resolution and difficulty in assigning a single behavior type to the entire window ( Staudenmayer, Pober, Crouter, Bassett, & Freedson, 2009 ). Automatically segmenting the acceleration data allows for the creation of variable duration windows without the same compromises as fixed duration windows ( Noor
Joshua Twaites, Richard Everson, Joss Langford and Melvyn Hillsdon
Alex V. Rowlands, John M. Schuna Jr., Victoria H. Stiles and Catrine Tudor-Locke
Previous research has reported peak vertical acceleration and peak loading rate thresholds beneficial to bone mineral density (BMD). Such thresholds are difficult to translate into meaningful recommendations for physical activity. Cadence (steps/min) is a more readily interpretable measure of ambulatory activity.
To examine relationships between cadence, peak vertical acceleration and peak loading rate during ambulation and identify the cadence associated with previously reported bone-beneficial thresholds for peak vertical acceleration (4.9 g) and peak loading rate (43 BW/s).
Ten participants completed 8 trials each of: slow walking, brisk walking, slow running, and fast running. Acceleration data were captured using a GT3×+ accelerometer worn at the hip. Peak loading rate was collected via a force plate.
Strong relationships were identified between cadence and peak vertical acceleration (r = .96, P < .05) and peak loading rate (r = .98, P < .05). Regression analyses indicated cadences of 157 ± 12 steps/min (2.6 ± 0.2 steps/s) and 122 ± 10 steps/min (2.0 ± 0.2 steps/s) corresponded with the 4.9 g peak vertical acceleration and 43 BW/s peak loading rate thresholds, respectively.
Cadences ≥ 2.0 to 2.6 steps/s equate to acceleration and loading rate thresholds related to bone health. Further research is needed to investigate whether the frequency of daily occurrences of this cadence is associated with BMD.
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.
Erreka Gil-Rey, Kevin C. Deere, Sara Maldonado-Martín, Natalia Palacios-Samper, Agueda Azpeitia, Esteban M. Gorostiaga and Jon H. Tobias
belt around the waist. Each monitor was previously initialized at 50-Hz frequency, and raw acceleration files were downloaded in Actilife 6 ® full software (ActiGraph LLC). The acceleration of gravity (9.81 m/s 2 = 1g) was subtracted, expressed as Euclidean Norm Minus One, and initial values of the
Richard A. Schmidt
Yoshifumi Kijima, Ryoji Kiyama, Masaki Sekine, Toshiyo Tamura, Toshiro Fujimoto, Tetsuo Maeda and Tadasu Ohshige
methods ( Kobsar, Olson, Paranjape, Hadjistavropoulos, & Barden, 2014 ). A previous study analyzed the effect of age on acceleration of the trunk during walking and found that older adults had a lower gait regularity than did young adults ( Menz, 2003 ). Matsumoto et al. ( 2015 ) reported that regularity
Garrett M. Hester, Zachary K. Pope, Mitchel A. Magrini, Ryan J. Colquhoun, Alejandra Barrera-Curiel, Carlos A. Estrada, Alex A. Olmos and Jason M. DeFreitas
peak velocity (PV) and acceleration (sometimes termed rate of velocity development) of the knee extensors are negatively affected by age ( Thompson, Conchola, Palmer, & Stock, 2014 ; Wallace, Power, Rice, & Dalton, 2016 ). Similar to the effect of age on other rapid, time-sensitive measures (e
Dinesh John, Qu Tang, Fahd Albinali and Stephen Intille
have emphasized the need to standardize data collection, processing, and analyses using raw acceleration data and non-proprietary algorithms ( Wijndaele et al., 2015 ). However, inconsistency and transparency among popular research-grade devices ( John, Morton, Arguello, Lyden, & Bassett, 2018 ; John
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
Alex V. Rowlands, Tatiana Plekhanova, Tom Yates, Evgeny M. Mirkes, Melanie Davies, Kamlesh Khunti and Charlotte L. Edwardson
activity measurement has advanced significantly. With the release of non-proprietary raw acceleration monitors that are being incorporated in many large surveys globally, there is considerable potential for data harmonization. Given that physical inactivity is a leading risk factor for non