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利用计算姿势控制模型解开帕金森病中的稳定性和灵活性程度。

Disentangling stability and flexibility degrees in Parkinson's disease using a computational postural control model.

机构信息

Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran.

Djawad Movafaghian Research Center in Rehab Technologies, Sharif University of Technology, Tehran, Iran.

出版信息

J Neuroeng Rehabil. 2019 Aug 14;16(1):104. doi: 10.1186/s12984-019-0574-0.

Abstract

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.

摘要

背景

帕金森病(PD)患者的姿势控制受损严重影响生活质量。平衡训练虽然可以改善运动和姿势稳定性,但由于缺乏对 PD 平衡训练神经生理机制的定量研究,阻碍了针对患者个体的治疗方法的发展。我们使用功能平衡和移动性测试、姿势描记术和姿势控制模型来评估平衡训练计划的效果。

方法

在 12 节平衡训练课程前后,记录了 40 名 PD 患者和 20 名健康对照者在刚性表面上进行的四项任务中的两种(R 任务)和两种在泡沫上的两种任务的中心压力(COP)数据。一个姿势控制模型被拟合来描述姿势描记术数据。该模型包括一个神经肌肉控制器、一个时间延迟和一个增益,用于缩放内部干扰扭矩。

结果

患者在训练前的轴向刚度导致在 R 任务中的 COP 速度较慢;这反映出内部扭矩增益较低。此外,患者在泡沫上表现出较差的稳定性,表现为异常高的摆动幅度。较低的控制参数和较高的时间延迟是导致患者异常高摆动幅度的原因。平衡训练改善了所有关于功能平衡和移动性的临床评分。一致地,“灵活性”的改善表现为摆动速度的增加(内部扭矩增益的增加)。平衡训练还有助于患者在泡沫不稳定的站立状态下发展“稳定性程度”(增加控制参数)并更快地做出反应。

结论

将常见的姿势描记术指标投影到姿势控制模型上,为揭示 PD 受损姿势控制的神经生理因素和不同恢复机制提供了一个定量框架。

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