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.
A model of muscle energy expenditure was developed for predicting thermal, as well as mechanical energy liberation during simulated muscle contractions. The model was designed to yield energy (heat and work) rate predictions appropriate for human skeletal muscle contracting at normal body temperature. The basic form of the present model is similar to many previous models of muscle energy expenditure, but parameter values were based almost entirely on mammalian muscle data, with preference given to human data where possible. Nonlinear phenomena associated with submaximal activation were also incorporated. The muscle energy model was evaluated at varying levels of complexity, ranging from simulated contractions of isolated muscle, to simulations of whole body locomotion. In all cases, acceptable agreement was found between simulated and experimental energy liberation. The present model should be useful in future studies of the energetics of human movement using forward dynamic computer simulation.
regret that there were errors in the parameter values that pertain to equation 4.The phrase immediately following equation 4 should have read, " . . . where A 1 ¼ 80 ms and A 2 ¼ 0.50 ms for t ACT , and A 1 ¼ 95 ms and A 2 ¼ 0.60 ms for t DEACT ".
The skeleton of Australopithecus afarensis (A.L. 288-1, better known as "Lucy") is by far the most complete record of locomotor morphology of early hominids currently available. Even though researchers agree that the postcranial skeleton of Lucy shows morphological features indicative of bipedality, only a few studies have investigated Lucy's bipedal locomotion itself. Lucy's energy expenditure during locomotion has been the topic of much speculation, but has not been investigated, except for several estimates derived from experimental data collected on other animals. To gain further insights into how Lucy may have walked, we generated a full three-dimensional (3D) reconstruction and forward-dynamic simulation of upright bipedal locomotion of this ancient human ancestor. Laser-scanned 3D bone geometries were combined with state-of-the-art neuromusculoskeletal modeling and simulation techniques from computational biomechanics. A detailed full 3D neuromusculoskeletal model was developed that encompassed all major bones, joints (10), and muscles (52) of the lower extremity. A model of muscle force and heat production was used to actuate the musculoskeletal system, and to estimate total energy expenditure during locomotion. Neural activation profiles for each of the 52 muscles that produced a single step of locomotion, while at the same time minimizing the energy consumed per meter traveled, were searched through numerical optimization. The numerical optimization resulted in smooth locomotor kinematics, and the predicted energy expenditure was appropriate for upright bipedal walking in an individual of Lucy's body size.
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