TY - JOUR
T1 - A combination method of improved impulse rejection filter and template matching for identification of anomalous intervals in RR sequences
AU - Liu, Chengyu
AU - li, Liping
AU - Zhao, Lina
AU - Zheng, Dingchang
AU - Li, Peng
AU - Liu, Changchun
PY - 2012
Y1 - 2012
N2 - Anomalous intervals in RR sequences of electrocardiogram (ECG) introduce practical problems in heart rate variability (HRV) analysis, trauma evaluation, and other clinical applications where ECG artifact rejection is important. Impulse rejection filters (IRFs) have been used to identify anomalous intervals. However, traditional IRFs do not consider the influence of non-stationary time series of RR intervals, and cannot effectively identify anomalous intervals caused by ECG morphology changes. This study therefore improves the traditional IRF method, develops an ECG morphology feature-based template matching method, and develops a combination method of improved IRF and template matching for better identification of anomalous intervals in RR sequences. Four methods (IRF, improved IRF, template matching, and the combination method of improved IRF and template matching) are applied to the MIT-BIH arrhythmia database. 43 RR sequences that contain 30368 normal intervals and 2760 anomalous intervals are analyzed. Sensitivity and specificity analyses are performed to quantify identification performance. The sensitivity and specificity values are 86.1% and 87.0% for IRF, 92.3% and 94.9% for improved IRF, 90.7% and 95.5% for template matching, and 98.5% and 99.2% for the combination method, respectively. The results verify that the combination method is suitable for the identification of anomalous RR intervals.
AB - Anomalous intervals in RR sequences of electrocardiogram (ECG) introduce practical problems in heart rate variability (HRV) analysis, trauma evaluation, and other clinical applications where ECG artifact rejection is important. Impulse rejection filters (IRFs) have been used to identify anomalous intervals. However, traditional IRFs do not consider the influence of non-stationary time series of RR intervals, and cannot effectively identify anomalous intervals caused by ECG morphology changes. This study therefore improves the traditional IRF method, develops an ECG morphology feature-based template matching method, and develops a combination method of improved IRF and template matching for better identification of anomalous intervals in RR sequences. Four methods (IRF, improved IRF, template matching, and the combination method of improved IRF and template matching) are applied to the MIT-BIH arrhythmia database. 43 RR sequences that contain 30368 normal intervals and 2760 anomalous intervals are analyzed. Sensitivity and specificity analyses are performed to quantify identification performance. The sensitivity and specificity values are 86.1% and 87.0% for IRF, 92.3% and 94.9% for improved IRF, 90.7% and 95.5% for template matching, and 98.5% and 99.2% for the combination method, respectively. The results verify that the combination method is suitable for the identification of anomalous RR intervals.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-84867417080&partnerID=MN8TOARS
U2 - 10.5405/jmbe.1006
DO - 10.5405/jmbe.1006
M3 - Article
SN - 2199-4757
VL - 32
SP - 245
EP - 250
JO - Journal of Medical and Biological Engineering
JF - Journal of Medical and Biological Engineering
IS - 4
ER -