Radboud University Nijmegen Medical Centre, Nijmegen Centre for Evidence Based Practice, Department of Rehabilitation, Nijmegen, The Netherlands.
Gait Posture. 2012 Mar;35(3):462-6. doi: 10.1016/j.gaitpost.2011.11.008. Epub 2011 Dec 22.
The mechanical efficiency of stepping to recover balance can be expressed by a biomechanical model that includes the trunk inclination angle and the angle of the leg at the instant of stepping-foot contact. The aim of the present study was to test the hypothesis that this model would accurately predict the successfulness of recovery attempts (recovery vs. falls) following large backward perturbations. Ten young participants were exposed to a series of 12 very large postural perturbations in the backward direction by means of a support-surface translation. At the instant of stepping-foot contact, we calculated the trunk inclination angle and the angle of the stepping leg with the vertical. Reaction time, step duration, step velocity and step length were also determined. A logistic regression analysis revealed that the model with leg and trunk inclination angles accurately predicted successful recovery, with a more forward tilted trunk and a further backward positioned leg increasing the probability of success. The set of spatiotemporal step variables was significantly less predictive. Over the course of the experiment, participants gradually became more successful in recovering balance, which coincided with an increase in leg but not in trunk angles. In conclusion, the body configuration at the instant of first stepping-foot contact accurately predicted successful balance recovery after a backward postural perturbation. Given the observation that participants improved their performance by increasing their leg angles, which suggests that it may be easier to improve this variable, compared to the trunk angle, by exercise interventions.
通过包含躯干倾斜角度和踏足接触瞬间腿部角度的生物力学模型,可以表达跨步恢复平衡的机械效率。本研究的目的是验证该模型是否能准确预测大向后干扰后恢复尝试(恢复与跌倒)的成功,10 名年轻参与者通过支撑面平移暴露在 12 次非常大的向后姿势干扰中。在踏足接触瞬间,我们计算了躯干倾斜角度和踏足腿与垂直的角度。还确定了反应时间、步幅持续时间、步幅速度和步幅长度。逻辑回归分析表明,带有腿部和躯干倾斜角度的模型可以准确预测成功的恢复,躯干更前倾,腿部更向后定位,增加成功的可能性。时空步变量集的预测能力显著降低。在实验过程中,参与者在恢复平衡方面逐渐变得更加成功,这与腿部角度的增加而不是躯干角度的增加相吻合。总之,在向后姿势干扰后,踏足接触瞬间的身体姿势可以准确预测平衡恢复的成功。鉴于参与者通过增加腿部角度来提高表现的观察结果,这表明通过运动干预,与躯干角度相比,可能更容易改善这个变量。