1 min/h). ActiGraph accelerometers captured significantly higher rates of moderate-to-vigorous physical activity (15 s: 9.2 min/h vs 2.6 min/h; 60 s: 8.0 min/h vs 1.27 min/h) and total physical activity (15 s: 31.7 min/h vs 22.3 min/h; 60 s: = 39.4 min/h vs 25.2 min/h) in comparison with Actical accelerometers. These results highlight the present accelerometry-related issues with interpretation of datasets derived from different monitors.
Leigh M. Vanderloo, Natascja A. Di Cristofaro, Nicole A. Proudfoot, Patricia Tucker and Brian W. Timmons
Kelli L. Cain, Edith Bonilla, Terry L. Conway, Jasper Schipperijn, Carrie M. Geremia, Alexandra Mignano, Jacqueline Kerr and James F. Sallis
difficult to establish a nonwear criterion that correctly differentiates true sedentary behavior from nonwear time. Further complicating the issue, ActiGraph (Pensacola, FL) introduced a new line of accelerometers in 2005 (referred to as GT models) that utilized a microelectromechanical system accelerometer
Marcin Straczkiewicz, Jacek Urbanek and Jaroslaw Harezlak
general-purpose data processing software (e.g., Matlab or R) or dedicated software provided by device manufacturer (e.g., ActiLife by ActiGraph) ( Brønd & Arvidsson, 2016 ; Skotte, Korshøj, Kristiansen, Hanisch, & Holtermann, 2014 ; Zhou et al., 2015 ). The downside of using software like Matlab or R
Katja Krustrup Pedersen, Esben Lykke Skovgaard, Ryan Larsen, Mikkel Stengaard, Søren Sørensen and Kristian Overgaard
Accelerometry is a widely used method for assessing quantity and quality of physical activity (PA), which is essential in all PA research ( Troiano, McClain, Brychta, & Chen, 2014 ). One of the more commonly used accelerometers in PA research is the ActiGraph, and this device has most frequently
Alex V. Rowlands, Tatiana Plekhanova, Tom Yates, Evgeny M. Mirkes, Melanie Davies, Kamlesh Khunti and Charlotte L. Edwardson
, Keane, Harrington, & Fitzgerald, 2017 ); and British Whitehall II Study ( Menai et al., 2017 ), ≅3750 participants. Of these, the Axivity was used in UK Biobank and the Breakthrough Generation Study, the ActiGraph in NHANES, and the GENEActiv in the remaining surveys. All surveys deployed monitors on
Emma L. J. Eyre, Jason Tallis, Susie Wilson, Lee Wilde, Liam Akhurst, Rildo Wanderleys and Michael J. Duncan
activities at specific intensities. Specifically, the ActiGraph, Actical, and Research Tracker 3 (RT3), which is an older model of the Research Tracker 6 (RT6), are the most commonly used accelerometers in physical activity research. Much research has examined the validity and reliability of different
Alexander H.K. Montoye, Jordana Dahmen, Nigel Campbell and Christopher P. Connolly
NL 2000 and Omron HJ-720) accurately measured steps at speeds from 2.0–3.5 miles/hour, whereas the other two (1 pedometer: Digiwalker SW-200; 1 accelerometer: ActiGraph GT3X) underestimated steps especially in the slower walking speeds. However, this study did not assess walking speeds <2.0 miles
Anne Martin, Mhairi McNeill, Victoria Penpraze, Philippa Dall, Malcolm Granat, James Y. Paton and John J. Reilly
The Actigraph is well established for measurement of both physical activity and sedentary behavior in children. The activPAL is being used increasingly in children, though with no published evidence on its use in free-living children to date. The present study compared the two monitors in preschool children. Children (n 23) wore both monitors simultaneously during waking hours for 5.6d and 10h/d. Daily mean percentage of time sedentary (nontranslocation of the trunk) was 74.6 (SD for the Actigraph and 78.9 (SD 4.3) for activPAL. Daily mean percentage of time physically active (light intensity physical activity plus MVPA) was 25.4 (SD for the Actigraph and 21.1 (SD 4.3) for the activPAL. Bland-Altman tests and paired t tests suggested small but statistically significant differences between the two monitors. Actigraph and activPAL estimates of sedentary behavior and physical activity in young children are similar at a group level.
Vitor Pires Lopes, Pedro Magalhães, José Bragada and Catarina Vasques
Several methods exist to asses and control physical intensity levels of subjects engaged in physical activities programs, accelerometry is a method that could be easily used in the field. The purposes were: to calibrate Actigraph in middle-aged to old obese/overweight and DM2 adult patients; and to determine the threshold counts for sedentary, light, moderate, and vigorous physical activity (PA).
Sample comprise 26 participants (62.6 ± 6.5 years of age) of both gender. Counts and VO2 were simultaneously assessed during: resting, seating, standing, walking at 2.5 km·h−1, 5 km·h−1, and 6 km·h−1. A hierarchical linear model was used to derive a regression equation between MET and counts. Receiver operating characteristics (ROC) analysis was used to define thresholds for PA levels.
The regression equation was: MET = 1.388400490262 + 0.001312683420044 (counts·min−1), r = .867. The threshold counts for sedentary-light, light-moderate and moderate-vigorous PA were: 200, 1240, 2400 counts·min−1 respectively.
The Actigraph is a valid and useful device for the assessment of the amount of time spent in each PA intensity levels in obese/overweight and DM2 middle-aged to old adult patients.
Mark Abel, James Hannon, Tia Lillie, Katie Sell, David Anderson and Geri Conlin
The Kenz Lifecorder EX (KL) is a relatively new, moderately priced, user friendly accelerometer that tracks step counts and time spent in various intensity classifications. Thus, the KL is an attractive instrument for researchers and the public. However, there is limited research comparing the KL’s output to other accelerometers during free-living conditions. Therefore the purpose of this study was to compare KL versus ActiGraph (AG) outputs of step counts and time spent in various intensity classifications during free-living conditions.
Ten men and 10 women volunteers wore an AG (right side) and 2 KL (right side: KL-R vs. left side: KL-L) accelerometers on their waistline during waking hours for one day.
KL-R vs. KL-L yielded similar physical activity (PA) output. The AG recorded fewer steps compared with KL-L (P = .002) but was similar to the KL-R. The KL-R and KL-L yielded lower estimates of accumulated time spent in moderate PA compared with most AG intensity derivations (P < .003). There were no differences between KL-R and KL-L vs. the AG for time spent in vigorous PA.
The KL provides similar estimates of step counts and time spent in vigorous PA compared with established AG intensity derivations.