DocumentCode :
167905
Title :
Ventricular Fibrillation Detection by an Improved Time Domain Algorithm Combined with SVM
Author :
Zhongjie Hou ; Yue Zhang
Author_Institution :
Lab. of Embedded Syst. & Technol., Tsinghua Univ., Shenzhen, China
fYear :
2014
fDate :
May 30 2014-June 1 2014
Firstpage :
189
Lastpage :
194
Abstract :
Correct detection of ventricular fibrillation (VF) is of great importance to real-time electrocardiogram (ECG) monitoring systems and automatic external defibrillator (AED). First, the paper gives a brief review of threshold crossing sample count algorithm (TCSC), and analyzes this algorithm´s drawbacks. Then the authors present an improved algorithm combined TCSC with support vector machine (SVM), which is more accuracy than the TCSC algorithm. For assessment of the performance of the algorithm, the complete CU database and MIT-BIH database are used. The authors compare the new algorithm with other VF detection methods under the same conditions. The ROC curve is created and the AUC is also calculated. The results show that the proposed algorithm has a high Accuracy of 91.2%, Specificity of 96.8%, and the AUC is 92.5. The new algorithm is fast, accurate and reliable, showing strong potential to be applied in real-time ECG monitor system.
Keywords :
diseases; electrocardiography; medical signal processing; patient monitoring; sensitivity analysis; support vector machines; time-domain analysis; MIT-BIH database; ROC curve; SVM; VF detection methods; automatic external defibrillator; complete CU database; improved time domain algorithm; real-time ECG monitor system; real-time electrocardiogram monitoring systems; support vector machine; threshold crossing sample count algorithm; ventricular fibrillation detection; Algorithm design and analysis; Classification algorithms; Electrocardiography; Fibrillation; Power capacitors; Support vector machines; Thyristors; arrhythmia classification; support vector machine; threshold crossing sample count algorithm; ventricular fibrillation; ventricular fibrillation detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Medical Biometrics, 2014 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4799-4014-1
Type :
conf
DOI :
10.1109/ICMB.2014.39
Filename :
6845848
Link To Document :
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