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Kimberly Hannam, Kevin Deere, Sue Worrall, April Hartley and Jon H. Tobias

The purpose of this study was to establish the feasibility of using an aerobics class to produce potentially bone protective vertical impacts of ≥ 4g in older adults and to determine whether impacts can be predicted by physical function. Participants recruited from older adult exercise classes completed an SF-12 questionnaire, short physical performance battery, and an aerobics class with seven different components, performed at low and high intensity. Maximum g and jerk values were identified for each activity. Forty-one participants (mean 69 years) were included. Mean maximal values approached or exceeded the 4g threshold for four of the seven exercises. In multivariate analyses, age (−0.53; −0.77, −0.28) (standardized beta coefficient; 95% CI) and 4-m walk time (−0.39; −0.63, −0.16) were inversely related to maximum g. Aerobics classes can be used to produce relatively high vertical accelerations in older individuals, although the outcome is strongly dependent on age and physical function.

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Jonathan M. Williams, Michael Gara and Carol Clark

back or sacral area have high reported correlation with force plate measures of balance. 3 , 7 , 8 Although it is acknowledged that the 2 measurement techniques measure subtly different constructs of balance (sway of center of pressure vs sacral acceleration), their relationship suggests that

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Ignacio Perez-Pozuelo, Thomas White, Kate Westgate, Katrien Wijndaele, Nicholas J. Wareham and Soren Brage

acceleration signal, including the magnitude of movement and the orientation of the accelerometer with respect to gravity. Previous research using wrist accelerometry has described variation in population physical activity expressed predominantly as the activity-related acceleration magnitude. For example, da

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Jairo H. Migueles, Alex V. Rowlands, Florian Huber, Séverine Sabia and Vincent T. van Hees

science, and thanks to technological evolution towards smaller, cheaper, and power efficient sensors, accelerometers now tend to store ‘raw’ data for offline processing and analysis. The data recorded are typically expressed in gravitational acceleration ( g ) because this is the reference point for

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Matthew Pearce, Tom R.P. Bishop, Stephen Sharp, Kate Westgate, Michelle Venables, Nicholas J. Wareham and Søren Brage

; Wareham et al., 2003 ); and (4) mean wrist acceleration expressed in milli-g (ACC WRIST ) ( White et al., 2019 ). Target Criterion Values The gold-standard target criterion for assessing PAEE (kJ·day −1 ·kg −1 ) was the difference between total and resting energy expenditure as measured by the DLW method

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Erin Strutz, Raymond Browning, Stephanie Smith, Barbara Lohse and Leslie Cunningham-Sabo

, and duration of PA. 17 The GENEActiv ACC (Activinsights Ltd, Cambridge, UK) is one such device that collects raw (ie, not processed) acceleration data and allows for a user-determined sampling frequency ranging from 10 to 100 Hz. This waterproof, wrist-mounted device has been validated for use in

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Kevin C. Deere, Kimberly Hannam, Jessica Coulson, Alex Ireland, Jamie S. McPhee, Charlotte Moss, Mark H. Edwards, Elaine Dennison, Cyrus Cooper, Adrian Sayers, Matthijs Lipperts, Bernd Grimm and Jon H. Tobias

Physical activity (PA) may need to produce high impacts to be osteogenic. The aim of this study was to identify threshold(s) for defining high impact PA for future analyses in the VIBE (Vertical Impact and Bone in the Elderly) study, based on home recordings with triaxial accelerometers. Recordings were obtained from 19 Master Athlete Cohort (MAC; mean 67.6 years) and 15 Hertfordshire Cohort Study (HCS; mean 77.7 years) participants. Data cleaning protocols were developed to exclude artifacts. Accelerations expressed in g units were categorized into three bands selected from the distribution of positive Y-axis peak accelerations. Data were available for 6.6 and 4.4 days from MAC and HCS participants respectively, with approximately 14 hr recording daily. Three-fold more 0.5−1.0g impacts were observed in MAC versus HCS, 20-fold more 1.0−1.5g impacts, and 140-fold more impacts ≥ 1.5g. Our analysis protocol successfully distinguishes PA levels in active and sedentary older individuals.

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Kristin Suorsa, Anna Pulakka, Tuija Leskinen, Jaana Pentti, Andreas Holtermann, Olli J. Heinonen, Juha Sunikka, Jussi Vahtera and Sari Stenholm

acceleration data from wrist-worn accelerometers to enable data harmonization between studies using different accelerometer devices. However, only a few studies have analyzed raw acceleration data, such as Euclidean Norm Minus One (ENMO), and examined wrist accelerometer threshold values for estimating

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Patty Freedson

 al., 2017 ). When simply looking at magnitudes of acceleration (i.e., movement), as cut-points do, outcomes are likely approximating stationary time rather than sedentary time. For example, in a laboratory-based protocol, Bakrania et al. ( 2016 ) showed that hip- and wrist-worn raw acceleration cut

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Roel De Ridder, Julien Lebleu, Tine Willems, Cedric De Blaiser, Christine Detrembleur and Philip Roosen

, data fusion of linear acceleration (accelerometer) and angular velocity (gyroscope) combined in an inertial measurement unit (IMU) permits compensation. 3 Notwithstanding the closer the IMU is positioned to the point of contact (eg, on the shank) the better gait events can be correctly detected, 4