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John M. Schuna Jr., Tiago V. Barreira, Daniel S. Hsia, William D. Johnson and Catrine Tudor-Locke

Background:

Energy expenditure (EE) estimates for a broad age range of youth performing a variety of activities are needed.

Methods:

106 participants (6–18 years) completed 6 free-living activities (seated rest, movie watching, coloring, stair climbing, basketball dribbling, jumping jacks) and up to 9 treadmill walking bouts (13.4 to 120.7 m/min; 13.4 m/min increments). Breath-by-breath oxygen uptake (VO2) was measured using the COSMED K4b2 and EE was quantified as youth metabolic equivalents (METy1:VO2/measured resting VO2, METy2:VO2/estimated resting VO2). Age trends were evaluated with ANOVA.

Results:

Seated movie watching produced the lowest mean METy1 (6- to 9-year-olds: 0.94 ± 0.13) and METy2 values (13- to 15-year-olds: 1.10 ± 0.19), and jumping jacks produced the highest mean METy1 (13- to 15-year-olds: 6.89 ± 1.47) and METy2 values (16- to 18-year-olds: 8.61 ± 2.03). Significant age-related variability in METy1 and METy2 were noted for 8 and 2 of the 15 evaluated activities, respectively.

Conclusions:

Descriptive EE data presented herein will augment the Youth Compendium of Physical Activities.

Open access

Mhairi K. MacLean and Daniel P. Ferris

between human and machine included a waist belt, hard thigh and shin cuffs with soft straps, and a soft material loop around the shoe. Next, we tuned the controller parameters using the participant’s feedback while they performed different ambulatory tasks. The tasks included walking on a treadmill

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Greg Petrucci Jr., Patty Freedson, Brittany Masteller, Melanna Cox, John Staudenmayer and John Sirard

. Another Misfit model has shown reliability in estimating steps during repeated treadmill walking bouts at 3.2 km·h −1 , 4.82 km·h −1 , and 6.42 km·h −1 ( Fokkema, Kooiman, Krijnen, Van Der Schans, & Groot, 2017 ). However, before widespread adoption of the MS in research, as an intervention tool or as a

Open access

Keishi Soga, Keita Kamijo and Hiroaki Masaki

coupled to gait cycle phase during treadmill walking . Neuroimage, 54 ( 2 ), 1289 – 1296 . PubMed doi:10.1016/j.neuroimage.2010.08.066 10.1016/j.neuroimage.2010.08.066 Herzmann , G. , Jin , M. , Cordes , D. , & Curran , T. ( 2012 ). A within-subject ERP and fMRI investigation of orientation