Chinese Journal of Tissue Engineering Research ›› 2010, Vol. 14 ›› Issue (39): 7353-7357.doi: 10.3969/j.issn.1673-8225.2010.39.032

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Arrhythmia recognition using a BP neural network-based DNA algorithm

Shi Li, Zhao Yun, Guo Bao   

  1. School of Electrical Engineering, Zhengzhou University, Zhengzhou  450001, Henan Province, China　
  • Online:2010-09-24 Published:2010-09-24
  • Contact: Zhao Yun, Master, School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, Henan Province, China zhaoyun_zzu@163.com
  • About author:Shi Li☆, Doctor, Doctoral supervisor, Professor, School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, Henan Province, China shili@zzu.edu.cn
  • Supported by:

    the National Natural Science Foundation of China, No. 60841004*, 60971110*

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Abstract:

BACKGROUND: Arrhythmia is commonly diagnosed by doctors, and the diagnosis depends on doctor experience and responsibility. Arrhythmia recognition is great important for rescuing and early treatment of cardiopathy sufferers.
OBJECTIVE: To investigate efficient method of auto-recognizing and diagnosis of arrhythmia.
METHODS: The whole morphology of arrhythmic heartbeat was extracted from electrocardiograph (ECG), and discrete cosine transform and inverse discrete cosine transform were used to compress the data. A BP neural network was designed for arrhythmic heartbeat recognition, and the initial weights and thresholds of network were optimized by DNA algorithm. Finally, the MIT/BIH ECG database was used to test the DNA-BP neural network.
RESULTS AND CONCLUSION: For the five types heart beat, including normal, left bundle branch block, right bundle branch block, ventricular escape heartbeat, Paced heartbeat, the experiment results demonstrate efficient by using DNA-BP neural network, with an average recognition rate of 99%.

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