pixels containing bone from soft tissue analysis, and the large proportion of trunk pixels that contain bone, due to the arrangement of the spine and ribs, introduce appreciable error ( Roubenoff et al., 1993 ). The trunk region also contains internal organs, which exhibit the same attenuation ratio as
Grant M. Tinsley and Brett S. Nickerson
Peggy A. Houglum
When soft tissue is injured, it must follow a complex healing process. The sports medicine specialist delivering care to an injured athlete should have an appreciation and understanding of the phases and timing of the healing process so that appropriate, efficient, and effective rehabilitation program may be established. This paper presents an overview of the chemical and cellular activity involved in soft tissue healing, with emphasis on those aspects that can be affected by a rehabilitation program. Outside factors commonly used in sports injury care and how they may influence tissue healing are addressed. Guidelines are presented for establishing a sports rehabilitation program based on the physiological effects of the healing process. Various aspects of a rehabilitation program must be carefully coordinated with the timing of tissue healing and designed in a logical sequence to permit successful rehabilitation of the injured athlete in an optimal and efficient manner.
Matthew J. Hussey, Alex E. Boron-Magulick, Tamara C. Valovich McLeod and Cailee E. Welch Bacon
measures (eg, no intervention, static self-stretching measures, and TheraBand warm-up measures), study procedures, and ROM measurements (eg, internal rotation, horizontal adduction). 1 – 3 Current research identifies a few soft tissue therapy techniques for treating pain and increasing ROM including
Yanxin Zhang, David G. Lloyd, Amity C. Campbell and Jacqueline A. Alderson
The purpose of this study was to quantify the effect of soft tissue artifact during three-dimensional motion capture and assess the effectiveness of an optimization method to reduce this effect. Four subjects were captured performing upper-arm internal-external rotation with retro-reflective marker sets attached to their upper extremities. A mechanical arm, with the same marker set attached, replicated the tasks human subjects performed. Artificial sinusoidal noise was then added to the recorded mechanical arm data to simulate soft tissue artifact. All data were processed by an optimization model. The result from both human and mechanical arm kinematic data demonstrates that soft tissue artifact can be reduced by an optimization model, although this error cannot be successfully eliminated. The soft tissue artifact from human subjects and the simulated soft tissue artifact from artificial sinusoidal noise were demonstrated to be considerably different. It was therefore concluded that the kinematic noise caused by skin movement artifact during upper-arm internal-external rotation does not follow a sinusoidal pattern and cannot be effectively eliminated by an optimization model.
Aurel Coza, Benno M. Nigg and Ladina Fliri
Soft-tissue vibrations can be used to quantify selected properties of human tissue and their response to impact. Vibrations are typically quantified using high-speed motion capture or accelerometry. The aim of this study was to compare the amplitude and frequency of soft-tissue vibrations during running when quantified by highspeed motion capture and accelerometry simultaneously. This study showed: (a) The estimated measurement errors for amplitude and frequency were of the same order of magnitude for both techniques. (b) There were no significant differences in the mean peak frequencies and peak amplitudes measured by the two methods. (c) The video method showed an inability to capture high frequency information. This study has shown that a tradeoff has to be made between the accuracy in amplitude and frequency when these methods are employed to quantify soft tissue vibrations in running.
Matthew T.G. Pain and John H. Challis
The aims of this study were to quantify intrasegmental motion using an array of 28 surface-mounted markers to examine frequency and amplitude measurements of the intrasegmental motion to calculate forces and energy transfer; and to show that the underlying muscles are a major contributor to the skin marker motion. One participant performed 27 trials under three conditions in which his forearm was struck against a solid object fixed to a force plate while the locations of the markers were recorded at 240 Hz. For impacts with equal peak forces, the muscle tension significantly affected the amount of intrasegmental motion. Tensing the arm reduced the intrasegmental motion by 50%. The quadrilateral sectors defined by the markers changed in area by 11% with approximately equal motion in the vertical and horizontal direction. The maximum linear marker motion was 1.7 cm. The intrasegmental motion had distinct frequency components around 14 and 20 Hz. Soft tissue deformation could account for 70% of the energy lost from the forearm during these impacts. The study has demonstrated the important role that intrasegment soft tissue motion can have on the kinetics of an impact.
Patrick F. Curran, Russell D. Fiore and Joseph J. Crisco
Self-myofascial release (SMR) is a technique used to treat myofascial restrictions and restore soft-tissue extensibility.
To determine whether the pressure and contact area on the lateral thigh differ between a Multilevel rigid roller (MRR) and a Bio-Foam roller (BFR) for participants performing SMR.
Ten healthy young men and women.
Participants performed an SMR technique on the lateral thigh using both myofascial rollers. Thin-film pressure sensels recorded pressure and contact area during each SMR trial.
Mean sensel pressure exerted on the soft tissue of the lateral thigh by the MRR (51.8 ± 10.7 kPa) was significantly (P < .001) greater than that of the conventional BFR (33.4 ± 6.4 kPa). Mean contact area of the MRR (47.0 ± 16.1 cm2) was significantly (P < .005) less than that of the BFR (68.4 ± 25.3 cm2).
The significantly higher pressure and isolated contact area with the MRR suggest a potential benefit in SMR.
Jeffrey D. Holmes, David M. Andrews, Jennifer L. Durkin and James J. Dowling
The purpose of this study was to derive and validate regression equations for the prediction of fat mass (FM), lean mass (LM), wobbling mass (WM), and bone mineral content (BMC) of the thigh, leg, and leg + foot segments of living people from easily measured segmental anthropometric measures. The segment masses of 68 university-age participants (26 M, 42 F) were obtained from full-body dual photon x-ray absorptiometry (DXA) scans, and were used as the criterion values against which predicted masses were compared. Comprehensive anthropometric measures (6 lengths, 6 circumferences, 8 breadths, 4 skinfolds) were taken bilaterally for the thigh and leg for each person. Stepwise multiple linear regression was used to derive a prediction equation for each mass type and segment. Prediction equations exhibited high adjusted R 2 values in general (0.673 to 0.925), with higher correlations evident for the LM and WM equations than for FM and BMC. Predicted (equations) and measured (DXA) segment LM and WM were also found to be highly correlated (R 2 = 0.85 to 0.96), and FM and BMC to a lesser extent (R 2 = 0.49 to 0.78). Relative errors between predicted and measured masses ranged between 0.7% and –11.3% for all those in the validation sample (n = 16). These results on university-age men and women are encouraging and suggest that in vivo estimates of the soft tissue masses of the lower extremity can be made fairly accurately from simple segmental anthropometric measures.
Matthew T.G. Pain and John H. Challis
This study had two purposes: to evaluate a new method for measuring segmental dimensions for determining body segment inertial parameters (BSIP), and to evaluate the changes in mass distribution within a limb as a consequence of muscular contraction. BSIP were calculated by obtaining surface data points of the body under investigation using a sonic digitizer, interpolating them into a regular grid, and then using Green’s theorem which relates surface to volume integrals. Four skilled operators measured a test object; the error was approximately 2.5% and repeatability was 1.4% (coefficient of variation) in the determination of BSIP. Six operators took repeat measures on human lower legs; coefficients of variation were typically around 5%, and 3% for the more skilled operators. Location of the center of mass of the lower leg was found to move up 1.7 cm proximally when the triceps surae muscles went from a relaxed state to causing plantar flexion. The force during an impact associated with such motion of the soft tissue of the lower leg was estimated to be up to 300 N. In summary, a new repeatable and accurate method for determining BSIP has been developed, and has been used to evaluate body segment mass redistribution due to muscular contraction.