Biomedical subjects

K G Gerritsen

Publications and source records attributed to K G Gerritsen.

8 recordsLinked to original sources

PubMed2000

A sensitivity analysis of the calculation of mechanical output through inverse dynamics: a computer simulation study.

The purpose of this study was to systematically determine the effect of experimental errors on the work output calculated using two different methods of inverse dynamics during vertical jumping: (a) the conventional (rotational) method and (b) the translational method. A two-dimensional musculoskeletal model was used to generate precisely known kinematics. Next, the location of each joint center (JC) and the location of each segment's center of mass (CM) were manipulated by +/-10% of segment length to simulate errors in the location of joint centers (delta JC) and errors in the location of segment's center of mass (delta CM), respectively. Work output was subsequently calculated by applying the two methods of inverse dynamics to the manipulated kinematic data. The results showed that the translational method of inverse dynamics was less sensitive (up to 13% error in total work output) to delta JC and delta CM than the rotational method (up to 28% error in total work output). The rotational method of inverse dynamics was particularly sensitive to simulated errors in JC.

Biomechanical Phenomena↗

PubMed1998

Human muscle modelling from a user's perspective.

Methods for developing mathematical models representing entire human muscles are briefly reviewed, with special emphasis on aspects of modelling velocity dependence using cross-bridge dynamics, and isometric force-length properties from myofilament lengths and muscle architecture. For each of these components, mechanistic (using basic contraction mechanisms) and phenomenological ("black-box") models are available. Experiments on constant-velocity lengthening at different velocities were simulated using (a) a cross-bridge based model and (b) a Hill-based model. The Hill model was superior in its ability to predict muscle forces under different conditions with the same model parameters. Regarding force-length properties, myofilament overlap and muscle architecture did not correctly predict maximal isometric joint moments over the entire functional range of motion. The width of the force-length relationship of all contractile elements in a lower extremity model may be optimized to fit measured isometric moment-angle relationships. The resulting increase in width suggests that for some short-fibered muscles with complex architecture, the "effective" muscle fibre length is increased because muscle fibres may be partly connected in series as well as in parallel. It is concluded that a hybrid phenomenological/mechanistic muscle model is most likely to be practical (i.e. parameters can be estimated for human muscle) as well as accurate (i.e. correct forces are predicted for a wide range of conditions.

Actin Cytoskeleton↗

PubMed1998

Intrinsic muscle properties facilitate locomotor control - a computer simulation study.

The purpose of this study was to investigate, theoretically, to what extent muscle properties could contribute to recovery from perturbations during locomotion. Four models with different actuator properties were created: the FLVT model, which encompassed force-length (FL) and force-velocity (FV) characteristics of human muscles as well as muscle stimulation inputs as functions of time (T); the FLT model, which had muscles without force-velocity characteristics; the FVT model, which had muscles without specific force-length characteristics; and the MT model, which had no muscles but was driven by joint moments (M) as a function of time. Each model was exposed to static and dynamic perturbations and its response was examined. FLVT showed good resistance to both static can dynamic perturbations. FLT was resistant to static perturbation but could not counteract dynamic perturbation, whereas the opposite was found for FVT. MT could not counteract either of the perturbations. Based on the results of the simulations, skeletal muscle force-length-velocity properties, although interactively complex, contribute substantially to the dynamic stability of the musculoskeletal system.

Computer Simulation↗

PubMed1997

Assessment of the mechanical properties of area-elastic sport surfaces with video analysis.

Mechanical properties of a surface are assumed to be of importance with respect to injuries, comfort, and performance in sport. For a better understanding of the factors that do influence the etiology of injuries as well as comfort, a method was developed to compare mechanical characteristics of wooden area-elastic indoor surfaces. The method was based on video analysis of markers mounted on the surface during tests using human subjects performing movements. The method provided information concerning deflection, area-elasticity, and vibration. With the proposed methodology it was possible to detect differences with respect to these variables in differently built wooden sport surfaces. The accuracy of the analysis was greater than 0.1 mm. The results show that it was possible to use the proposed methodology in the assessment of the area-elastic wooden sport surfaces. This information may be at help in understanding the relation between surface characteristics and surface-related injuries, comfort, and possible fatigue.

Elasticity↗

PubMed1996

Computer simulation of landing movement in downhill skiing: anterior cruciate ligament injuries.

Anterior cruciate ligament (ACL) injuries typically occur in high-speed downhill skiing during the landing phase following a jump. A direct dynamics simulation model was developed which allows investigation of possible ACL injury mechanisms without the need to use actual skiers in a potentially dangerous environment. The model included multibody dynamics, muscle dynamics and a model for ski-snow interaction. The model's ability to reproduce an actual landing movement was investigated by minimizing the differences between measured and stimulated landing movements as a function of constant muscle stimulation levels. The remaining difference was mainly due to noise in the measurements. A small balance disturbance was induced to simulate an injury condition. This disturbance caused the modeled skier to fall slightly backwards. A recovery attempt was made by maximal activation of the quadriceps and iliopsoas muscles. Peak resultant shear force at the knee joint in ACL direction was substantially higher in the injury simulation (1001 N) when compared to the simulated normal landing movement (589 N). Taking into account quadriceps contraction and orientation of the ACL with respect to tibial plateau, peak ACL force during the injury simulation was estimated to be 1350 N, which is within the range of failure loads for this ligament. The external forces were mainly (75%) responsible for this loading. The contribution of the fully activated quadriceps muscles was only 25%. It was concluded that the model could reproduce a typical landing movement and is therefore considered to be sufficiently realistic. Second, the simulation results suggest that external forces are the main cause for ACL injuries during landing movements in downhill skiing.

