title: [Analysis of HRV from brain injury by use of nonextensive relative entropy].
abstract: Due to its great clinical significance, brain injury following cardiac arrest (CA) has attracted more attention now. Meanwhile, there are currently no approved real time objective methods used to monitor brain injury following CA. In this study, we adopt the method of nonextensive Kullback-Leibler Entropy in investigating the HRV signals from brain injury and compare the result with that of corresponding EEG analysis. The comparative analysis shows that Kullback-Leibler Entropy can reveal the injury level of brain following CA. And we propose a novel quantitative approach for monitoring brain injury.
authors.affiliation: Department of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200030, China.
authors.forename: Hong
authors.initials: H
authors.lastname: Zhang
authors.forename: Yihong
authors.initials: Y
authors.lastname: Qiu
authors.forename: Ziming
authors.initials: Z
authors.lastname: Wang
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Cai
authors.forename: Yisheng
authors.initials: Y
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology / Q000503:physiopathology*; D002545:Brain Ischemia / Q000503:physiopathology*; D004569:Electroencephalography; D006323:Heart Arrest / Q000150:complications; D006339:Heart Rate / Q000502:physiology*; D006801:Humans