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中文摘要：
目的步态信号的研究是现今生物医学研究的重点。对不同步态信号的分析，有助于进行临床诊断和医学研究。方法采用Lopez—Mancini—CalbetDivergence（LMCD）的复杂度分析方法，对老年人、年轻人和帕金森患者各10例的步态信号分别计算复杂度，并对实验数据进行方差分析。结果3种步态信号的复杂度差异显著性，年轻人的步态信号复杂度最大，老年人次之，帕金森患者的复杂度最小。结论基于LMCD的步态信号复杂度分析可以得出人的步态信号随机性的强弱。
英文摘要：
Objective The gait signal is now the focus of biomedical research and the analysis of gait signal is helpful to clinical diagnosis and medical research. Methods The Lopez-Mancini-Calbet Divergence （LMCD） ,the method of complexity analysis is used to calculate ten cases of the complexity of the elderly, young people and patients with Parkinson＇ s gait signal, and then we detect the experimental data by variance detection. Results The differences among the complexity of the three groups of gait signals are significant. The gait signal complexity of the young people group is higher than that of the elderly people group, and that of the Parkinson＇ s patient group is the lowest. Conclusions The complexity analysis of gait signal based on LMCD can get the strength of the randomness of human gait signal.
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