Al-Nashash Hasan A, Paul Joseph S, Ziai Wendy C, Hanley Daniel F, Thakor Nitish V
School of Engineering, American University of Sharjah, Sharjah, United Arab Emirates.
Ann Biomed Eng. 2003 Jun;31(6):653-8. doi: 10.1114/1.1575757.
In this paper, subband wavelet entropy (SWE) is used for the segmentation of electroencephalographic signals (EEG) recorded during injury and recovery following global cerebral ischemia. Wavelet analysis is used to decompose the EEG into standard clinical subbands followed by computation of the Shannon entropy. The EEG was measured from rodent brains in a controlled experimental brain injury model by hypoxic-ischemic cardiac arrest. Results show that while the relative EEG power failed to reveal the order of bursting activity associated with recovery, SWE was used to segment the EEG and delineate the initial bursting periods in each subband. Based on entropy variations obtained from a cohort of animals with graded levels of hypoxic-ischemic cardiac arrest, an intermittent pattern of bursting was observed in the high frequency bands.
在本文中，子带小波熵（SWE）用于对全脑缺血损伤及恢复过程中记录的脑电图信号（EEG）进行分割。小波分析用于将EEG分解为标准临床子带，随后计算香农熵。通过缺氧缺血性心脏骤停，在受控实验性脑损伤模型中测量啮齿动物大脑的EEG。结果表明，虽然相对EEG功率未能揭示与恢复相关的爆发活动顺序，但SWE用于分割EEG并描绘每个子带中的初始爆发期。基于从一组具有不同程度缺氧缺血性心脏骤停的动物获得的熵变化，在高频带中观察到爆发的间歇性模式。
