High-frequency vibrations e.g., induced by legs impacting with the ground during terrestrial locomotion can provoke damage within tendons even leading to ruptures. So far, macroscopic Hill-type muscle models do not account for the observed high-frequency damping at low-amplitudes. Therefore, former studies proposed that protective damping might be explained by modelling the contractile machinery of the muscles in more detail, i.e., taking the microscopic processes of the actin-myosin coupling into account. In contrast, this study formulates an alternative hypothesis: low but significant damping of the passive material in series to the contractile machinery--e.g., tendons, aponeuroses, titin--may well suffice to damp these hazardous vibrations. Thereto, we measured the contraction dynamics of a piglet muscle-tendon complex (MTC) in three contraction modes at varying loads and muscle-tendon lengths. We simulated all three respective load situations on a computer: a Hill-type muscle model including a contractile element (CE) and each an elastic element in parallel (PEE) and in series (SEE) to the CE pulled on a loading mass. By comparing the model to the measured output of the MTC, we extracted a consistent set of muscle parameters. We varied the model by introducing either linear damping in parallel or in series to the CE leading to accordant re-formulations of the contraction dynamics of the CE. The comparison of the three cases (no additional damping, parallel damping, serial damping) revealed that serial damping at a physiological magnitude suffices to explain damping of high-frequency vibrations of low amplitudes. The simulation demonstrates that any undamped serial structure within the MTC enforces SEE-load eigenoscillations. Consequently, damping must be spread all over the MTC, i.e., rather has to be de-localised than localised within just the active muscle material. Additionally, due to suppressed eigenoscillations Hill-type muscle models taking into account serial damping are numerically more efficient when used in macroscopic biomechanical neuro-musculo-skeletal models.

Treadmills are often used in research to analyse kinematic and physiological variables. The success of transfering the results to overground running depends on the comparability of the values between the two situations. The aim of the present study was to compare the kinematics and muscle activities in overground and treadmill running. Ten male physical education students with experience in treadmill running were asked to run with a speed of 4.0 and 6.0 m/s both overground and on a Woodway treadmill. The 3D-kinematics of the limbs were studied using a two camera video tracking system. Additionally the surface EMG of six lower limb muscles and the pattern of ground contact of the right foot was registered. Both the activities of the leg muscles and several kinematic variables showed systematic changes from overground to treadmill running. On the treadmill the subjects favoured a type of running that provided them with a higher level of security. The swing amplitude of the leg, the vertical displacement and the variance in vertical and horizontal velocity were lower in treadmill running. The angle between shoe sole and ground at foot impact was also lower and the forward lean of the upper body was higher in running on the treadmill compared with the overground mode. Most of the subjects reduced their step length and increased stride frequency in treadmill running. Furthermore, the contact time in treadmill running was shorter than for overground running. The above mentioned kinematic variables were significantly different (p < 0.05). The EMG patterns of the leg muscles were generally similar between overground and treadmill modes, but some minor differences could consistently be identified.

No abstract

Inverse dynamics is a standard analysis in biomechanics to reconstruct time histories of internal driving forces and torques from measured external forces and segmental kinematics. The main sources of inconsistency leading to analytical artefacts in this process are skin marker and soft tissue motion. These potentially artificial high frequency fluctuations in the joint torques may serve as an erroneous basis of (misleading) assumptions with respect to muscular activity. Here we suggest techniques to reduce these errors. In both parts of this study, high-speed video and force platform data were acquired. In one part, 69 sequences of human barefoot running were sampled followed by an inverse dynamic analysis of the stance leg. The time history of the hip joint torque in the sagittal plane served as a sensitive "detector" of dynamic analysis artefacts. We show that the most important error — the relative skin to bone motion especially of the knee marker — can be reduced significantly by processing kinematic data using bone rigidity (constant segment lengths) and bony contour (frontal knee edge) information. Further on, neglecting significantly initiated soft tissue dynamics in the inverse dynamic model introduces another inconsistency in the analytical process. Therefore, in a second part of this study, soft tissue kinematics from 14 jumping sequences were identified. These data provided a set of coupling parameters of wobbling masses to the bone that were ready to be implemented in the inverse dynamic model. Using realistic bone kinematics mainly avoids phase shifts in the acceleration scenario within the leg, and thus artifical hip torque fluctuations within the whole contact period. In human running, accounting for soft tissue dynamics mainly affects the calculated timing of the hip joint torque during the impact phase.