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A Postural Control Model to Assess the Improvement of Balance Rehabilitation in Parkinson's Disease

机译:评估帕金森病平衡康复改善的姿势控制模型

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Studies have shown that balance and mobility in people with Parkinson's disease (PD) can improve through rehabilitation interventions. However, until now no quantitative method investigated how these patients improve their balance control. In this study, a single inverted pendulum model with PID controller was used to describe the improvement of forty PD patients after a 12-session therapy program, and to compare their balance with twenty healthy subjects. The Center of Pressure (COP) data were recorded in seven sensory conditions - on rigid and foam surface, each with eyes open and closed, and with visual disturbance; and stance on rigid surface with attached vibrator to the Achilles tendons. From COP data four Stabilogram Diffusion Function (SDF) measures were extracted. In order to find the appropriate model parameters (three control parameters and a noise gain) from the SDF measures, first model simulations were performed to tune an artificial neural network (ANN) which relates the SDF measures to the PID parameters, and second the trained ANN was used to find the suitable PID model parameters from the experimentally recorded SDF measures. Statistical analysis revealed that patients had lower control parameters and noise gain than healthy subjects; confirming reduced control ability and sensory information in PDs. Balance rehabilitation improved the patients' clinical scores, which is reflected in the increased control parameters (particularly in foam tasks), and noise gain (in tasks on rigid surface). The presented method provides a good and sensitive measure to describe functional balance and mobility in PD.
机译:研究表明,帕金森病(PD)的平衡和流动性可以通过康复干预来改善。然而,直到现在没有定量方法研究这些患者如何改善平衡控制。在这项研究中,使用PID控制器的单个倒立摆模型来描述12-会议治疗计划后四十PD患者的改进,并将其与20个健康受试者的平衡进行比较。压力中心(COP)数据被记录在七种感官条件下 - 刚性和泡沫表面上,每个孔表面打开和关闭,视觉干扰;和刚性表面上的姿势,带有附接振动器到Achilles肌腱。从COP数据中提取四个稳定值扩散功能(SDF)措施。为了从SDF测量找到适当的模型参数(三个控制参数和噪声增益),执行第一模拟模拟以调整人工神经网络(ANN),该人工神经网络(ANN)将SDF措施与PID参数相关,第二个模型模拟,以及第二训练ANN用于从实验记录的SDF措施中找到合适的PID模型参数。统计分析显示,患者的控制参数和噪声增益低于健康的受试者;确认PDS中的控制能力和感官信息。平衡康复改善了患者的临床评分,其反映在增加的控制参数(特别是泡沫任务)和噪声增益(刚性表面上的任务中)。该方法提供了良好且敏感的措施,以描述PD中的功能平衡和移动性。

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