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心电信号多形态T波检测方法研究 被引量:4

Study on Detection Method of T Waves with Different Morphologies in Electrocardiogram
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摘要 目的研究一种T波检测新方法,以提高检测形态异常T波的准确率。方法基于小波变换和支持矢量机技术,设计了一种准确性高且适用于检测心电信号多形态T波的新方法,并从QT数据库下载了50组真实心电信号中5000个形态多样的T波数据验证新方法的性能。结果将实验结果与库中专家标注的信息对比,在误差容忍度20 ms内,检测准确率达到96.38%,敏感度达到98.04%,阳性预测率达到100%。与现有其他类似方法比较,新方法的平均检测精确度和敏感度分别高出6.73%和4.48%。结论本文方法对于各种形态的T波均具有高的检测准确率,且具有良好的抗噪性和可扩展性。 Objective To propose a novel T wave detection method for increasing the detection accuracy of T waves with abnormal morphologies. Methods Based on wavelet transform and support vector machine technolo- gy, a new method for detecting T waves with different morphologies in electrocardiogram (ECG) was pro- posed. The 5000 beat data from 50 sets of real ECG signals with various T wave morphologies downloaded from the QT database were applied to validate the proposed method. Results Compared with the results annotated by the cardiologists on QT database, the accuracy, sensitivity and positive predictive accuracy were 96.38%, 98.04% and 100% respectively with the error tolerance being of 20 ms. The average detection accuracy and sensitivity were 6.73% and 4.48% higher respectively than those of other related methods. Conclusion The novel method is of high accuracy to detect T waves with various morphologies and has good scalability and noise immunity.
出处 《航天医学与医学工程》 CAS CSCD 北大核心 2013年第4期295-298,共4页 Space Medicine & Medical Engineering
基金 国家自然科学基金资助项目(81171411)
关键词 T波检测 形态 小波变换 支持矢量机 T wave detection morphology wavelet transform support vector machine
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  • 1葛丁飞,邵宇权,蒋惠忠.基于双导联ECG和多变量回归模型的远程心电诊断算法研究[J].航天医学与医学工程,2004,17(5):355-359. 被引量:6
  • 2李娜,郑晓势,李士锋.一种基于小波变换的自适应图像水印算法[J].计算机工程,2006,32(19):167-169. 被引量:5
  • 3刘家胜,黄贤武,朱灿焰,张燕,吕皖丽.基于m序列整数调制和置乱的图像加密算法[J].计算机应用,2007,27(1):118-121. 被引量:3
  • 4Jang D S,Ho Seok Moon,Taewoo You,et al.Expert System for Low Frequency Adaptive Image Watermarking:Using Psychological Experiments on Human Image Perception[J].Expert Systems with Applications,2007,32(2):674-686.
  • 5Zhang Xinpeng,Wang Shuozhong.Watermarking Scheme Capable of Resisting Sensitivity AUack[J].IEEE Signal Processing Leach,2007,14(2):125-128.
  • 6Chang Chinchen,Tai Weifiang,Lin Chiachen.A Multipurpose Wavelet-based Image Watermarking[C]//Proc.of the 1st International Conference on Innovative Computing,Information and Control.Beijing.China:[s.n.],2006.
  • 7陈国良,王熙法,庄镇泉,等.遗传算法及其应用[M].北京:人民邮电出版社,2003.
  • 8Unser M. A review of wavelets in biomedical applicatlos[J]. Proc of IEEE, 2004,84(4) :870- 872.
  • 9Pedrycz W. Fuzzy neural networks with reference neurons as pattern classifiers [ J ]. IEEE Trans on Neural Networks, 2000,3 ( 5 ) : 770 - 775.
  • 10Mallat S. The. singularity detection and processing with wavelets [J]. IEEE Trans Information Theory, 2002, 76(5) :962 - 963.

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