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Alison R. Oates, Aaron Awdhan, Catherine Arnold, Joyce Fung and Joel L. Lanovaz

motion capture system (Vicon Motion Systems, Denver, CO). Kinematic data were sampled at 100 Hz and low-pass filtered at 8 Hz. Virtual markers delineating the edges of the feet were used to calculate the ML base of support boundary during stance phase. A 12-segment whole-body model was created with the

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Jeff E. Goodwin

haptic feedback in learning a complex rowing-type task . Journal of Motor Behavior, 45 , 455 – 472 . doi:10.1080/00222895.2013.826169 10.1080/00222895.2013.826169 Todorov , E. , Shadmehr , R. , & Bizzi , E. ( 1997 ). Augmented feedback presented in a virtual environment accelerates learning of

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Pål Haugnes, Per-Øyvind Torvik, Gertjan Ettema, Jan Kocbach and Øyvind Sandbakk

6), according to terrain topography (Figure  1 ). The maximal difference in elevation was 24 m with a total climb of 38 m for the entire course. The time each skier spent in a section was calculated based on virtual split times. Speed for each section was calculated by dividing the length of a

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Cornelia Frank, Gian-Luca Linstromberg, Linda Hennig, Thomas Heinen and Thomas Schack

coordinated actions (e.g.,  Memmert, Lemmink, & Sampaio, 2017 ), both in real world as well as in virtual reality scenarios ( Hülsmann, Frank, Schack, Kopp, & Botsch, 2016 ). Using artificial neural network approaches to analyze position data over time in order to learn about coordinated team action in

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Shijun Zhu, Eun-Shim Nahm, Barbara Resnick, Erika Friedmann, Clayton Brown, Jumin Park, Jooyoung Cheon and DoHwan Park

ongoing motivational intervention geared toward increasing adherence to bone health behaviors, including exercise, among older adults. The Bone Power program consisted of 11 learning modules, eight moderated discussion boards, and additional resources such as virtual and video lecture libraries, an Ask

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Theresa C. Hauge, Garrett E. Katz, Gregory P. Davis, Kyle J. Jaquess, Matthew J. Reinhard, Michelle E. Costanzo, James A. Reggia and Rodolphe J. Gentili

– 51 . PubMed ID: 29378284 doi:10.1016/j.biopsycho.2018.01.009 10.1016/j.biopsycho.2018.01.009 Shewokis , P.A. , Ayaz , H. , Panait , L. , Liu , Y. , Syed , M. , Greenawald , L. , & Castellanos , A. ( 2015 ). Brain-in-the-loop learning using fNIR and simulated virtual reality surgical

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Lauren McMichan, Ann-Marie Gibson and David A. Rowe

. Teach Teach Educ . 2015 ; 52 : 113 – 127 . doi:10.1016/j.tate.2015.09.007 10.1016/j.tate.2015.09.007 45. Norris E , Shelton N , Dunsmuir S , Duke-Williams O , Stamatakis E . Virtual field trips as physically active lessons for children: a pilot study . BMC Public Health . 2015 ; 15

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Harsh H. Buddhadev and Philip E. Martin

digitally filtered at 4 Hz and used to compute coordinates of a virtual marker representing the pedal axle. A crank cycle was defined as the period between sequential top dead center positions of the left crank arm (i.e., peak vertical position of the pedal axle). Data for 15 crank cycles collected during

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David A. Ferrer and Rebecca Ellis

/posttest design Women with young children (mean age = 34.3 ± 2.9) App was used for 28 d with cumulative goal = 280,000 steps. Active Australia Survey Attrition rate = 14% Theoretical framework: TPB Teams of 4–8 friends measured daily step counts. Could send teammates virtual gifts for encouragement. Strategies

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Grace C. Bellinger, Kristen A. Pickett and Andrea H. Mason

size and distance . Experimental Brain Research, 117 ( 3 ), 457 – 464 . PubMed ID: 9438714 doi:10.1007/s002210050241 10.1007/s002210050241 Mason , A.H. ( 2007 ). An experimental study on the role of graphical information about hand movement when interacting with objects in virtual reality