between mean error of the devices and BMI, percent fat, SSRP, and WC. Finally, stepwise linear regressions were performed to determine whether BMI, SSRP, or WC contributed to NL-2000, SW-200, or HJ-303 error. All statistical analyses were carried out using the Statistical Package for the Social Sciences
Brian Tyo, Rebecca Spataro-Kearns and David R. Bassett Jr.
Nathan F. Meier, Yang Bai, Chong Wang and Duck-chul Lee
plots on the right side display the elimination of random mean error, reduced range of individual error, and inverse systematic bias of a similar magnitude. The sample mean accuracy changed from −2.2 kg of ALM, −5.6 kg of FFM, and +6.1%BF to 0.0 for ALM, FFM, and %BF using the prediction equations. In
Kristie-Lee Taylor, Will G. Hopkins, Dale W. Chapman and John B. Cronin
The purpose of this study was to calculate the coefficients of variation in jump performance for individual participants in multiple trials over time to determine the extent to which there are real differences in the error of measurement between participants. The effect of training phase on measurement error was also investigated. Six subjects participated in a resistance-training intervention for 12 wk with mean power from a countermovement jump measured 6 d/wk. Using a mixed-model meta-analysis, differences between subjects, within-subject changes between training phases, and the mean error values during different phases of training were examined. Small, substantial factor differences of 1.11 were observed between subjects; however, the finding was unclear based on the width of the confidence limits. The mean error was clearly higher during overload training than baseline training, by a factor of ×/÷ 1.3 (confidence limits 1.0–1.6). The random factor representing the interaction between subjects and training phases revealed further substantial differences of ×/÷ 1.2 (1.1–1.3), indicating that on average, the error of measurement in some subjects changes more than in others when overload training is introduced. The results from this study provide the first indication that within-subject variability in performance is substantially different between training phases and, possibly, different between individuals. The implications of these findings for monitoring individuals and estimating sample size are discussed.
Hidetomo Suzuki, Kathleen A. Swanik, Kellie C. Huxel, John D. Kelly IV and C. Buz Swanik
To determine the effect of scapular fatigue on shoulder and elbow kinematics and accuracy.
30 healthy men.
Subjects performed seated overhead throws into a target before and after a standardized scapular-muscle-fatigue protocol.
Main Outcome Measurements:
Shoulder and elbow kinematic data were analyzed during throwing. Scapular upward rotation was measured (0°, 45°, and 90° humeral elevation in scaption) with an inclinometer. Throwing accuracy was measured as mean error distance from the target (cm).
After fatigue, there was a significant increase in total elbow motion (12 % more in cocking phase, P < .05) and elbow velocity in the follow-through phase (average and maximum into flexion, P < .05). Throwing accuracy decreased 26% after fatigue (P < .05).
Scapular-muscle fatigue results in compensatory motions at the elbow that might affect performance and contribute to elbow pathologies.
Barry R. Greene, Timothy G. Foran, Denise McGrath, Emer P. Doheny, Adrian Burns and Brian Caulfield
This study compares the performance of algorithms for body-worn sensors used with a spatiotemporal gait analysis platform to the GAITRite electronic walkway. The mean error in detection time (true error) for heel strike and toe-off was 33.9 ± 10.4 ms and 3.8 ± 28.7 ms, respectively. The ICC for temporal parameters step, stride, swing and stance time was found to be greater than 0.84, indicating good agreement. Similarly, for spatial gait parameters—stride length and velocity—the ICC was found to be greater than 0.88. Results show good to excellent concurrent validity in spatiotemporal gait parameters, at three different walking speeds (best agreement observed at normal walking speed). The reported algorithms for body-worn sensors are comparable to the GAITRite electronic walkway for measurement of spatiotemporal gait parameters in healthy subjects.
L. R. Brawley, R. C. Powers and K. A. Phillips
This experiment examined if a general expectancy for male superiority biased subjective evaluation of motor performance. Alternatively, sex bias could be specific to tasks involving muscular work. If the former, rather than the latter explanation is viable, a bias favoring males would be generalized to a task not obviously sex typed: motor accuracy. Observers, 22 of each sex, watched the softball pitching accuracy of performers of both sexes. Performer accuracy was trained and tested to ensure equality. Observers estimated preperformance accuracy, then observed three throws, estimating postperformance after each. Unlike the muscular endurance experiments, neither preperformance nor postperformance analysis revealed a sex bias. Thus a task-specific expectancy rather than general expectancy for male superiority was suggested to explain evaluation sex bias of previous muscular endurance experiments. Surprisingly, mean error magnitude of postperformance estimates was significantly greater for performers observed second than those viewed first, although actual performer accuracy was not different. This finding appears analogous to psychophysical judgment results in which successive stimulus judgments were conditions sufficient to cause estimation error. Suggestions are made for future research.
