Analyzing the EEG Energy of Quasi Brain Death using MEMD
Electroencephalography (EEG) based preliminary examination system has been proposed in the clinical brain death determination. This paper presents a novel data analysis algorithm based on multivariate empirical mode decomposition (MEMD) to calculate and evaluate the energy of EEG recorded from the comatose patients and brain deaths. MEMD is an extended approach of empirical mode decomposition (EMD), in which it overcomes the problem of the decomposed number and frequency, and enable to extract brain activity features from multi-channel EEG simultaneously. Comparison with the previous study by used EMD, not only the performance of computation complexity but also the accuracy of data analysis improved.
Yunchao Yin Jianting Cao Qiwei Shi Danilo P. Mandic Toshihisa Tanaka Rubin Wang
Saitama Institute of Technology, 1690 Fusaiji Fukaya-shi 369-0293 Saitama Japan Saitama Institute of Technology, 1690 Fusaiji Fukaya-shi 369-0293 Saitama Japan Brain Science Instit Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K. Tokyo University of Agriculture and Technology, 2-24-16 Nakacho Koganei-shi Tokyo 184-8588 Japan Bra East China University of Science and Technology, Meilong Road 130 Shanghai 200237
国际会议
2011亚太信号与信息处理协会年度峰会(APSIPAASC 2011)
西安
英文
1-6
2011-10-18（万方平台首次上网日期，不代表论文的发表时间）