A low-complexity data-adaptive approach for premature ventricular contraction recognition

Signal, Image and Video Processing

Volumn 8, Issue 1, 2014, Pages 111-120

  Li, Peng ^a   Liu, Chengyu ^a   Wang, Xinpei ^a   Zheng, Dingchang ^b   Li, Yuanyang ^c   Liu, Changchun ^a  

^a SHANDONG UNIVERSITY   (China)

^b NEWCASTLE UNIVERSITY   (United Kingdom)

^c SHANDONG PROVINCIAL HOSPITAL AFFILIATED TO SHANDONG UNIVERSITY   (China)

Author keywords

Data adaptive; Electrocardiogram (ECG); Low complexity; Premature ventricular contraction (PVC); Template matching

Indexed keywords

CORRELATION COEFFICIENT; DATA-ADAPTIVE; GENERALIZATION CAPABILITY; LOW-COMPLEXITY; PREMATURE VENTRICULAR CONTRACTION; REAL-TIME APPLICATION; ROBUSTNESS AGAINST NOISE; STATE-OF-THE-ART METHODS;

DATABASE SYSTEMS; FACE RECOGNITION; TEMPLATE MATCHING;

ELECTROCARDIOGRAPHY;

EID: 84891885335     PISSN: 18631703     EISSN: 18631711     Source Type: Journal    
DOI: 10.1007/s11760-013-0478-6     Document Type: Article

References (25)

1. Clifford, G. D., Moody, G. B.: Signal quality in cardiorespiratory monitoring. Physiol. Meas. 33(9), E01 (2012).
2. Nikita, K. S., Lin, J. C., Fotiadis, D. I., Arredondo, M. T.: Editorial: special issue on mobile and wireless technologies for healthcare delivery. IEEE Trans. Biomed. Eng. 59(11), 3083-3089 (2012).
3. Iwasa, A., Hwa, M., Hassankhani, A., Liu, T., Narayan, S. M.: Abnormal heart rate turbulence predicts the initiation of ventricular arrhythmias. Pacing Clin. Electrophysiol. 28(11), 1189-1197 (2005).
4. Liu, C. Y., Liu, C. C., Shao, P., Li, L. P., Sun, X., Wang, X. P., Liu, F.: Comparison of different threshold values r for approximate entropy: application to investigate the heart rate variability between heart failure and healthy control groups. Physiol. Meas. 32(2), 167-180 (2011).
5. Liu, C. Y., Li, L. P., Zhao, L. N., Zheng, D. C., Li, P., Liu, C. C.: A combination method of improved impulse rejection filter and template matching for identification of anomalous intervals in electrocardiographic RR sequences. J. Med. Biol. Eng. 32(4), 245-250 (2012).
6. Hu, Y. H., Palreddy, S., Tompkins, W. J.: A patient-adaptable ECG beat classifier using a mixture of experts approach. IEEE Trans. Biomed. Eng. 44(9), 891-900 (1997).
7. Zhang, X., Zhu, Y., Thakor, N. V., Wang, Z.: Detecting ventricular tachycardia and fibrillation by complexity measure. IEEE Trans. Biomed. Eng. 46(5), 548-555 (1999).
8. Lagerholm, M., Peterson, C., Braccini, G., Edenbrandt, L., Sornmo, L.: Clustering ECG complexes using Hermite functions and self-organizing maps. IEEE Trans. Biomed. Eng. 47(7), 838-848 (2000).
9. de Chazal, P., O'Dwyer, M., Reilly, R. B.: Automatic classification of heartbeats using ECG morphology and heartbeat interval features. IEEE Trans. Biomed. Eng. 51(7), 1196-1206 (2004).
10. Shyu, L. Y., Wu, Y. H., Hu, W.: Using wavelet transform and fuzzy neural network for VPC detection from the holter ECG. IEEE Trans. Biomed. Eng. 51(7), 1269-1273 (2004).
11. Sun, Y., Chan, K. L., Krishnan, S. M.: Life-threatening ventricular arrhythmia recognition by nonlinear descriptor. Biomed. Eng. Online 4(1), 6 (2005).
12. de Chazal, P., Reilly, R. B.: A patient-adapting heartbeat classifier using ECG morphology and heartbeat interval features. IEEE Trans. Biomed. Eng. 53(12), 2535-2543 (2006).
13. Inan, O. T., Giovangrandi, L., Kovacs, G. T. A.: Robust neural-network-based classification of premature ventricular contractions using wavelet transform and timing interval features. IEEE Trans. Biomed. Eng. 53(12), 2507-2515 (2006).
14. Lim, J. S.: Finding features for real-time premature ventricular contraction detection using a fuzzy neural network system. IEEE Trans. Neural Netw. 20(3), 522-527 (2009).
15. Homaeinezhad, M. R., Tavakkoli, E., Ghaffari, A.: Discrete wavelet-based fuzzy network architecture for ECG rhythm-type recognition: feature extraction and clustering-oriented tuning of fuzzy inference system. Int. J. Signal Proces. Image Process. and Pattern Recognit. 4(3), 107-130 (2011).
16. Llamedo, M., Martinez, J. P.: Heartbeat classification using feature selection driven by database generalization criteria. IEEE Trans. Biomed. Eng. 58(3), 616-625 (2011).
17. Zhou, H., Hou, K. M., Ponsonnaille, J., Gineste, L., De Vaulx, C.: A real-time continuous cardiac arrhythmias detection system: RECAD. In: Proceedings of 27th Annual International Conference of the Engineering in Medicine and Biology Society. Shanghai, China, pp. 875-881, 17-18 Jan 2005.
18. Hu, S., Wei, H., Chen, Y., Tan, J.: A real-time cardiac arrhythmia classification system with wearable sensor networks. Sensors 12(9), 12844-12869 (2012).
19. Goldberger, A. L., Amaral, L. A., Glass, L., Hausdorff, J. M., Ivanov, P. C., Mark, R. G., Mietus, J. E., Moody, G. B., Peng, C. K., Stanley, H. E.: PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23), E215-220 (2000).
20. Moody, G. B., Mark, R. G.: The impact of the MIT-BIH arrhythmia database. IEEE Eng. Med. Biol. Mag. 20(3), 45-50 (2001).
21. Berger, R. D.: QT variability. J. Electrocardiol. 36(Suppl), 83-87 (2003).
22. Li, P., Liu, C. Y., Liu, C. C., Sun, H., Yang, J., Ma, G. Q.: Higher order spectra for heart rate variability and QT interval variability analysis: a comparison between heart failure and normal control groups. In: Computing in Cardiology, Hangzhou, China, pp. 309-312, 18-21 Sep 2011.
23. Goh, K. W., Lavanya, J., Kim, Y., Tan, E. K., Soh, C. B.: A PDA-based ECG beat detector for home cardiac care. In: Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society. Shanghai, China, pp. 375-378, 17-18 Jan 2005.
24. Tabakov, S., Iliev, I., Krasteva, V.: Online digital filter and QRS detector applicable in low resource ECG monitoring systems. Ann. Biomed. Eng. 36(11), 1805-1815 (2008).
25. Li, P., Liu, C. C., Zhang, M., Che, W. B., Li, J.: A real-time QRS complex detection method. Acta Biophys. Sin. 27(3), 222-230 (2011).