摘要
采用关联维数、分形维数、尺度指数分析38例受试者麻醉期心率变异性信号的分形特性。结果表明:麻醉期心搏周期有显著性的分形特性变化,麻醉状态下心率变异性信号的关联维数(P<0.000001)明显低于清醒状态,而短时程尺度指数α1(P<0.0001)显著性地高于清醒状态。说明了麻醉期心率变异性信号的分形特性有明显地变化,提示运用非趋势波动分析方法分析麻醉期心率变异性信号的分形特性更适合于临床麻醉深度监测。
By use of fractal analysis indexes-correlation dimension , fractal dimension and scaling exponent, the heart rate variability signals obtained from 38 subjects' ECG during anesthesia are analyzed. The results show that there is an obvious change of fractal characteristic of heart rate variability during anesthesia. The correlation dimension(P〈0. 000001) during anesthesia is evidently less than that during consciousness, while the short-range scaling exponent a2 (P〈0. 0001) during consciousness is evidently less than that during anesthesia. These illustrate that the difference in fractal characteristic between anesthesia and well-balanced state can be detected by the fractal analysis of heart rate variability. In the end, the paper poses that the analysis of heart rate variability is fit for monitoring the depth of anesthesia by detrended fluctuation analysis.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2006年第3期492-495,共4页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(60271011)
关键词
心率变异性
麻醉深度
分形特性分析
Heart rate variability(HRV) The depth of anesthesia Analysis of fractal characteristic