Repeat measurements were made by 2 operators on a group of 50 physically active subjects (age, 20.7 years ± 1.8; males: height 1.780 m ± 0.043. mass, 78.09 kg ± 9.30; females: height. 1.680 m ± 0.064. mass. 66.67 kg ± 6.67) to determine the precision with which the subjects' limb segment inertial parameters could be estimated. Segmental inertial parameters were determined using 3 techniques. 2 of which involved modeling segments as geometric solids, and a 3rd which used the equations of Zatsiorsky et al. (1990). Precisions were high for all 3 techniques, with little difference between inter- and intra-operator precisions. The lowest precisions were obtained for the hands and feet. For these segments the use of repeat measures to improve precision is recommended. These results imply that with similarly trained measurers, comparison of inertial parameters determined using the same protocol but obtained by different operators is appropriate, and that it is viable to have 2 measurers taking measurements on the same subject to accelerate data collection.
John H. Challis
John J. Jeka, Pedro Ribeiro, Kelvin Oie and James R. Lackner
The goal of the present study was to determine the properties of the somatosensory stimulus that alter its temporal coupling to body sway. Six standing subjects were tested while touching a metal plate positioned either directly in front of or lateral to the subject. In each condition, the plate moved 4 mm at 0.2 Hz in either the medial-lateral (ML) or anterior-posterior direction (AP). The results showed that coupling between body sway and touch plate movement was strongest when the touch plate moved in a direction along the longitudinal axis of the arm. Coupling strength was weaker when the touch plate moved perpendicular to the longitudinal axis of the arm. The results consistently show that a radial expansion stimulus was more effective than a lamellar-type stimulus at the fingertip. Moreover, somatosensory information from a surface is interpreted in terms of the orientation of the contact limb and the potential degrees of freedom available through its movement.
Jae Kun Shim, Jeffrey Hsu, Sohit Karol and Ben F. Hurley
The purpose of the current study was to investigate the effects of finger strength training (ST) on finger strength, independence, force control, and adaptations in multifinger coordination. Thirty-three healthy, young (23.0 ± 2.9 years) subjects were randomly assigned into 4 groups. Group 1 (G1) trained all fingers together, Group 2 (G2) trained individual fingers without restricting movements of the non-training fingers, and Group 3 (G3) trained individual fingers while restricting the movement of the nontraining fingers. The control group (G0) did not undergo any training. A vertically hanging load was attached to a spring that passed through a pulley. The other end of the string extended to the horizontal plane and had thimbles attached to it. Subjects were asked to rest their forearm on the table and lift the load by inserting their fingers into the thimbles. The training protocol lasted 6 weeks. Identical experimental tests were conducted 4 times, biweekly, across the 6-week training. Force coordination and moment coordination, defined as synergies stabilizing the resultant force and the resultant moment of all finger forces, in a multifinger pressing task were quantified using the Uncontrolled Manifold (UCM) analysis. The UCM analysis allocates motor variability into two components, one in the null space of a motor task and the other perpendicular to the null space. During multifinger pressing tasks, multifinger coordination exists when the variability in the null space is greater than the variability in the subspace perpendicular to the null space. The multifinger coordination was quantified as the difference between the variance within the null space and that perpendicular to the null space, normalized by the total variance. Thus, the coordination measure in our analysis is a unitless variable. A greater coordination measure indicates better multifinger coordination. Moment-stabilizing multifinger coordination increased only in G1 (from 1.197 ± 0.004 to 1.323 ± 0.002, p < .01), and force-stabilizing coordination increased only in G3 (from 0.207 ± 0.106 to 0.727 ± 0.071, p < .01). Finger strength, measured by the maximal voluntary finger force of pressing 4 fingers, increased significantly in all training groups (from 103.7 ± 3.1 N to 144.0 ± 3.6 N for training groups, all p < .001). Finger-force errors, quantified by the deviations between the required force profiles (20% maximal voluntary force) presented to the subjects and the actual force produced, decreased significantly with ST for all the training groups (all p < .05). Finger independence also decreased significantly for all the training groups (p < .05). We conclude that the neuromuscular system adaptations to multifinger ST are specific to the training protocol being employed, yielding improvements in different types of multifinger coordination (i.e., coordination-specific ST), finger-force control, and finger strength and a decrease in finger independence. Finger independence, depending on the nature of the task, might or might not be favorable to certain task performances. We suggest that ST protocol should be carefully designed for the improvement of specific coordination of multieffector motor systems.
