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On the calculation of sample entropy using continuous and discrete human gait data

机译:关于使用连续和离散人体步态数据计算样本熵

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摘要

Sample entropy (SE) has relative consistency using biologically-derived, discrete data >500 data points. For certain populations, collecting this quantity is not feasible and continuous data has been used. The effect of using continuous versus discrete data on SE is unknown, nor are the relative effects of sampling rate and input parameters m (comparison vector length) and r (tolerance). Eleven subjects walked for 10-minutes and continuous joint angles (480Hz) were calculated for each lower-extremity joint. Data were downsampled (240, 120, 60Hz) and discrete range-of-motion was calculated. SE was quantified for angles and range-of-motion at all sampling rates and multiple combinations of parameters. A differential relationship between joints was observed between range-of-motion and joint angles. Range-of-motion SE showed no difference; whereas, joint angle SE significantly decreased from ankle to knee to hip. To confirm findings from biological data, continuous signals with manipulations to frequency, amplitude, and both were generated and underwent similar analysis to the biological data. In general, changes to m, r, and sampling rate had a greater effect on continuous compared to discrete data. Discrete data was robust to sampling rate and m. It is recommended that different data types not be compared and discrete data be used for SE.
机译:使用大于500个数据点的生物离散数据,样本熵(SE)具有相对一致性。对于某些人群,收集此数量是不可行的,并且已使用了连续数据。在SE上使用连续数据还是离散数据的影响是未知的,采样率和输入参数m(比较矢量长度)和r(容差)的相对影响也不是很明显。 11名受试者步行10分钟,并为每个下肢关节计算了连续的关节角度(480Hz)。对数据进行下采样(240、120、60Hz),并计算离散的运动范围。在所有采样率和参数的多个组合下,对SE的角度和运动范围进行了量化。在运动范围和关节角度之间观察到关节之间的差异关系。动作范围SE无差异。相反,关节角度SE从脚踝到膝盖再到臀部都明显减小。为了确认从生物学数据中得到的发现,产生了对频率,幅度和两者均具有操纵性的连续信号,并对其进行了与生物学数据类似的分析。通常,与离散数据相比,m,r和采样率的变化对连续性的影响更大。离散数据对采样率和m有鲁棒性。建议不要比较不同的数据类型,并且将离散数据用于SE。

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