模压成型的EVA中底提供整个步态周期的最高缓冲。
Compression molded EVA midsole offers supreme cushioning throughout the gait cycle.
首先根据摆动距离计算出步态周期，并指定步态周期中的关键时刻。
The MGEI at each key moment is calculated from all the mean moment images in gait period.
结论早期使用A FO可以促进脑卒中偏瘫患者步态周期及各时相的改善。
Conclusion: Using the AFO in the early time can contribute to the improvements of gait cycle and its phases in the hemiplegic stroke patients.
用背景差方法得到运动人体的轮廓，通过步态周期分析提取步态序列的关键帧。
Body silhouettes are extracted by background subtraction, and cyclic gait analysis is performed to extract key frames.
结果 计算获得了该研究对象不同步行速度和路面坡度下踝关节、膝关节及髋关节在一个步态周期内的矢状面关节角的变化曲线以及主要肌肉的激活度变化曲线。
The mean joint angles of hip, knee and ankle in sagittal plane at different speeds and different slopes were calculated. The subject whose data was closest to the mean value could be easily found.
在对膝上假肢使用者健侧和残侧的步态进行检测的基础上，对健、残侧在步态周期内的地面反力、下肢运动和时相对称性进行了对比和分析，时相对称性差是膝上截肢者步态的主要问题。
Based on the data obtained from gait tests, the differences of ground reaction forces and the movements of lower limbs between the sound side and prosthetic side of above knee amputee were analyzed.
完成认知测验时，与受损害个体相比，正常个体步态呈规则周期性、抬脚速度更快，并且头部和躯体的运动也更迅速。
Healthy individuals demonstrated a more periodic gait with regular and higher velocity foot kicks and faster torso and head movement than impaired individuals when completing a cognitive task.
考虑到人体步态的周期性，步态实验的数据可以表示成富里哀级数的形式。
With a view to the periodicity of human gait, experimental data maybe expressed in the form of the Fourier series.
为了快速地提取步态，提出了一种基于周期序列宽度图的步态识别方法。
A novel gait recognition method based on periodic sequence width images is proposed in order to gain gait quickly and correctly.
结论：在自然行走过程中，偏瘫患者双下肢的单支撑期和摆动期的明显缩短是导致患者步行周期延长，步态异常，步速减慢，步行能力下降的根本原因。
Conclusion: The study indicates that the shorter single support time during the gait cycle in patients is responsible for the abnormal walking velocity , awful gait and decreased ability of walking.
得到了斜面倾角增大时样机的倍周期步态。
The period-doubling and chaotic gaits of passive dynamic walking have been analyzed.
周期序列宽度图中的灰度值及其变化能清晰地反映步态运动，是一种以图的形式直观准确表征步态时空变化的方法。
The vector sequences are turned into the periodic sequence width images, presented by grey values. These grey values can exactly depict the gait motion.
周期序列宽度图中的灰度值及其变化能清晰地反映步态运动，是一种以图的形式直观准确表征步态时空变化的方法。
The vector sequences are turned into the periodic sequence width images, presented by grey values. These grey values can exactly depict the gait motion.
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