人体静态平衡运动力学分析中多元多尺度熵特征改进算法

发布时间：2018-05-18 04:32

本文选题：静态平衡 + 特征提取　；参考：《航天医学与医学工程》2017年05期

【摘要】：目的利用改进的多元多尺度熵特征对人体静态平衡运动力学信号进行分析。方法在多元多尺度熵计算中,要对多元延迟向量的维数进行扩展,本文针对性地将单个变量的依次嵌入改成对所有变量同时嵌入。结果改进算法的多元多尺度熵特征应用于多种平衡模式的实验中,处理速度更快,熵值在模式间的距离更大,模式内的散度更小,更易区分。结论本文算法提高了计算效率,改善了特征的可区分性,可以更好地分析人体的静态平衡能力。
[Abstract]:Objective to analyze the dynamic signals of human static equilibrium motion by using the improved multi-scale entropy. Methods in the multivariate multi-scale entropy calculation, the dimension of multivariate delay vector is extended. In this paper, the sequence embedding of a single variable is changed into simultaneous embedding of all variables. Results the multi-scale and multi-scale entropy feature of the improved algorithm is applied to the experiments of multiple equilibrium models. The processing speed is faster, the entropy value is larger in the distance between the modes, and the divergence in the model is smaller and easier to distinguish. Conclusion the proposed algorithm improves the computational efficiency, improves the distinctiveness of the features, and can better analyze the static balance ability of the human body.
【作者单位】：杭州电子科技大学智能控制与机器人研究所;
【基金】：国家自然科学基金(61671197)
【分类号】：R318.01;TP212.9

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