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新生儿心动周期信号混沌特征分析及参考值测定 被引量:1

Analysis of chaotic characteristics and reference values of heart period signals in normal neonates
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摘要 目的 对正常新生儿心动周期信号混沌特征分析及参考值测定。方法 用重庆医科大学生物医学工程研究室研制的儿童心动周期信号混沌特征分析系统,II导联,采样频率300 Hz,获得512 心动周期组成的心动周期信号(HPS) 。计算HPS的混沌特征参数:相对分散度(HRD)、李氏指数(HLE) 、分维数(HFD) 和混沌度(HCC)。分析HPS的功率谱和动态谱。计算HPS的功率谱参数9 项。结果 正常新生儿HPS 的混沌特征参数为:HRD6 .33 ±1 .87 ;HLE3.17 ±0.71 ;HFD1.83 ±0.04;HCC19.99±12 .40 。正常新生儿HPS的功率谱特征参数为:超低频带功率(PVV) 626.89 ±496.42 MS2 ; 低频带功率(PVL):251 .35 ±170.31 MS2 ;高频带功率(PVH) 148.97±128.57 MS2 ;超低频带相对功率(PRV) 57 .54 % ±15 .68% ;低频带相对功率(PRL) 26.68% ±10.15% ;高频带相对功率(PRH) 15 .15 % ±7 .37 % ;超低频带与高频带功率比(RVH) 5 .53 ±4.48;低频带与高频带功率比(RLH) 1.99±0.? Objective To analyze chaotic characteristics of heart period signals (HPS) in normal neonates. Methods 512 HPS from 73 normal neonates were collected to analyze their chaotic characteristics using a computerized system. Results Four parameters of chaotic characteristics were calculated: HPS relative dispersion (6.33±1.87), HPS lyapunov exponent (3.17±0.71), HPS fractal dimension (1.83±0.04), and heart cycle chaosness (19.99±12.40). The power value and power rate of HPS in very low (626.89±496.42 MS 2 and 57.54%±15.68%), low (251.35±170.31 MS 2 and 26.68%±10.15%), and high frequency bands (148.97±128.57 MS 2 and 15.15%±7.37%) were analyzed respectively, with a total frequency band power of 1062.17±696.60 MS 2. The power value ratios of very low/high (5.53±4.48) and low/high frequency bands (1.99±0.93) were also calculated. Conclusions Comparing the data with those of adults, we found lower chaotic characteristics of HPS in neonates with a higher power rate in the very low frequency band. The results suggest that the complexity of the heart state and the controlling ability of the autonomic nervous system to the heart are lower and that the interaction component is predominant comparatively in normal neonates.
出处 《中国当代儿科杂志》 CAS CSCD 1999年第5期257-260,共4页 Chinese Journal of Contemporary Pediatrics
关键词 心动周期信号 HPS 正常新生儿 参考值 MS HLE HCC 相对 提示 目的 Neonate Heart period Chaotic characteristics Power spectrum
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