项目名称: 基于模糊思想与信号质量评估协同作用的熵测度理论和技术研究
项目编号: No.61201049
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 电子学与信息系统
项目作者: 刘澄玉
作者单位: 山东大学
项目金额: 25万元
中文摘要: 心血管潜在危险评估是世界各国面临的重大难题,生理信号熵测度分析是解决该问题的有效途径。然而,熵测度易受多种因素影响、准确性难以保证,成为制约该技术临床应用的主要瓶颈。为了提高熵测度统计稳定性,本项目拟通过研究不同影响因素与统计稳定性单一或多变量函数关系建立量化评估模型,确定参数最优选值原则;考虑到信号质量是算法准确性的前提,我们拟研究新的心电信号质量评估算法,建立依据信号质量指数不同而可调的熵测度计算模式;以指数函数为基础寻求更好的隶属函数,融合信号质量指数,提出新的熵测度算法,并对算法一致性和敏感性进行检验。本项目旨在探求基于模糊思想和信号质量评估协同作用的熵测度算法构建机制,为提高生理信号熵测度分析的准确性提供一些新的理论和方法,进而为心血管病早期筛查和长期监测等医学临床应用提供理论和技术支持。
中文关键词: 熵算法;模糊测度熵;时间序列复杂度分析;心电信号质量评估;心血管时间序列
英文摘要: Potential risk assessment for cardiovascular system has become a worldwide problem. The entropy measure analysis of physiological signals is an effective way to solve it. However, entropy measure is susceptible to a variety of factors and has a low accuracy. In order to improve the statistical stability, the single- or multi-variable relationship between different factors and statistical stability will be studied and the quantitative assessment model will be established. So the optimum parameters could be obtained. Then the quality assessment algorithm of the electrocardiogram (ECG) signal will be studied since the signal quality is important for the accuracy of entropy measure. We will propose a new calculation mode for entropy measure, which could adjusts itself according to different signal quality index. Subsequently, we will test the different membership functions and determine the proper one. The determined membership function, combined with the signal quality index, will be used to construct the new entropy measure. Finally, the consistency and sensitivity of new entropy measure will be evaluated. This project aims to explore the construct mechanisms of new entropy measure based on the synergism between fuzzy concept and signal quality assessment. It will improve the analysis accuracy of physiological sig
英文关键词: Entropy algorithm;Fuzzy measure entropy;Complexity analysis of time series;ECG signal quality assessment;Cardiovascular time series