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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >On the use of information theory for detecting upper limb motor dysfunction: An application to Parkinson's disease
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On the use of information theory for detecting upper limb motor dysfunction: An application to Parkinson's disease

机译：信息论在检测上肢运动功能障碍中的应用：在帕金森氏病中的应用

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Parkinson's disease (PD) is a chronic neurodegenerative disorder characterized by a selective loss of dopaminergic neurons in the substantia nigra, decreased striatal dopamine levels, and consequent extrapyramidal motor dysfunctions. Several potential early diagnostic markers of PD have been proposed. Since they have not been validated in presymptomatic PD, the diagnosis and monitoring of the disease is based on subjective clinical assessment of cognitive and motor symptoms. In this study, we investigated interjoint coordination synergies in the upper limb of healthy and parkinsonian subjects during the performance of unconstrained linear-periodic movements in a horizontal plane using the mutual information (MI). We found that the MI is a sensitive metric in detecting upper limb motor dysfunction, thus suggesting that this method might be applicable to quantitatively evaluating the effects of the antiparkinsonian medication and to monitor the disease progression.
机译：帕金森氏病（PD）是一种慢性神经退行性疾病，其特征是黑质中的多巴胺能神经元选择性丢失，纹状体多巴胺水平降低以及随之而来的锥体束外运动功能障碍。已经提出了PD的几种潜在的早期诊断标记。由于尚未通过症状前PD对其进行验证，因此该疾病的诊断和监测基于认知和运动症状的主观临床评估。在这项研究中，我们使用互信息（MI）研究了健康人和帕金森病患者上肢在水平面内不受约束的线性周期性运动过程中的关节间协调协同增效作用。我们发现MI是检测上肢运动功能障碍的敏感指标，因此表明该方法可能适用于定量评估抗帕金森病药物的作用并监测疾病的进展。

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