Anterior Cruciate Ligament Injuries↗

PubMed1996

Modelling of force production in skeletal muscle undergoing stretch.

Many human movements involve eccentric contraction of muscles. Therefore, it is important that a theoretical model is able to represent the kinetic response of activated muscle during lengthening if it is to be applied to dynamic simulation of such movements. The so-called Hill and Distribution Moment models are two commonly used models of skeletal muscle. The Hill model is a phenomenological model based on experimental observations; the Distribution Moment model is based on the cross-bridge theory of muscle contraction. The ability of each of these models to predict the force-velocity relation has been considered previously; however, few attempts have been made to evaluate the force response of each model with respect to time during stretches at different velocities. The purpose of this study was to compare the predicted force-time responses of the Hill and Distribution Moment models to the actual force produced by the cat soleus during experimental iso-velocity stretches at maximal activation. Two stretch velocities were simulated: 7.2 and 400 mm s-1. Model parameters were derived from the literature where possible. In addition, model parameters were optimized to provide the best possible fit between model force predictions and experimental results at each velocity. The results of the study showed that using the Hill model, it was possible to describe qualitatively the force-time response of the muscle at both velocities of stretch using parameters derived from the literature. It was also possible to optimize a set of parameters for the Hill model to provide a quantitative description of the force-time response at each velocity. Using the Distribution Moment model, it was not possible to describe the force-time response of the muscle for both velocities using a single set of rate constants, suggesting that the cross-bridge theory, upon which the model is based, may have to be further evaluated for lengthening muscle. Further research is required to determine if the model results can be generalized to other muscles and other velocities of stretch.

Animals↗

PubMed1996

Why is countermovement jump height greater than squat jump height?

In the literature, it is well established that subjects are able to jump higher in a countermovement jump (CMJ) than in a squat jump (SJ). The purpose of this study was to estimate the relative contribution of the time available for force development and the storage and reutilization of elastic energy to the enhancement of performance in CMJ compared with SJ. Six male volleyball players performed CMJ and SJ. Kinematics, kinetics, and muscle electrical activity (EMG) from six muscles of the lower extremity were monitored. It was found that even when the body position at the start of push-off was the same in SJ as in CMJ, jump height was on average 3.4 cm greater in CMJ. The possibility that nonoptimal coordination in SJ explained the difference in jump height was ruled out: there were no signs of movement disintegration in SJ, and toe-off position was the same in SJ as in CMJ. The greater jump height in CMJ was attributed to the fact that the countermovement allowed the subjects to attain greater joint moments at the start of push-off. As a consequence, joint moments were greater over the first part of the range of joint extension in CMJ, so that more work could be produced than in SJ. To explain this finding, measured and manipulated kinematics and electromyographic activity were used as input for a model of the musculoskeletal system. According to simulation results, storage and reutilization of elastic energy could be ruled out as explanation for the enhancement of performance in CMJ over that in SJ. The crucial contribution of the countermovement seemed to be that it allowed the muscles to build up a high level of active state (fraction of attached cross-bridges) and force before the start of shortening, so that they were able to produce more work over the first part of their shortening distance.

Adult↗

PubMed1995

Direct dynamics simulation of the impact phase in heel-toe running.

The influence of muscle activation, position and velocities of body segments at touchdown and surface properties on impact forces during heel-toe running was investigated using a direct dynamics simulation technique. The runner was represented by a two-dimensional four- (rigid body) segment musculo-skeletal model. Incorporated into the muscle model were activation dynamics, force-length and force-velocity characteristics of seven major muscle groups of the lower extremities: mm. glutei, hamstrings, m. rectus femoris, mm. vasti, m. gastrocnemius, m. soleus and m. tibialis anterior. The vertical force-deformation characteristics of heel, shoe and ground were modeled by a non-linear visco-elastic element. The maximum of a typical simulated impact force was 1.6 times body weight. The influence of muscle activation was examined by generating muscle stimulation combinations which produce the same (experimentally determined) resultant joint moments at heelstrike. Simulated impact peak forces with these different combinations of muscle stimulation levels varied less than 10%. Without this restriction on initial joint moments, muscle activation had potentially a much larger effect on impact force. Impact peak force was to a great extent influenced by plantar flexion (85 N per degree of change in foot angle) and vertical velocity of the heel (212 N per 0.1 m s-1 change in velocity) at touchdown. Initial knee flexion (68 N per degree of change in leg angle) also played a role in the absorption of impact. Increased surface stiffness resulted in higher impact peak forces (60 N mm-1 decrease in deformation).(ABSTRACT TRUNCATED AT 250 WORDS)

Ankle Joint↗