metrics. To ameliorate this, researchers have proposed methods to incorporate cocontraction into optimization; 2 common approaches are constraining predicted muscle excitations to match magnitudes of normalized surface electromyography (EMG) signals within a tolerance 8 or constraining optimization to
Daniel C. McFarland, Alexander G. Brynildsen and Katherine R. Saul
Jupil Ko, Erik Wikstrom, Yumeng Li, Michelle Weber and Cathleen N. Brown
indicator box to increase their reach distance during the YBT, the trial was eliminated and repeated. 5 , 11 Figure 2 —The foot placement on the Star Excursion Balance Test (left) and Y-Balance Test (right). Data Reduction and Analysis Reach distances were normalized to leg length ([reach distance
Jillian J. Haszard, Kim Meredith-Jones, Victoria Farmer, Sheila Williams, Barbara Galland and Rachael Taylor
component unbroken). This means that there will be variation in day length and component variables must be normalized to sum to 24 hours. As part of this process, non-wear time is generally removed from the day before normalization ( Carson, Tremblay, & Chastin, 2017 ; Chastin et al., 2015 ; Dumuid
Bryan L. Riemann and George J. Davies
normalization methods, 3 and underlying projection mechanics. 1 Although the test is believed to reflect test limb strength, 1 there have been no assessments determining whether test performance is directly associated with UE strength. Isokinetics is the gold standard for assessing muscular strength in
Damien Moore, Tania Pizzari, Jodie McClelland and Adam I. Semciw
actions) were performed for data normalization ( Supplementary Table S1 [available online]). Statistical Analysis The R statistical software package (version 3.4.1; https://cran.r-project.org/ ) was used for analysis. The EMG data processing has been described in detail previously. 6 Muscle activity
Melissa Lau, Li Wang, Sari Acra and Maciej S. Buchowski
Standardized measures of energy expenditure (EE) for sedentary activities in youth are needed. The goal was to determine EE of common contemporary and computer-related sedentary activities in youth.
We measured EE for sedentary tasks in 10- to 17-year-old youths (n = 24) during ~24 hours in a whole-room indirect calorimeter. Directly monitored tasks were performed for ~10-min. EE was calculated from oxygen consumed and carbon dioxide produced, converted to metabolic equivalents (MET) by normalization to an individual’s measured resting EE, and compared with the Compendium of Energy Expenditures for Youth.
Compared with the youth compendium, measured METs were lower for internet surfing (1.3), computer keyboard typing (1.3), and sorting beads/crafts (1.5) (all P < .002), and similar for handwriting (1.4), playing cards (1.6), video-gaming (1.6), and telephoning (1.5).
Current youth compendium MET estimates should be used with caution when predicting EE of common contemporary and computer-related sedentary activities in youth.
Sarah A. Roelker, Elena J. Caruthers, Rachel K. Hall, Nicholas C. Pelz, Ajit M.W. Chaudhari and Robert A. Siston
long head of the biceps femoris, gluteus maximus, gluteus medius, medial gastrocnemius, rectus femoris, soleus, tibialis anterior, and vastus lateralis. The EMG was high-pass filtered at 10 Hz, rectified, and root mean square (RMS) smoothed, with a 20 millisecond window. The EMG was normalized to the
Samantha L. Winter, Sarah M. Forrest, Joanne Wallace and John H. Challis
assessed using an Anderson Darling test of normality. All variables were normally distributed. The segment mass data for each method was normalized by dividing by the DXA-derived whole-body mass. Percentage root mean square errors (RMSE) are reported for the normalized estimates from each model compared
Jonathan M. Williams, Michael Gara and Carol Clark
used to denote start and landing positions. Hop distances were normalized to 50% the individual’s height (forward hopping) and 33% the individual’s height (medial and lateral hopping). The hop was deemed successful if the participant landed with their foot touching the floor marker and balance
with comparable normalized strength, years of movement, or sporting-skill training. As such, undoubtedly well-intended research on female athletes, through lack of control or description of modifiable factors such as strength, skill, and training age, has mostly perpetuated conclusions that overly