A Bayesian classification of heart rate variability data
A Bayesian classification of heart rate variability data
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DOI：
10.1016/j.physa.2003.12.021
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发表时间：
2004-05
影响因子：
3.3
通讯作者：
R. Muirhead;R. Puff
中科院分区：
文献类型：
--
作者：
R. Muirhead;R. Puff
我们提出了一个简单的贝叶斯方法的时间序列信号的分类源于互斥的来源。特别地，该方法用于解决人类心率数据的24小时记录是由正常功能的心脏还是由表现出充血性心力衰竭症状的心脏产生的问题。我们的方法正确分类18个正常的心脏数据集，38个44充血性心力衰竭数据集。
We propose a simple Bayesian method for the classification of time series signals originating from mutually exclusive sources. In particular, the method is used to address the question of whether a 24-h recording of human heart rate data is produced by a normally functioning heart or by one exhibiting symptoms of congestive heart failure. Our method correctly classifies 18 of 18 normal heart data sets, and 38 of 44 congestive failure data sets.