自回归谱模型的运动员心音频谱特征研究  

Study on heart sound spectral features for athletes using autoregressive power spectrum model

作　　者：郭兴明[1] 卢德林[1] 汤丽平[1] 

机构地区：[1]重庆大学生物工程学院,重庆400044

出　　处：《计算机工程与应用》2013年第7期106-110,共5页Computer Engineering and Applications

基　　金：中央高校基本科研业务费"研究生科技创新基金"项目(No.CDJXS11230049)

摘　　要：S1/S2指标是表征心肌收缩能力的重要标志,为从频域角度来了解运动对运动员心肌收缩功能的影响,将运动员和普通大学生在运动前后的心音信号纳入到自回归功率谱中加以研究。通过分析运动员组和普通大学生组心音次频段(<20Hz)范围的自回归功率谱曲线,发现在该频段范围两组之间的心音频谱存在显著的差异性,因此,提出了两个新的评估的指标R值和A值。结果显示,运动前后两组之间的特征参数R值和A值存在显著性差异(P<0.05),且两组之间的特征值与指标S1/S2有显著的相关性(P<0.01)。这表明通过频域的角度所提出的两个特征参数可以用于评估运动员心脏功能状态和心肌的收缩能力。S1/S2 is an important index which reflects the cardiac contractility. In order to study the influence of sports on the cardiac contractility from the viewpoint of frequency domain, heart sounds of athlete group and general college student group in pre-exercise and post-exercise have been processed using autoregressive power spectrum model. Significant difference is found between the two groups of the heart sound spectral curve in frequency domain by analyzing the autoregressive power spectral curve in the range of subbands （〈20 Hz）. Therefore, two new evaluation index R and A are proposed. The results show that index R and A of the two groups have significant differences （P〈0.05） in pre-exercise and post-exercise, and have significant correlation （P〈0.01） with the index S1/$2. This suggests that two characteristic parameters proposed from the angle of frequency domain can be used to evaluate the heart function state of athlete and cardiac contractility.

关 键 词：心音 自回归谱模型 心肌收缩能力 次频段 S1 S2指标 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] TM711[自动化与计算机技术—计算机科学与技术]