中文摘要：

作为人体输出生理信号之一的步态信号通常呈现一定的分形结构,具有明显的非线性特征,如何准确地探测到人体运动控制这一复杂生理系统的动力学特征具有重要的现实意义.本文通过一种改进的重标度极差法准确地捕捉到了不同自由行走速度下人体步态信号的动力学分形特征,而将原始步态时间间隔序列随机打乱顺序,获得的新序列则呈现出明显的随机性;通过与按节拍器产生的三种对应行走速率下的步态信号进行分析和比较后发现：正常健康人体输出的步态信号呈现出长程正相关性,而按节拍器节律获得的步态信号则长程正相关性减弱甚至消失,证明了人体运动控制系统调控输出步态信号的重要性.步态信号的动力学分形特性是健康人体的固有特征,具有很强的鲁棒性.缩短步态时间间隔序列长度后分析,该方法依然能够有效地探测到正常健康人体步态信号的动力学特征,并且算法简单可靠、运算快速、参数敏感、抗干扰能力强,研究结果对于人体运动控制系统的建模以及量化步态信号动力学的生理状态具有一定的应用价值.

英文摘要：

The stride interval is a measure of the gait rhythm and is typically defined as the time from the initial heel strike to the next heel strike of the same foot.At first inspection,human walking appears to be a periodic and regular process.However,closer examination reveals small fluctuations in the gait pattern,even under constant conditions.One possible explanation for these stride-to-stride variations in the walking rhythm is that they simply represent uncorrelated noise superimposed on a basically regular process.A second possibility is that there are finite-range correlations： the current value is only influenced by the most recent stride intervals,but over the long term,fluctuations are random.A third and less intuitive possibility is that the fluctuations in the stride interval exhibit long-range correlations,as seen in a wide class of scale-free phenomena.In this case,the stride interval at any instant would depend on the interval at relatively remote times,and this dependence would decay in a scale-free（fractal-like）,power-law fashion. Actually,human gait,as one of the physiological signals,normally exhibits a fractal structure and has an obviously nonlinear characteristic.How to accurately detect dynamics of human locomotor control system is of much practical significance.An improved rescaled range analysis method in the paper was used to precisely obtain the fractal dynamics of human gait at different free walking speeds,whereas the new time series resulting from the original gait fluctuation sequence randomly shuffled became total random.Long-range correlations of healthy human gait under free condition at all three walking rates were observed,while correlations degraded or even disappeared during three corresponding metronomically-paced walks.The method can be still effective in probing the fractal dynamics of human gait with data length shortened.These findings indicate that the fractal dynamics of walking rhythm are normally quite robust and intrinsic to human locomotor system.It further impli