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Gait complexity and frequency content analyses of patients with Parkinson's disease

机译：帕金森氏病患者的步态复杂度和频率含量分析

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The gait kinematics for Parkinson's disease (PD) are usually examined in the time domain and limited to selected points on motion-time graphs. Wavelet analysis allows the examination of the whole waveform and demonstrates a high potential to assess the effects of PD treatment. The purpose of this study was to investigate whether differences existed in gait complexity and the frequency content of foot trajectories during walking between patients with PD and healthy individuals by using wavelet analyses. Fifteen persons with idiopathic PD and eleven healthy age- and height- matched healthy adults (HAs) were recruited. The foot trajectories of each subject during walking were detected by using a three-camera Optotrak Certus motion capture system. The scale wavelet energy raitos and wavelet entropy were computed after seven-scale wavelet decomposition, and the results of the two groups were compared using Wilcoxon rank-sum test with Bonferroni correction for multiple testing. The results showed that, the PD subjects walked with a higher degree of complexity for the foot motion in anteroposterior direction and a lower degree of complexity for the foot motion in vertical direction. Both groups had comparable gait frequency, but the differences in the energy distributed over some frequency bands were significant between the PD and control groups. In addition to previously described gait kinematics in time domain, the parameters of scale wavelet energy ratios and wavelet entropy could be used to provide additional insight into gait changes.
机译：帕金森氏病（PD）的步态运动学通常在时域中检查，并且仅限于运动时间图上的选定点。小波分析可以检查整个波形，并显示出评估PD治疗效果的巨大潜力。这项研究的目的是通过小波分析调查PD患者和健康个体之间步态复杂性和步行过程中脚部轨迹的频率含量是否存在差异。招募了15名特发性PD患者和11名年龄与身高匹配的健康成人（HAs）。使用三相机Optotrak Certus运动捕捉系统检测步行过程中每个对象的脚部轨迹。七尺度小波分解后计算尺度小波能量Raitos和小波熵，并使用Wilcoxon秩和检验和Bonferroni校正对两组的结果进行多次测试。结果表明，PD受试者的步行在前后方向上具有较高的复杂度，而在竖直方向上具有较低的复杂度。两组步态频率相当，但PD和对照组之间在某些频带上分布的能量差异显着。除了在时域中先前描述的步态运动学之外，比例小波能量比和小波熵的参数可以用来提供对步态变化的更多了解。

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