首页> 外文期刊>Journal of electromyography and kinesiology: Official journal of the International Society of Electrophysiological Kinesiology >EMG signal morphology and kinematic parameters in essential tremor and Parkinson's disease patients
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EMG signal morphology and kinematic parameters in essential tremor and Parkinson's disease patients

机译:原发性震颤和帕金森氏病患者的肌电信号形态学和运动学参数

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The aim of this work was to differentiate patients with essential tremor from patients with Parkinson's disease. Electromyographic data from biceps brachii muscles and kinematic data from arms during isometric tension of the arms were measured from 17 patients with essential tremor, 35 patients with Parkinson's disease and 40 healthy controls. The EMG signals were divided to smaller segments from which histograms were calculated. The histogram shape was analysed with a feature dimension reduction method, the principal component analysis, and the shape parameters were used to differentiate between different subject groups. Three parameters, RMS-amplitude, sample entropy and peak frequency were determined from the kinematic measurements of the arms. The height and the side differences of the histogram were the most effective for differentiating between essential tremor and Parkinson's disease groups. The histogram parameters of patients with essential tremor were more similar to patients with Parkinson's disease than healthy controls. With this method it was possible to discriminate 13/17 patients with essential tremor from 26/35 patients with Parkinson's disease and 14/17 patients with essential tremor from 29/40 healthy controls. The kinematic parameters of patients with essential tremor were closer to parameters of patients with Parkinson's disease compared to healthy controls. Combining EMG and kinematic analysis did not increase discrimination efficiency but provided more reliability to the discrimination of subject groups.
机译:这项工作的目的是将原发性震颤患者与帕金森氏病患者区分开。从17名原发性震颤患者,35例帕金森氏病患者和40名健康对照中测量了肱二头肌肌肉的肌电数据和手臂等轴测期间手臂的运动学数据。 EMG信号被分为较小的部分,从中可以计算出直方图。直方图形状通过特征维数缩减方法进行分析,主成分分析,形状参数用于区分不同的对象组。从臂的运动学测量中确定了三个参数,RMS振幅,样品熵和峰值频率。直方图的高度和侧面差异对区分原发性震颤和帕金森氏病组最有效。与健康对照组相比,原发性震颤患者的直方图参数与帕金森氏病患者更相似。通过这种方法,可以将13/17例原发性震颤患者与26/35帕金森病患者和14/17例原发性震颤患者区别于29/40名健康对照者。与健康对照组相比,原发性震颤患者的运动学参数更接近帕金森氏病患者的参数。将肌电图和运动学分析相结合并不能提高判别效率,但可以为受试者群体的判别提供更高的可靠性。

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