Patrick W. Kennedy Jr., David L. Wright and Gerald A. Smith
The precision of the kinematic values depends upon the methods of recording a subject’s motion. With the introduction of video recording techniques, questions have arisen concerning the accuracy of video compared with that of 16-mm film. Accordingly, the purpose of this study was to compare the accuracy of the two techniques for point reprediction using the Direct Linear Transformation method. Range poles, serving as boundaries of a cube with 20 known spatial coordinates, were filmed and videotaped. The 20 control points on the film and video recordings were digitized by three individuals. Nine sets of digitized points (three digitizers × three trials) for both film and video were compared with the actual three-dimensional coordinate values. Resultant mean errors were statistically significantly different (p<.05), 4.8 mm and 5.8 mm for film and video, respectively. However, from a practical standpoint the video error was only .29% of the calibrated field compared to .24% for film. Thus it is concluded that video techniques are comparable in accuracy to 16-mm filming methods.
James C. Martin, Steven J. Elmer, Robert D. Horscroft, Nicholas A.T. Brown and Barry B. Shultz
The purpose of this study was to develop and evaluate an alternative method for determining the position of the anterior superior iliac spine (ASIS) during cycling. The approach used in this study employed an instrumented spatial linkage (ISL) system to determine the position of the ASIS in the parasagittal plane. A two-segment ISL constructed using aluminum segments, bearings, and digital encoders was tested statically against a calibration plate and dynamically against a video-based motion capture system. Four well-trained cyclists provided data at three pedaling rates. Statically, the ISL had a mean horizontal error of 0.03 ± 0.21 mm and a mean vertical error of −0.13 ± 0.59 mm. Compared with the video-based motion capture system, the agreement of the location of the ASIS had a mean error of 0.30 ± 0.55 mm for the horizontal dimension and −0.27 ± 0.60 mm for the vertical dimension. The ISL system is a cost-effective, accurate, and valid measure for two-dimensional kinematic data within a range of motion typical for cycling.
Karsten Koehler, Thomas Abel, Birgit Wallmann-Sperlich, Annika Dreuscher and Volker Anneken
Inactivity and overweight are major health concerns in children and adolescents with disabilities. Methods for the assessment of activity and energy expenditure may be affected negatively by the underlying disability, especially when motor function is impaired. The purpose of this study was to assess the validity of the SenseWear Armband in adolescents with cerebral palsy and hemiparesis.
Ten volunteers (age: 13.4 ± 1.6 years) were equipped with SenseWear Armbands on the hemiparetic and nonhemiparetic side of the body. Energy expenditure was measured at rest and during treadmill exercise (speed range: 0.85 to 2.35 m/s). Indirect calorimetry served as independent reference method.
The mean error was between −0.6 and 0.8 kcal/min and there were no significant differences between SenseWear and indirect calorimetry at any speed. Differences between body sides in expenditure (mean: −0.2 to 0.0 kcal/min) and step count (mean: −3.4 to 9.7 steps/min) were not significant.
The validity of the SenseWear Armband does not appear to be negatively affected by cerebral palsy during laboratory treadmill exercise. Future field studies are necessary to assess the validity and practicability of energy expenditure and physical activity assessment in children and adolescents with physical disabilities.
Scott E. Crouter, Diane M. DellaValle, Jere D. Haas, Edward A. Frongillo and David R. Bassett
The purpose of this study was to compare the 2006 and 2010 Crouter algorithms for the ActiGraph accelerometer and the NHANES and Matthews cut-points, to indirect calorimetry during a 6-hr free-living measurement period.
Twenty-nine participants (mean ± SD; age, 38 ± 11.7 yrs; BMI, 25.0 ± 4.6 kg·m-2) were monitored for 6 hours while at work or during their leisure time. Physical activity (PA) data were collected using an ActiGraph GT1M and energy expenditure (METs) was measured using a Cosmed K4b2. ActiGraph prediction equations were compared with the Cosmed for METs and time spent in sedentary behaviors, light PA (LPA), moderate PA (MPA), and vigorous PA (VPA).
The 2010 Crouter algorithm overestimated time spent in LPA, MPA, and VPA by 9.0%−44.5% and underestimated sedentary time by 20.8%. The NHANES cut-points overestimated sedentary time and LPA by 8.3%−9.9% and underestimated MPA and VPA by 50.4%−56.7%. The Matthews cut-points overestimated sedentary time (9.9%) and MPA (33.4%) and underestimated LPA (25.7%) and VPA (50.1%). The 2006 Crouter algorithm was within 1.8% of measured sedentary time; however, mean errors ranged from 34.4%−163.1% for LPA, MPA, and VPA.
Of the ActiGraph prediction methods examined, none of them was clearly superior for estimating free-living PA compared with indirect calorimetry.