BACKGROUND Impaired postural control in Parkinson's disease (PD) seriously compromises life quality. Although balance training improves mobility and postural stability, lack of quantitative studies on the neurophysiological mechanisms of balance training in PD impedes the development of patient-specific therapies. We evaluated the effects of a balance-training program using functional balance and mobility tests, posturography, and a postural control model. METHODS Center-of-pressure (COP) data of 40 PD patients before and after a 12-session balance-training program, and 20 healthy control subjects were recorded in four conditions with two tasks on a rigid surface (R-tasks) and two on foam. A postural control model was fitted to describe the posturography data. The model comprises a neuromuscular controller, a time delay, and a gain scaling the internal disturbance torque. RESULTS Patients' axial rigidity before training resulted in slower COP velocity in R-tasks; which was reflected as lower internal torque gain. Furthermore, patients exhibited poor stability on foam, remarked by abnormal higher sway amplitude. Lower control parameters as well as higher time delay were responsible for patients' abnormal high sway amplitude. Balance training improved all clinical scores on functional balance and mobility. Consistently, improved 'flexibility' appeared as enhanced sway velocity (increased internal torque gain). Balance training also helped patients to develop the 'stability degree' (increase control parameters), and to respond more quickly in unstable condition of stance on foam. CONCLUSIONS Projection of the common posturography measures on a postural control model provided a quantitative framework for unraveling the neurophysiological factors and different recovery mechanisms in impaired postural control in PD.

中文翻译：

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使用计算姿势控制模型解开帕金森氏病的稳定性和柔韧性度。

背景技术帕金森氏病（PD）中姿势控制的受损严重损害了生活质量。尽管平衡训练可改善活动能力和姿势稳定性，但缺乏有关PD平衡训练的神经生理机制的定量研究阻碍了针对患者的疗法的发展。我们使用功能平衡和移动性测试，姿势描记法和姿势控制模型评估了平衡训练计划的效果。方法在12个阶段的平衡训练计划前后，对40名PD患者和20名健康对照受试者的压力中心（COP）数据进行了记录，分别在四种情况下在刚性表面执行两项任务（R任务），在两项进行在泡沫上。拟合了姿势控制模型来描述姿势摄影数据。该模型包括神经肌肉控制器，时间延迟，增益调节内部干扰转矩。结果训练前患者的轴向僵硬导致R任务中的COP速度降低。这反映为较低的内部扭矩增益。此外，患者表现出对泡沫的不良稳定性，异常高的摇摆幅度表明了这一点。较低的控制参数以及较高的时间延迟是造成患者异常高摆幅的原因。平衡训练改善了所有有关功能平衡和活动性的临床评分。一致地，随着摇摆速度的增加（内部扭矩增益的增加），改善了的“柔韧性”。平衡训练还帮助患者发展“稳定度”（增加控制参数），并在不稳定的泡沫姿势下更快速地做出反应。