been used while worn on the hip ( Migueles et al., 2017 ). However, the optimal placement for this and other accelerometers remains unknown, but may depend on the type and intensity of the activity of interest ( Allahbakhshi, Hinrichs, Huang, & Weibel, 2019 ). For example, thigh-mounted accelerometers
Katja Krustrup Pedersen, Esben Lykke Skovgaard, Ryan Larsen, Mikkel Stengaard, Søren Sørensen and Kristian Overgaard
Christiana M.T. van Loo, Anthony D. Okely, Marijka Batterham, Tina Hinkley, Ulf Ekelund, Soren Brage, John J. Reilly, Gregory E. Peoples, Rachel Jones, Xanne Janssen and Dylan P. Cliff
To validate the activPAL3 algorithm for predicting metabolic equivalents (TAMETs) and classifying MVPA in 5- to 12-year-old children.
Fifty-seven children (9.2 ± 2.3y, 49.1% boys) completed 14 activities including sedentary behaviors (SB), light (LPA) and moderate-to-vigorous physical activities (MVPA). Indirect calorimetry (IC) was used as the criterion measure. Analyses included equivalence testing, Bland-Altman procedures and area under the receiver operating curve (ROC-AUC).
At the group level, TAMETs were significantly equivalent to IC for handheld e-game, writing/coloring, and standing class activity (P < .05). Overall, TAMETs were overestimated for SB (7.9 ± 6.7%) and LPA (1.9 ± 20.2%) and underestimated for MVPA (27.7 ± 26.6%); however, classification accuracy of MVPA was good (ROC-AUC = 0.86). Limits of agreement were wide for all activities, indicating large individual error (SB: −27.6% to 44.7%; LPA: −47.1% to 51.0%; MVPA: −88.8% to 33.9%).
TAMETs were accurate for some SB and standing, but were overestimated for overall SB and LPA, and underestimated for MVPA. Accuracy for classifying MVPA was, however, acceptable.
Yoshifumi Kijima, Ryoji Kiyama, Masaki Sekine, Toshiyo Tamura, Toshiro Fujimoto, Tetsuo Maeda and Tadasu Ohshige
bilateral thigh could estimate whether a stroke patient could walk independently or not. We consider that accelerometers could estimate gait quality relating to gait independence more objectively and in greater detail than simple visual observation. Such additional information would be extremely beneficial
Bronwyn K. Clark, Nyssa T. Hadgraft, Takemi Sugiyama and Elisabeth A. Winkler
) was always measured via the activPAL. Two wear positions that researchers using accelerometers often employ to collect movement and posture data (thigh, wrist) were evaluated, with three beacon configurations (wall, desk or both). This enabled evaluation across a range of feasible options (single
Amber Watts, Mauricio Garnier-Villarreal and Paul Gardiner
( Rosenberger et al., 2013 ). Thigh or waist placement of postural monitors have higher rates of accuracy compared to wrist worn monitors ( Janssen & Cliff, 2015 ; Yang & Hsu, 2009 ). The activPAL ™ postural monitor, worn on the thigh, uses both postural angle and acceleration to measure sitting. It can
Declan Ryan, Jorgen Wullems, Georgina Stebbings, Christopher Morse, Claire Stewart and Gladys Onambele-Pearson
improve heath, 17 , 18 either directly or indirectly. With technological improvements, it is now possible to accurately quantify the physical behavior (PB) levels (SB and PA time). Thigh-mounted triaxial accelerometers are considered the gold standard for SB time quantification as posture can be
Sheri J. Hartman, Catherine R. Marinac, Lisa Cadmus-Bertram, Jacqueline Kerr, Loki Natarajan, Suneeta Godbole, Ruth E. Patterson, Brittany Morey and Dorothy D. Sears
standing position, it is difficult to derive thigh and body posture from a hip-worn accelerometer signal. 21 This measurement limitation is important because sedentary behavior dimensions such as sit-to-stand postural transitions and time spent standing may influence metabolic biomarkers and health
Berit Steenbock, Marvin N. Wright, Norman Wirsik and Mirko Brandes
provide energy expenditure (EE) prediction models from raw accelerometry data established against indirect calorimetry, (2) to compare two linear and two machine learning models, and (3) to compare accuracy of different accelerometers placed on the hips, thigh, and wrists. Methods Study Participants To
Alan K. Bourke, Espen A. F. Ihlen and Jorunn L. Helbostad
-third of the way down on the anterior aspect of the left thigh using a hydrogel patch (PALStickies ™ ). Activity classification, postural transfer detection, and steps detected by the activPAL3 were compared directly against video observations. Participants were recorded in two scenarios. The first was an
Scott E. Crouter, Paul R. Hibbing and Samuel R. LaMunion
/sec, the AG assumes the person is standing and inclination angle is ignored. In contrast, the AP is not as susceptible to confusing sitting and standing, because it is worn on the thigh, meaning the device will experience a change in incline of about 90 degrees between sitting and standing. However, the AP