Information entropy and dimension calculation on heart rate variability

1993 IEEE Annual Northeast Bioengineering Conference Pub Date : 1993-03-18 DOI:10.1109/NEBC.1993.404438

P.Z. Zhang, S. Reisman, W. Tapp, D. Cordero

{"title":"Information entropy and dimension calculation on heart rate variability","authors":"P.Z. Zhang, S. Reisman, W. Tapp, D. Cordero","doi":"10.1109/NEBC.1993.404438","DOIUrl":null,"url":null,"abstract":"An approach to construct the probability density curve (PDC) of a phase response curve (PRC), in which the PRC reflects directly heart rate fluctuations by phase shifts during different vagal stimuli, is presented. It was found that the width of the PDC usually represents the amount of heart rate variation. The narrow PDC with high peaks implies less heart rate variability, while the wide and flat PDC implies high heart rate variability. Based on the PDC, information entropy has been calculated. Information entropy can give the amount of information needed to specify the state of the PRC or the state of the heart rate variability to an accuracy of the box size. Current work has indicated that large information entropy means large heart rate variability and less predictability. On the other hand, information dimension has been derived from information entropies of the different box sizes. Information dimension is an index of the complexity of a system that generated the data. A low dimension means that less states are needed to describe the system while a large dimension means more states are required to describe the system.<<ETX>>","PeriodicalId":159783,"journal":{"name":"1993 IEEE Annual Northeast Bioengineering Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1993 IEEE Annual Northeast Bioengineering Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEBC.1993.404438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

Abstract

An approach to construct the probability density curve (PDC) of a phase response curve (PRC), in which the PRC reflects directly heart rate fluctuations by phase shifts during different vagal stimuli, is presented. It was found that the width of the PDC usually represents the amount of heart rate variation. The narrow PDC with high peaks implies less heart rate variability, while the wide and flat PDC implies high heart rate variability. Based on the PDC, information entropy has been calculated. Information entropy can give the amount of information needed to specify the state of the PRC or the state of the heart rate variability to an accuracy of the box size. Current work has indicated that large information entropy means large heart rate variability and less predictability. On the other hand, information dimension has been derived from information entropies of the different box sizes. Information dimension is an index of the complexity of a system that generated the data. A low dimension means that less states are needed to describe the system while a large dimension means more states are required to describe the system.<>

查看原文本刊更多论文

心率变异性的信息熵与维数计算

提出了一种构建相响应曲线概率密度曲线(PDC)的方法，其中PRC直接反映了不同迷走神经刺激下相移引起的心率波动。研究发现，PDC的宽度通常代表心率的变化量。窄且峰高的PDC表明心率变异性较小，而宽且平坦的PDC表明心率变异性较大。基于PDC计算信息熵。信息熵可以给出指定PRC状态或心率变异性状态所需的信息量，以达到框大小的精度。目前的研究表明，大的信息熵意味着大的心率变异性和更少的可预测性。另一方面，信息维度由不同盒子大小的信息熵得到。信息维度是生成数据的系统复杂性的索引。低维意味着需要更少的状态来描述系统，而大维意味着需要更多的状态来描述系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

1993 IEEE Annual Northeast Bioengineering Conference

自引率

0.00%

发文量