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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能力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,帕金森氏病(PD)患者的平衡和活动能力可以通过康复干预得到改善。但是,到目前为止,还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,使用带有PID控制器的单个倒立摆模型来描述40个PD患者经过12个疗程的治疗方案后的改善情况,并将其与20名健康受试者的平衡进行比较。压力中心(COP)数据记录在七个感官条件下-在刚性和泡沫表面上,每个眼睛睁开和闭合,并且有视觉障碍;并在与阿喀琉斯腱附有振动器的刚性表面上保持姿势。从COP数据中提取了四个稳定图像扩散功能(SDF)度量。为了从SDF措施中找到合适的模型参数(三个控制参数和噪声增益),首先进行了模型仿真,以调整将SDF措施与PID参数相关联的人工神经网络(ANN), ANN用于从实验记录的SDF度量中找到合适的PID模型参数。统计分析表明,与健康受试者相比,患者的控制参数和噪声增益较低。确认PD的控制能力和感觉信息降低。平衡康复改善了患者的临床评分,这反映在增加的控制参数(尤其是泡沫任务)和噪音增加(刚性表面任务)上。所提出的方法提供了一种很好且敏感的方法来描述PD中的功能平衡和移动性。

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