Karmakar Chandan, Khandoker Ahsan, Begg Rezaul, Palaniswami Marimuthu
Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia.
Comput Methods Biomech Biomed Engin. 2013;16(5):554-64. doi: 10.1080/10255842.2011.628943. Epub 2012 Jan 30.
Ageing influences gait patterns which in turn can affect the balance control of human locomotion. Entropy-based regularity and complexity measures have been highly effective in analysing a broad range of physiological signals. Minimum toe clearance (MTC) is an event during the swing phase of the gait cycle and is highly sensitive to the spatial balance control properties of the locomotor system. The aim of this research was to investigate the regularity and complexity of the MTC time series due to healthy ageing and locomotors' disorders. MTC data from 30 healthy young (HY), 27 healthy elderly (HE) and 10 falls risk (FR) elderly subjects with balance problems were analysed. Continuous MTC data were collected and using the first 500 data points, MTC mean, standard deviation (SD) and entropy-based complexity analysis were performed using sample entropy (SampEn) for different window lengths (m) and filtering levels (r). The MTC SampEn values were lower in the FR group compared to the HY and HE groups for all m and r. The HY group had a greater mean SampEn value than both HE and FR reflecting higher complexity in their MTC series. The mean SampEn values of HY and FR groups were found significantly different for m = 2, 4, 5 and r = (0.1-0.9) × SD, (0.3-0.9) × SD and (0.3-0.9) × SD, respectively. They were also significant difference between HE and FR groups for m = 4-5 and r = (0.3-0.7) × SD, but no significant differences were seen between HY and HE groups for any m and r. A significant correlation of SampEn with SD of MTC was revealed for the HY and HE groups only, suggesting that locomotor disorders could significantly change the regularity or the complexity of the MTC series while healthy ageing does not. These results can be usefully applied to the early diagnosis of common gait pathologies.
衰老会影响步态模式，而步态模式反过来又会影响人体运动的平衡控制。基于熵的规律性和复杂性度量在分析广泛的生理信号方面非常有效。最小脚趾间隙（MTC）是步态周期摆动阶段的一个事件，对运动系统的空间平衡控制特性高度敏感。本研究的目的是调查健康衰老和运动障碍导致的MTC时间序列的规律性和复杂性。分析了来自30名健康年轻人（HY）、27名健康老年人（HE）和10名有平衡问题的跌倒风险（FR）老年人的MTC数据。收集了连续的MTC数据，并使用前500个数据点，针对不同的窗口长度（m）和滤波水平（r），使用样本熵（SampEn）进行MTC均值、标准差（SD）和基于熵的复杂性分析。对于所有的m和r，FR组的MTC SampEn值均低于HY组和HE组。HY组的平均SampEn值高于HE组和FR组，反映出其MTC序列具有更高的复杂性。对于m = 2、4、5以及r =（0.1 - 0.9）× SD、（0.3 - 0.9）× SD和（0.3 - 0.9）× SD，分别发现HY组和FR组的平均SampEn值存在显著差异。对于m = 4 - 5以及r =（0.3 - 0.7）× SD，HE组和FR组之间也存在显著差异，但对于任何m和r，HY组和HE组之间均未观察到显著差异。仅在HY组和HE组中发现SampEn与MTC的SD之间存在显著相关性，这表明运动障碍会显著改变MTC序列的规律性或复杂性，而健康衰老则不会。这些结果可有效地应用于常见步态病理学的早期诊断。
