Sixteen normal healthy adult males (age 26.8 ± 4.7 years) of height 1.76 ± 0.05 m and body mass 79.2 ± 9.4 kg with no history of orthopedic disease participated in this study. They voluntarily read and signed a written consent form before participating in the experiment that was approved by the University Institutional Review Board. A Biodex System 3 Pro isokinetic dynamometer (Biodex Corp., Shirley, NY, USA) was calibrated and assembled with the knee attachment according to the manufacturer’s specifications (Biodex, 1998). Biodex has been shown to be a reliable instrument for collecting data of human torque, joint position, and limb velocity (Brown et al., 1993; Drouin et al., 2004; Feiring et al., 1990; Gross et al., 1991; Ortqvist et al., 2007; Taylor et al., 1991). The dynamometer shaft was aligned with the assumed axis of rotation (lateral femoral condyle) of the dominant knee (right leg for all the subjects) with the subject in a seated position and the back reclined at approximately 110°. The left thigh was secured with straps as were the waist and thoracic torso (Weir et al., 1996). Arms were placed across the chest with hands grasping the straps (Stumbo et al., 2001). The lever arm pad was positioned to place the inferior aspect immediately superior to the medial malleolus. Subjects were passively moved to 0° of extension (full extension). After, the knee was flexed about 5° to 10° to a comfortable position set as the extension mechanical stop. Then, the flexion mechanical stop was defined so as to ensure a range of motion of 85 degrees. Gravity compensation analysis was performed by the computer system software provided with the Biodex System 3 Pro. The biomechanical signals were acquired trough the dynamometer DB-15 female interface (Biodex, 1998) which provides real time analog signals of torque, angular velocity, and angular position. An adaptor was built by the authors in order to get the signals from the DB-15 interface into three separate BNC connectors to a digitizer board (BNC-2120, National Instruments, TX, USA) which sampled the biomechanical signals at 2048 samples·s-1, and converted it to digital data via a 12 bit A/D. A software tool (Schwartz et al., 2008) was used to adjust the DB-15 voltage of the recorded signals to real units (N·m, degrees·s-1, and degrees), following the manufacturer’s specifications. This mechanism was used in order to get higher resolution for the digitized signals once the Biodex System 3 Pro only provides signals sampled at 100 samples·s-1. Although the rate of 100 samples·s-1 is sufficient for the isokinetic exercises analysis, a better resolution was chosen for a better precision of the biomechanical descriptors calculus. Following equipment setup, subjects were asked to perform 10 gradient sub-maximal reciprocal concentric extension (240°·s-1) and flexion (300°·s-1) repetitions for warm-up and familiarization with the equipment. For testing, subjects performed two sets of ten maximal concentric repetitions of dominant knee extension (at 60°·s-1 and 180°·s-1), on separate days and in a counterbalanced order. Consistent and standard, moderate (no yelling or screaming) verbal encouragement was given. No visual feedback of the biomechanical signals was provided to subjects during the test. In order to calculate the biomechanical descriptors on each separate IRP a computational algorithm (Figure 1) was developed by the authors in Matlab 6.5 (MathWorks, Natick, MA, USA). The algorithm divided the LR segment into two segments: VO and an isokinetic load range (ILR) segment. First, all the values less than the mean value of the extension angular velocity are set to zero and the original signal is shifted to the dashed-dot line trajectory of Figure 1a. Second, the first-difference technique (Smith, 1998) is applied to the shifted signal. This results in the circled-dots and the bold line shown in Figure 1b. Third, the absolute values of the bold line segment between the two circle-dots are determined and their mean value calculated. Figure 1c displays a zoomed image of this bold line segment and Figure 1d shows its absolute values with a straight line representing their mean value. Fourth, the algorithm investigates the first point greater than the mean value on the left and on the right side from the center of the segment, as illustrated by the asterisks in Figure 1d. These asterisks delineate the ILR segment. Finally, VO could be considered as the region between the first circled-dot and the first asterisk. However, its starting point is adjusted to the first point with at least 95 percent of the preset speed in order to meet the criterion for windowing (Wilk et al., 1992). The result is shown in the highlighted portion of Figure 1e. Four of the most common biomechanical descriptors were determined for each separated IRP: (1) the total work (TW) which is the total amount of work that is produced in a set (Brown, 2000; Remaud et al., 2007); (2) the peak torque to body weight (PTBW) which is the maximum torque produced in a set of repetitions, normalized to body weight (Brown, 2000); (3) the time interval (TI) in seconds of each phase of the movement; (4) the average length (AL) in degrees of each phase range. For all subjects, the four IRPs were identified in each repetition of each set of the knee extension movement at 60°·s-1 and 180°·s-1. The biomechanical descriptors were calculated from the total ROM and for each IRP. Then, the percent relation (PR) between the values of each IRP and the value of total ROM were established according to the following equation: Percent relation is a measure of how much each IRP contributes with the whole value of the descriptor inside a repetition. The same procedure was repeated for the windowing (Wilk et al., 1992) and data reduction techniques (Tis and Perrin, 1993) considering only the three major isokinetic phases, since these techniques do not manage the VO artifact. The behavior of isokinetic movement phases was focused on the PR ratio of each descriptor. Student’s t-test for dependent samples was applied to compare normally distributed data with a level of significance of 0.05 (two-tailed) and 95% of confidence interval. Wilcoxon Signed-Rank non-parametric test (De Sá, 2007) was applied to compare non-normal data. |