John L. Woodard and Annalise A.M. Rahman
Recent progress in technology has allowed for the development and validation of computer-based adaptations of existing pencil-and-paper neuropsychological measures and comprehensive cognitive test batteries. These computer-based assessments are frequently implemented in the field of clinical sports psychology to evaluate athletes’ functioning postconcussion. These tests provide practical and psychometric advantages over their pencil-and-paper counterparts in this setting; however, these tests also provide clinicians with unique challenges absent in paper-and-pencil testing. The purpose of this article is to present advantages and disadvantages of computer-based testing, generally, as well as considerations for the use of computer-based assessments for the evaluation of concussion among athletes. Furthermore, the paper provides suggestions for further development of computerized assessment of sports concussion given the limitations of the current technology.
Jeanick Brisswalter and Christophe Hausswirth
Benjamin W. Infantolino and John H. Challis
The pennated arrangement of muscle fibers has important implications for muscle function in vivo, but complex arrangement of muscle fascicles in whole muscle raises the question whether the arrangement of fascicles produce variations in pennation angle throughout muscle. The purpose of this study was to describe the variability in pennation angle observed throughout the first dorsal interosseous (FDI) muscle using magnetic resonance imaging (MRI). Two cadaveric muscles were scanned in a 14.1 tesla MRI unit. Muscles were divided into slices and pennation angle was measured in the same representative location throughout the muscle in each slice for the medial-lateral and anterior posterior-image planes. Data showed large nonuniform variation in pennation angles throughout the muscles. For example, for cadaver 2, pennation angle in 287 planes along the medial-lateral axis ranged from 3.2° to 22.6°, while for the anterior-posterior axis, in 237 planes it ranged from 3.1° to 24.5°. The nonnormal distribution of pennation angles along each axis suggests a more complex distribution of fascicles than is assumed when a single pennation angle is used to represent an entire muscle. This distribution indicates that a single pennation angle may not accurately describe the arrangement of muscle fascicles in whole muscle.
Lindsay A. Ellis, Brandon A. Yates, Amy L. McKenzie, Colleen X. Muñoz, Douglas J. Casa and Lawrence E. Armstrong
Urine color (Ucol) as a hydration assessment tool provides practicality, ease of use, and correlates moderately to strongly with urine specific gravity (Usg) and urine osmolality (Uosm). Indicative of daily fluid turnover, along with solute and urochrome excretion in 24-hr samples, Ucol may also reflect dietary composition. Thus, the purpose of this investigation was to determine the efficacy of Ucol as a hydration status biomarker after nutritional supplementation with beetroot (880 mg), vitamin C (1000 mg), and riboflavin (200 mg). Twenty males (Mean ± SD; age, 21 ± 2 y; body mass, 82.12 ± 15.58 kg; height, 1.77 ± 0.06 m) consumed a standardized breakfast and collected all urine voids on one control day (CON) and 1 day after consuming a standardized breakfast and a randomized and double-blinded supplement (SUP) over 3 weeks. Participants replicated exercise and diet for one day before CON, and throughout CON and SUP. Ucol, Usg, Uosm, and urine volume were measured in all 24-hr samples, and Ucol and Usg were measured in all single samples. Ucol was a significant predictor of single sample Usg after all supplements (p < .05). Interestingly, 24-hr Ucol was not a significant predictor of 24-h Usg and Uosm after riboflavin supplementation (p = .20, p = .21). Further, there was a significant difference between CON and SUP 24-h Ucol only after riboflavin supplementation (p < .05). In conclusion, this investigation suggests that users of the UCC (urine color chart) should consider riboflavin supplementation when classifying hydration status and use a combination of urinary biomarkers (e.g., Usg and Ucol), both acutely and over 24 hr.