DocumentCode :
1700172
Title :
A novel multi-resolution SVM (MR-SVM) algorithm to detect ECG signal anomaly in WE-CARE project
Author :
Qian Zheng ; Chao Chen ; Zhinan Li ; Anpeng Huang ; Bingli Jiao ; Xiaohui Duan ; Linzhen Xie
Author_Institution :
Center for Wireless Commun. & Signal Process., Peking Univ., Beijing, China
fYear :
2013
Firstpage :
1
Lastpage :
6
Abstract :
Cardiovascular disease (CVD) has become the leading cause of human deaths today. In order to combat this disease, many professionals are using mobile electrocardiogram (ECG) remote monitoring system. While using mobile ECG systems, most of the cardiac anomalies can be observed, especially when serious myocardial ischemia, heart failure, and malignant arrhythmia occur. Thus, ECG anomaly detection and analysis have attracted more and more attention in the clinical and research communities. Currently, the existing solutions of ECG automatic detection and analysis technologies are challenged by an accuracy requirement. Based on this motivation, we propose a novel Multi-Resolution Support Vector Machine (MR-SVM) algorithm to detect ECG waveform anomaly. This proposal is tested in our WE-CARE (a Wearable Efficient telecardiology system) project. Clinical trials and experimental results show that the algorithm can successfully extract original QRS complex waves and T waves regardless of noise magnitude and distinguish the ST segment morphological anomalies. Compared with European standard ST-T database, our solution can achieve the average T wave recognition accuracy rate of 97.5% and ST anomaly detection accuracy rate of 93%.
Keywords :
diseases; electrocardiography; medical disorders; medical signal processing; signal resolution; support vector machines; telemedicine; ECG anomaly detection; ECG automatic detection; ECG signal anomaly; ECG waveform anomaly; European standard ST-T database; MR-SVM algorithm; QRS complex T waves; ST anomaly detection accuracy rate; ST segment morphological anomalies; WE-CARE project; average T wave recognition accuracy rate; cardiac anomalies; cardiovascular disease; heart failure; malignant arrhythmia; mobile ECG remote monitoring system; mobile electrocardiogram remote monitoring system; multiresolution SVM algorithm; multiresolution support vector machine algorithm; myocardial ischemia; wearable efficient telecardiology system project; Accuracy; Algorithm design and analysis; Electrocardiography; Multiresolution analysis; Signal processing algorithms; Signal resolution; Support vector machines; ECG; MR-SVM; QRS Complex; Recognition Accuracy; T Wave;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biosignals and Biorobotics Conference (BRC), 2013 ISSNIP
Conference_Location :
Rio de Janerio
ISSN :
2326-7771
Print_ISBN :
978-1-4673-3024-4
Type :
conf
DOI :
10.1109/BRC.2013.6487453
Filename :
6487453
Link To Document :
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