ACL injuries identifiable for pre-participation imagiological analysis: Risk factors

Identification of pre-participation risk factors for noncontact anterior cruciate ligament (ACL) injuries has been attracting a great deal of interest in the sports medicine and traumatology communities. Appropriate methods that enable predicting which patients could benefit from pre- ventive strategies are most welcome. This would enable athlete-specific training and conditioning or tailored equipment in order to develop appropriate strategies to reduce incidence of injury. In order to accomplish these goals, the ideal system should be able to assess both anatomic and functional features. Complementarily, the screening method must be cost-effective and suited for widespread application. Anatomic study protocol requiring only standard X rays could answer some of such demands. Dynamic MRI/CT evaluation and electronically assisted pivot-shift evaluation can be powerful tools providing complementary information. These upcoming insights, when validated and properly combined, envision changing pre-participation knee examination in the near future. Herein different methods (validated or under research) aiming to improve the capacity to identify persons/athletes with higher risk for ACL injury are overviewed.

Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?

It is widely accepted that humans and animals minimize energetic cost while walking. While such principles predict average behavior, they do not explain the variability observed in walking. For robust performance, walking movements must adapt at each step, not just on average. Here, we propose an analytical framework that reconciles issues of optimality, redundancy, and stochasticity. For human treadmill walking, we defined a goal function to formulate a precise mathematical definition of one possible control strategy: maintain constant speed at each stride. We recorded stride times and stride lengths from healthy subjects walking at five speeds. The specified goal function yielded a decomposition of stride-to-stride variations into new gait variables explicitly related to achieving the hypothesized strategy. Subjects exhibited greatly decreased variability for goal-relevant gait fluctuations directly related to achieving this strategy, but far greater variability for goal-irrelevant fluctuations. More importantly, humans immediately corrected goal-relevant deviations at each successive stride, while allowing goal-irrelevant deviations to persist across multiple strides. To demonstrate that this was not the only strategy people could have used to successfully accomplish the task, we created three surrogate data sets. Each tested a specific alternative hypothesis that subjects used a different strategy that made no reference to the hypothesized goal function. Humans did not adopt any of these viable alternative strategies. Finally, we developed a sequence of stochastic control models of stride-to-stride variability for walking, based on the Minimum Intervention Principle. We demonstrate that healthy humans are not precisely “optimal,” but instead consistently slightly over-correct small deviations in walking speed at each stride. Our results reveal a new governing principle for regulating stride-to-stride fluctuations in human walking that acts independently of, but in parallel with, minimizing energetic cost. Thus, humans exploit task redundancies to achieve robust control while minimizing effort and allowing potentially beneficial motor variability

Effects of Perturbation-Based Slip Training Using a Virtual Reality Environment on Slip-induced Falls

The purpose of the current study was to design and evaluate the effectiveness of virtual reality training in improving recovery reactions and reducing fall frequency in older adults. Twenty-four older adults were recruited and randomly assigned to two groups (virtual reality training and control). Both groups underwent three sessions including baseline slip, training and transfer of training on slippery surface. Both groups experienced two slips, one during baseline and the other during the transfer of training trial. The training group underwent twelve simulated slips using a visual perturbation induced by tilting a virtual reality scene while walking on the treadmill and the control group performed normal walking during the training session. Kinematic and kinetic data were collected during all the sessions. Results demonstrated a reduced incidence of falls in the training group during the transfer of training trial as compared to the control group. The training group was able to transfer reactive control strategies learned during training to the second slip trial. The reactive adjustments included reduced slip distance. Additionally, gait parameters reflective of gait instability (stride length, step width, variability in stride velocity) reduced after walking in the VR environment for 15–20 min. The results indicated a beneficial effect of the virtual reality training in reducing slip severity and recovery kinematics in healthy older adults